The global prevalence of obesity and type 2 diabetes is increasing and these chronic metabolic disorders are associated with dysregulation of multiple signaling pathways, including those involving dopamine. Dopamine receptor D2 (DRD2) is a low-abundance G protein-coupled receptor expressed in adipose tissue and involved in the regulation of energy metabolism, insulin secretion and reward-related eating behavior, making its reliable detection and quantification in biological samples relevant to metabolic disease research. Western blot is a widely used technique for protein detection, but its sensitivity is limited by the signal generation capacity of conventional detection systems, which may be insufficient for low-abundance targets such as DRD2. Binding Oligo Ladder Detection (BOLD) is a signal amplification strategy based on polymerization and incorporation of bromodeoxyuridine triphosphate (BrdUTP) into a DNA/RNA strand conjugated to secondary antibody, enabling the detection of the DNA/RNA strand by anti-BrdUTP tertiary antibody. This study investigated the feasibility of integrating BOLD into a Western blot workflow for DRD2 detection in adipose tissue cell lysate. Two goat anti-rabbit secondary antibodies were conjugated to an oligonucleotide primer using click chemistry and their biotinylated variants were prepared for comparison. Functionality of conjugates was verified by dot blotting, which also demonstrated that BOLD produced signal amplification superior to that of biotinylated antibody-based detection at low antigen concentrations, providing proof of concept for the detection system. Western blot experiments were performed to evaluate detection performance, investigate background signal, optimize conditions and benchmark BOLD against conventional methods. In the initial Western blot, one oligonucleotide-conjugated secondary antibody achieved signal-to-noise ratio comparable to standard detection with an HRP-conjugated secondary antibody, while the other underperformed, suggesting that click chemistry configuration affects conjugate performance. Persistent background signal was observed across experiments and was attributed primarily to non-specific binding of HRP-conjugated anti-BrdUTP tertiary antibody (with residual primer as a possible additional contributing factor). Reducing the tertiary antibody concentration substantially improved signal-to-noise ratio. EveryBlot Blocking Buffer was identified as the most favorable blocking strategy for oligo-dT-conjugated antibodies, while PVDF membranes were incompatible with BOLD under the tested conditions. In benchmarking, a standard HRP-conjugated secondary antibody outperformed both oligonucleotide-conjugated and biotinylated secondary antibodies in signal intensity, signal-to-noise ratio and detection sensitivity. However, as the HRP-conjugated secondary antibody was of a different clone than the oligo-dT-conjugated and biotinylated antibodies, differences in binding affinity may have contributed to the observed performance difference. These findings demonstrate that BOLD is feasible in a Western blot workflow and shows promising signal amplification potential. Repeating the benchmarking experiment at optimized conditions for BOLD using the existing antibodies is recommended as an immediate next step, alongside obtaining an unmodified variant of the HRP-conjugated goat anti-rabbit antibody to enable comparison of HRP- and oligo-dT-conjugated variants of this antibody clone. 

The global energy sector is undergoing a profound digital transformation driven by growing demands for sustainability, efficiency, and resilience. The shift from traditional power grids to smart, decentralized energy systems has accelerated the adoption of artificial intelligence (AI)-enabled Energy Management Systems (EMS). While these technologies offer significant benefits, they also introduce new data security and governance challenges that must be addressed to ensure trustworthy and resilient energy infrastructure. This study adopts a Design Science Research (DSR) approach to investigate security issues associated with the development and implementation of AI-enabled EMS. Through an analysis of academic and practice-oriented literature, a conceptual framework was developed that takes a lifecycle perspective, tracing data flows through interconnected phases of data generation, sensing, model development, and deployment. Based on the identified challenges, four design principles were formulated to address specific security vulnerabilities. The primary outcome is a conceptual artifact that categorizes data security challenges in AI-enabled EMS across different lifecycle phases. The analysis revealed that these challenges require coordinated action by multiple stakeholders across different system layers, supported by dedicated security tools and governance mechanisms. The study proposes the Prevent–Audit–Learn–Harden (PALH) framework as a practical approach for guiding the secure design, deployment, and operation of AI-enabled EMS. By linking identified security challenges to corresponding design principles and lifecycle stages, the framework helps strengthen data security and governance in smart energy systems. The findings highlight the importance of a holistic, lifecycle-oriented approach to security in supporting the ongoing transition toward decentralized smart grids.

This study investigates how the design of BI dashboards affects users’ understanding, interpretation,and decision-making, with a focus on cognitive factors that may contribute to difficulties in their use.The study was conducted in collaboration with the IT consulting company Elvenite and focused ontheir internal dashboards used by people managers to monitor consultants. Data collection was carriedout in several stages and included a preliminary study and a main study. These phases involvedmethods such as interviews, usability testing, thematic analysis, HTA, and NASA-TLX to examineperceived workload. Based on the results, a prototype of a BI dashboard was developed andsubsequently usability tested and analyzed in a manner equivalent to the main study. The results showthat the existing dashboard was perceived as somewhat complex and difficult to overview, whichcontributed to increased cognitive load and difficulties in interpreting information. The developedprototype was perceived as more intuitive, clear, and user-friendly. The study demonstrates that factorssuch as visual structure, information hierarchy, interaction design, and mental models are of greatimportance for the use of BI dashboards. By considering these aspects, usability can be improved andthe conditions for data-driven decision-making can be strengthened.

Region Östergötland is looking to expand their already established infection tracking tool to accommodate incidents with risk of blood contamination due to current tracking using a limited tool that is susceptible to security risks. To develop an effective and usable tool that can aid the infection tracking process, needs, requirements and context of usage must be identified. The study uses the Research through Design approach where design activities aim to generate knowledge. By which a three-phase human-centered design process was used to first gather information, develop and test main features of the tool and then create a highly detailed extensive prototype of an infection tracking tool.

The study identified informational needs of the tool based on the information required by the already used existing tool which outlined what information is to be noted and how. Needs were then identified from interviews which described the need of offload cognitive intention, functions that can aid remembering and the capability of representing certain information as statistics. Lo-Fi prototypes were developed to evaluate different alternative implementations that fulfilled identified needs and requirements based on efficiency usability metric and suitability to the context. After deciding upon the main features, a Hi-Fi prototype was developed which gave insights on the integration of different functionalities and features. The study produced a Hi-Fi prototype that can aid   infection tracking of incidents with risk of blood contamination, however usability tests with related healthcare workers is highly encouraged for future work.

This study examines why static PDF timetables are still used by travellers of public transport despite the widespread availability of digital journey planners and real-time information. The aim is to understand how travellers use timetables and what value they perceive them to have in relation to other information channels. 

The study was conducted using a mixed-method approach in which ten semi-structured interviews were combined with a survey answered by 359 respondents. The interviews were analysed thematically to identify recurring patterns in use and experiences. Survey data was analysed using descriptive statistics to examine how common these patterns are. 

The results show that timetables are primarily used during the planning phase before travelling, particularly for new or more complex journeys. Timetables are perceived to provide an overview of the transport system and to make it possible to identify relationships between departures, stops and frequency in ways that are difficult to achieve in search-based systems. Timetables are often used together with other information channels, where journey planners are used for quick decisions while timetables are used to create mental models and compare alternatives. At the same time, some limitations are highlighted such as timetables being perceived as difficult to read and lacking real-time information. 

The results suggest that timetables fulfil a distinct function as cognitive support. The study contributes to a broader understanding of how different information representations influence travellers’ ways of planning and understanding public transport systems, which may have implications for the future design of digital information systems. 

Procrastination is widespread and closely tied to well-being, stress, and academic and work performance. This explorative study investigates potential risks of using large language model chatbots to treat procrastination, as well as design approaches that could mitigate these risks. Experts in three areas, psychology, language technology, and human-computer interaction, were interviewed, and thematic analysis was conducted on the resulting material. Five themes emerged, concerning individual adaptation, engagement and motivation, alignment and feedback, social factors, and anthropomorphism. Key risks include alignment conflicts between general and specialised chatbots, loss of social accountability, anthropomorphism-induced overtrust, and over-generalisation in treatment. Proposed design responses include gradual user modelling, predefined personality presets, simulated accountability mechanisms, language adaptation, and redirection to alternative treatments when appropriate. The study contributes to understanding the specific challenges of using chatbots for procrastination reduction and suggests that while some risks are inherent to the technology, others are addressable through design and warrant consideration by developers.

This thesis investigates praxeological differences among the mathematics tracks 1a, 1b, and 1c through a textbook analysis of the topic of functions in the Matematik 7000 textbook series. The study is grounded in the Anthropological Theory of the Didactic (ATD) and aims to analyze how mathematical activities are expressed in textbooks and how these may be related to differences in the curriculum documents governing the three mathematics tracks in Swedish upper secondary school. To facilitate the analysis, an epistemological reference model was constructed, consisting of four praxeological elements: task types, techniques, technology, and theory. The model was developed based on the introductory chapters of the textbooks as well as the regulatory documents for mathematics levels 1a, 1b, and 1c. The empirical material comprises all tasks included in the chapter on functions in the analyzed textbooks. The tasks were categorized according to the reference model, and the results were presented using contingency tables and statistical analyses employing chi-square tests with Holm–Bonferroni correction and Cramér’s V. The findings show that the textbooks for mathematics levels 1b and 1c exhibit substantial similarities across all analyzed categories, whereas the textbook for level 1a differs primarily with respect to task types, techniques, and technology. Despite the statistically significant differences, the effect sizes, as measured by Cramér’s V, are small.

Furthermore, the study demonstrates that Mathematics Level 1a contains a higher proportion of context-based problem-solving tasks, while levels 1b and 1c place greater emphasis on reasoning-oriented and concept-oriented tasks. This finding partially contrasts with the curriculum documents, in which mathematics level 1a emphasizes concepts related to working life and vocational applications; however, the textbook exhibits a weaker conceptual focus than the textbooks for mathematics levels 1b and 1c. The analysis also highlights how didactic transposition may result in the knowledge presented in textbooks not fully corresponding to the selected knowledge articulated in the curriculum documents. The study thus contributes to a deeper understanding of how mathematics tracks represent mathematical practices and how textbooks influence the content and character of mathematics instruction.

This report presents a current-state analysis of research on how municipalities and companies work with sustainable transition, with a focus on circularity and climate pledges, complemented by empirical insights from actors in the Västra Götaland region (companies: climate pledges 12–17; municipalities: climate pledges 23, 24, 25, 27). The report has been produced within Work Package 2 (led by Linköping University) in the project Circular Climate Pledges – Application and Needs Analysis, coordinated by Lindholmen Science Park.

Previous research shows that circular initiatives in both the public and private sectors are often driven by strong ambitions but are characterized by fragmented implementation, where pilot projects dominate and integration into core operations remains limited. Success is closely linked to factors such as clear governance, collaboration, competence, and access to resources, while barriers often relate to organizational silos, lack of incentives, uncertainty in markets and regulatory frameworks, and limited capacity. Overall, the research indicates that the transition is systemic and requires both internal changes and the development of external support systems in order to be scaled up.

The analysis of the empirical insights shows that both municipalities and companies use climate pledges to structure and legitimize sustainability work, but often underestimate the complexity of implementation, which requires increased collaboration, coordination, and support. At the same time, the drivers and challenges differ—municipalities are more shaped by organizational and political issues, while companies are influenced by markets and value chains—but both face similar systemic barriers.

Finally, the recommendations for municipalities, companies, and support actors emphasize that circular climate pledges need to be integrated into core operations and regular governance, combined with experimentation and planned scaling, and supported by collaboration, cross-functional work, and more coordinated and needs-adapted support systems.

Key takeaways

Circular climate pledges are widely used to structure and legitimize sustainability work, but their implementation is more complex than initially anticipated.Both municipalities and companies depend on coordination, collaboration, and inter-nal champions to translate pledges into practice.Key barriers differ across sectors (organizational and governance challenges in mu-nicipalities; market and value chain constraints in companies), but share similar sys-temic roots.Current efforts are often fragmented and pilot-driven, highlighting the need to inte-grate circular practices into core operations and governance structures.Effective support requires tailored, coordinated, and practice-oriented approaches that enable scaling beyond isolated initiatives.

Denna rapport presenterar resultat och slutsatser från projektet ”Biogasscenarier”, som har finansierats av Energimyndigheten. Projektet utfördes 2022–26 och hade projektnummer P2021-00098. Rapporten analyserar utvecklingen, produktionen och användningen av biogas i Sverige, med betoning på scenarier för en tänkt framtida tillväxt fram till 2035. Den beskriver den historiska utvecklingen från tidigt 1990-tal fram mitten av 2020-talet. Utifrån nuvarande produktionskapacitet, distributionssystem, användningsmönster och sentida utvecklingstrender modelleras därefter möjligheter till expansion på basis av tillgängliga substrat, politiska styrmedel, distribution, och efterfrågan från olika användarsegment. Två scenarier för produktion modelleras: Business-as-usual med måttlig expansion, samt Planned and pledged där produktionskapaciteten mer än fördubblas fram till 2035. Den stora ökningen av produktionskapacitet i det senare scenariot möjliggörs framför allt av en väsentligt ökad användning av gödsel som substrat.

Efterfrågan på biogas förväntas öka inom transportsektorn, och då särskilt tunga lastbilar, men biogas förväntas också att få en allt större roll inom sjöfart. Dessutom förväntas efterfrågan från industrin att öka. I samtliga förväntade tillväxtsegment efterfrågas framför allt vätskeformig gas, vilket leder till ett krav på storskalighet i produktion för att möjliggöra förvätskning. Samtidigt leder behovet av att nyttja mer lågvärdiga och geografiskt spridda substrat såsom gödsel till att det kan bli allt svårare att etablera centraliserad produktion med stora anläggningar.

En positiv marknadsutveckling för biogas i Sverige beror på samordnade insatser för att möjliggöra handel, att utveckla system för produktion, distribution och användning, och att utforma en berättelse om biogas som motiverar engagemang och investeringar. I detta sammanhang har nationell försörjningstrygghet kommit till som ytterligare ett argument, vid sidan om existerande miljö- och klimatrelaterade argument för satsningar på biogas. Långsiktigt politiskt stöd är avgörande för en stabil tillväxt av biogasproduktion och biogasanvändning. Detta inbegriper åtgärder för att underlätta internationell handel.

In this report, the principles of satellite navigation are analyzed and described, with a primary focus on the NAVSTAR global positioning system. The topics covered include satellite components, signal structure, trilateration and relativistic effects. Orbital information is described using Keplerian elements. A system of equations is set up to determine both the position and the receiver´s clock error using signals from multiple satellites. The results show how the positioning problem can be solved mathematically, and that accurate positioning requires accounting for relativistic effects like time dilation and the Sagnac effect. These are derived and computed. In addition to this report, four satellite navigation systems are visualized in both 2D and 3D with an accompaning user manual available in a Gitlab repository https://gitlab.liu.se/embfr688/satellit

This study investigates whether integrating tabular clinical data with histopathological whole slide image (WSI) features improves classification performance for pediatric central nervous system (CNS) tumors, using the Children’s Brain Tumor Network (CBTN) dataset. Five tumor types are classified, including low-grade glioma (LGG), high-grade glioma (HGG), medulloblastoma (MB), ependymoma (EP), and ganglioglioma (GG), spanning 513 patients and 1,054 hematoxylin and eosin (H&E)-stained WSIs.

WSI features were extracted using the contrastive learning from captions for histopathology (CONCH) foundation model and classified with the clustering- constrained-attention multiple-instance learning (CLAM) framework. Three tabular variables were considered, patient age at diagnosis, biological sex, and Ki-67 proliferation index. Six multimodal fusion strategies were evaluated, comprising three early fusion methods (concatenation, cross-gate, and FiLM) and three late fusion methods (probabil- ity averaging, weighted averaging, and meta-learner stacking), each tested across seven tabular feature combinations (age, sex, Ki-67, age + sex, age + Ki-67, sex + Ki-67, and age + sex + Ki-67), resulting in 42 configurations in total.

The image-only baseline achieved a balanced accuracy of 0.76±0.05. The tabular-only baseline performed substantially lower at 0.45±0.05, suggesting that clinical tabular variables alone are insufficient for reliable classification. Both early and late fusion improved over the image-only baseline, with five out of six configurations achieving statistically significant improvements after Bonferroni correction. The best early fusion configuration using concatenation of H&E WSI with age + sex + Ki-67 achieved a balanced accuracy of 0.80 ± 0.05. The best late fusion configuration using meta-learner stacking of H&E WSI with Ki-67 achieved 0.78 ± 0.05. Early fusion outperformed late fusion in terms of balanced accuracy, and was statistically superior in 5 out of 9 pairwise comparisons (three early fusion strategies each compared against three late fusion strategies) after Bonferroni correction. Values are rounded to two decimal places for readability.

In conclusion, Ki-67 was the most informative tabular feature across fusion configurations. Age and sex alone did not consistently improve over the image-only baseline, but in early fusion, combining them with Ki-67 yielded higher balanced accuracy than using Ki-67 alone. Overall, the fusion of age, sex, and Ki-67 with H&E WSI features improves five-class pediatric brain tumor classification, and the choice of fusion strategy is important.

The growth paradigm affects the strategic planning in many of the shrinking municipalities. Motala municipality is, in contrast to the typical shrinking municipalities, a mid-sized city without long-term population decline. The purpose of this study is to analyze the different interpretations of growth that is prominent in the work of public actors involved in Motala municipality’s strategic planning. To find out, we chose to conduct a qualitative interview study where representatives, who work with questions regarding development and growth in Motala municipality, at publicly owned companies have been interviewed. A thematic analysis of the interviews was done with the help of “Growth Machine Theory”. This led to conclusions that point in the direction that the current growth paradigm largely permeates the interpretations of growth that public actors have in the context of strategic planning.

Bakgrund och syfte: I civilsamhället spelar idéburna verksamheter en viktig roll, med sina kärnuppdrag som fokuserar på människans inkludering, utveckling, gemenskapsbyggande och trygghet. Men det ställs allt högre administrativa krav på idéburna verksamheter. Syftet med studien är att undersöka hur medarbetare upplever administrativa strukturer, såsom förbestämda processer, arbetssätt eller system inom organisationen, i förhållande till verksamhetens kärnuppdrag och hur de hanterar kraven.

Metod: Studien baseras på en kvalitativ studie med sju semistrukturerade intervjuer med medarbetare inom olika idéburna verksamheter.

Resultat: Studien visar på olika upplevelser av de administrativa kraven i relation till kärnuppdraget. Organisationer hanterar de krav och förväntningar som ställs från bidragsgivare på olika sätt.

Slutsatser: De administrativa arbetsuppgifterna har ökat och detta påverkar möjligheterna för medarbetarna att arbeta med kärnuppdraget. Genom olika faktorer påverkar kraven de anställdas arbetsmiljö. De idéburna organisationerna är i beroendeställning men saknar rätt förutsättningar att möta de krav och förväntningar som ställs.

Rekommendationer: Det finns ett behov av att utveckla relationen mellan bidragsgivare och idéburna organisationer. Det finns möjligheter att förbättra delar såsom kommunikation, metod och teknik. Nyckelord: idéburen organisation, civilsamhälle, administration, administrativa krav, arbetsbelastning, isoformism.

Moving toward fully autonomous agricultural machinery offers the potential to increase efficiency and reduce human-dependent operations. However, without a reliable method to monitor operating conditions and evaluate the outcome of field work in the harsh farming environment, the use cases of autonomous machinery remains limited. Advanced sensors, such as depth cameras and LiDAR, are easily disturbed by dust and other measuring tools such as soil moisture sensors require physical contact with the soil. To address these limitations the Acconeer A212 radar is investigated in this thesis as a robust alternative to the aforementioned sensors. 

Based on radar data collected from different soil types and moisture levels, five models were developed and compared, employing different strategies for handling and utilizing the data for soil classification. The resulting models demonstrate that soil surface classification is possible. In moisture level comparisons for clay soil, for the best model a weighted F1-score of 0.914 was achieved. Furthermore, when classifying between stony clay soil, stone-free clay soil, and sandy soil, for the best model a weighted F1-score of 0.881 was obtained.

This thesis examines the so-called 'welcome culture', which denotes a brief period of widespread euphoria regarding refugee reception in the Germany of 2015. Newspaper articles, political speeches, legal sources and testimonies from civil society are consulted to reconstruct how asylum and the social relations that arose from it were framed in the German public discourse at the time. Approached as an archival resource documenting how social relations between host society and refugee could be imagined in Germany, the 'welcome culture' is examined for the alternatives it offers to the open xenophobia dominating the contemporary national discourse on asylum. It is argued that throughout the 'welcome culture', refugee reception practices took the form of gift-exchange. Deploying scepticism against unidirectional acts of giving, the symbolic surplus that Germans acquired from gifting asylum is detailed. The thesis finds that the establishment of a gift-relation with refugees functioned as a vital strategy for the German hosts to work on crises that affect the personal, national and civilizational layers of their identity. Refugees, on the other hand, risk being humiliated and stripped of their selfhood through the obligations inscribed into this social relation. While the harm of the egocentric gift-practices that were prevalent throughout the welcome culture is made visible, the possibility of a 'pure gift' of asylum is affirmed. 'Rights' and 'Baseline communism' are introduced as revitalisable frameworks which allow the host society to welcome strangers in need without disciplining or dominating them. 

This thesis examines how Ukraine has been positioned within imperial regimes of knowledge, from Enlightenment temporal hierarchies to contemporary Western representations of the country. The study asks how Western teleological conceptions of historical progress became embedded in imperial practices of governance, classification, and territorial transformation, and how these practices shaped the epistemic positioning of Ukraine. The study traces this history from Leibniz’s plans for Peter I’s Academy of Sciences to the development of imperial universities in Dorpat and Kharkiv. Along the way, it draws on James C. Scott’s ideas about simplification by the state and Timothy Mitchell’s work on technical expertise to show how administrative and technocratic power expanded over time. The central case is the Kakhovka Hydroelectric Power Plant and the flooding of the Great Meadow. The thesis argues that Soviet hydrotechnocracy transformed the hydrosocial lifeworld of the Dnipro region into an object of state calculation. In this thesis, I reconceptualize Spivak’s notion of subalternity and Stoler’s notion of colonial aphasia for the analysis of Soviet hydrotechnical violence in Ukraine. In Spivak’s terms, this process created conditions of subalternisation: local communities lost the material world in which they could reproduce themselves as historical subjects. In Stoler’s terms, colonial aphasia appears at the level of the communities themselves: a traumatic rupture between lived violence and the available language through which this violence could be articulated. The final part of the thesis turns to Ukrainian intellectual and political traditions, including the Kyiv-Mohyla tradition and the Zaporizhian Sich, to challenge inherited narratives that present Ukrainian history through Russian imperial categories. The thesis argues for reading Ukraine as an autonomous historical and epistemic subject, whose political traditions, archives, and landscapes have long been obscured by Russian mediation and Western models of historical development.

This study asks how Greek migrants who moved to Sweden between 2012 and 2024, during the Greek economic crisis and its aftermath, navigate the Swedish labor market, as well as the challenges they have faced and the coping strategies they have used. The study is based on nine qualitative semi-structured interviews with Greek migrants living and working in Sweden. To answer these research questions, the analysis is structured aroung the concepts of labor market integration, human capital, cultural capital, social capital, and belonging. The findings show that labor market integration is a multidimensional process shaped by the interaction of human, cultural, and social capital. Most participants have experienced structural integration into the Swedish labor market, as their formal qualifications and work experience are generally recognized. However, this recognition does not necessarily guarantee equal salaries or opportunities for non-native workers. Language proficiency emerges as the most crucial form of cultural capital, shaping their labor market integration and outcomes. This study also shows that bonding social capital, through ethnic networks, is widely used by participants, whereas bridging social capital is less common. While employment provides the participants with economic stability and future prospects, it does not automatically translate into inclusion or a sense of belonging in Swedish society.

This thesis explores how the Seto community perceives and navigates challenges to identity, cultural continuity and security, and how they relate to change and future uncertainty within a context of a divided homeland and geopolitical tensions. Perspectives on Seto Indigeneity and the influence of current geopolitical insecurity in Setomaa are explored. Seto identity is understood and negotiated across generations, with belonging and cultural continuity shaped by lived experiences, historical and contemporary Seto practices, and attachment to their Indigenous land. These aspects are discussed in relation to the political and historical conditions currently present in Setomaa. This study is based on qualitative data, based on thirteen conversations with Setos of different ages in Setomaa. The findings show that Seto identity is not fixed but continuously negotiated between inherited belonging and cultural participation. Participants express general concern about language loss, decreasing intergenerational tramission of language and culture, and differing perspectives on Seto traditions. Conversely, some participants view cultural change as necessary for cultural continuity in contemporary society. Setomaa's position as a borderland and rural periphery strongly shapes everyday life through limited employment opportunities, outmigration and structural marginality. Furthermore, Indigeneity appears as contested and politically negotiated category, with differing interpretations of recognition both within the Seto community and in relation to state and institutional frameworks. Ultimately, geopolitical insecurity and proximity to the Estonian–Russian border significantly affect Setos' sense of security. This insecurity is often managed through normalization and adaptation in everyday life. Overall, Seto identity is understood as a lived borderland condition, shaped by intersecting cultural, emotional, political, and geopolitical processes. Rather than a fixed category, Seto identity emerges through continuous negotiation between continuity and change, belonging and exclusion, and stability and uncertainty.

To meet the requirements for real-time operation and flexibility in chromatic disper-sion compensation (CDC) for high-speed coherent optical communication systems, tra-ditional fixed-structure frequency-domain CDC filters suffer from limited adaptability aswell as high power and hardware cost. This thesis proposes a high-speed reconfigurable-length frequency-domain CDC filter architecture based on a cascaded structure consistingof a fixed 192-point P-FFT and a reconfigurable C-FFT in C = 2/4/8. Combined withoverlap-save streaming processing, the architecture enables real-time chromatic disper-sion compensation at a sampling rate of 60 GSa/s with 128-way parallel input. The workcompletes the RTL design and implementation of the reconfigurable data-routing unit,reconfigurable FFT, and compensation modules, and evaluates the hardware through syn-thesis and simulation in a 28-nm CMOS process at 0.70 V and 553 MHz. The resultsshow that the proposed architecture operates correctly, supports dynamic adjustment ofthe filter length without interrupting the data stream, and achieves significantly reducedreconfigurability overhead in high-parallelism modes. At C = 8 the additional poweroverhead relative to the fixed architecture is only 33.52%, while the proposed design alsoshows a clear area advantage. The architecture provides a practical solution that balanceshigh-speed processing capability, low power consumption, and reconfigurability for ASICdesign in high-speed coherent optical communication systems.

Video material in simulation-based training systems is often recorded and later reviewed during After-Action Review (AAR). To make this review process interactive, the encoded video should support responsive playback, random access, and faster-than-real-time navigation while still maintaining acceptable quality and manageable bandwidth and storage requirements. This thesis compares H.264, MJPEG, and JPEG XS as intra-frame compression alternatives for interactive AAR. The evaluation combines benchmarking with frame-markerprototype implementations for identifying safe access points in compressed video streams, meaning positions where decoding can begin without depending on earlier frames. A stand-alone Java prototype was developed to generate frame marker lists for MJPEG and JPEGXS, while FFmpeg-based benchmarks were used to compare bitrate, storage usage, encoding and decoding performance, CPU time, and visual quality measured with the objective metrics SSIM and PSNR. The results show that intra-frame compression simplifies frame-level random access compared with inter-frame coding, but increases bandwidth and storage requirements. Among the tested codecs, H.264 intra provided the strongest compression efficiency, MJPEG achieved the fastest encoding performance and allowed simple marker-based frame detection, while JPEG XS offered predictable bitrate behavior and strong decoding performance at a higher bitrate cost. Frame markers were implemented for both MJPEG and JPEG XS. MJPEG frame boundaries could be identified through direct marker search, whereas JPEG XS required additional codestream validation to avoid false detections. The results indicate that the suitability of a codec for interactive AAR depends on the trade-off between compression efficiency, processing cost, predictable transmission, and practical support for random access.

This is the fourth volume of the concurring series of Reports in Applied Mechanics, which is based on the outcome of the advanced project course TMPM10 in Applied Mechanics at Link¨oping University during the autumn of 2025. The course lay-up is based on several industrial or in-house research related projects within the field of Solid Mechanics concerning fatigue, topology optimisation, structural dimensioning, contacts etc, and Fluid Mechanics concerning fluid dynamics, flow, aerodynamics, heat transfer etc. The students tackle industry or forefront research relevant projects in close collaboration with industry from near and neighbouring regions or the university and work in project groups to solve the given tasks within the time limit of the course. Close collaboration with the industry/university is necessary to define planning, update and feedback for further evaluation at the industry/university. 

This year there were a total of seven projects performed during the course of 2025, five within Solid Mechanics and two in Fluid Mechanics. Some projects were performed in tight collaboration with industry partners, and had a close application to real industrial problems. The other were related to in-house research projects, pushing the research front forward. New knowledge had to be learned and skills were obtained. This has been a good opportunity for the students to show-off all their gained knowledge and apply it in the best possible way to make innovative solutions in the respective projects. Something they all managed to do with success! Tight deadlines can be vital in the industry, and one project group from the Solid Mechanics track fulfilled all deadlines within time during the course, thus earning a LiU reflector tag. A shining example of meeting deadlines! 

Daniel Leidermark & Magnus Andersson

Teleoperated systems are increasingly being used for tasks that are dangerous, repetitive, or difficult for humans to perform directly. Unmanned aerial vehicles (UAVs) are often used in scenarios where an operator needs to have a bird's-eye perspective and the ability to cover an area quickly, such as in search and rescue, disaster response, or reconnaissance missions. Increased autonomy could reduce the cognitive load on the operator while also making it possible for several UAVs to cooperate with less human control. Coordinating multiple UAVs is challenging, especially in environments with unreliable communication links or dynamically changing conditions, which makes it difficult to rely on a centralized unit to coordinate the mission.

To address this, a decentralized behavior tree-based architecture is proposed for a reconnaissance mission in a simulated environment. Each UAV runs its own behavior tree, which integrates search behavior, task allocation, task execution, and coordination with other UAVs. When a task needs to be allocated, the detecting UAV initiates an auction-based task allocation process using a modified version of the Contract Net Protocol, allowing other UAVs to bid on the task. The evaluation considers three aspects of the system: its ability to complete the mission and recover from UAV failures, its scalability as the number of UAVs increases, and the effect of heterogeneous team compositions with different capabilities.

The results show that behavior trees can be used to model a decentralized multi-agent system of UAVs, and that the proposed architecture was able to complete the designed mission scenario without relying on a centralized coordinator. The system was also able to recover from UAV failures during a mission, although the failure scenarios increased the mean mission completion time compared to normal operation. Increasing the number of UAVs reduced the mission completion time from 1607 seconds with three UAVs to approximately 1380-1440 seconds with six to eight UAVs, while communication overhead increased with the number of UAVs. The results also show that role specialization alone did not necessarily improve performance, as the outcome depended on how the task allocation strategy took the capabilities of the UAVs into consideration.

As artificial intelligence (AI) systems become increasingly sophisticated, accessible, and integrated into society, they are also becoming more present in children’s everyday contexts. Despite this growing integration, there is a limited understanding of how children interact with AI and what implications these interactions may have. To address this knowledge gap, 95 Swedish children aged 6-17 years were interviewed regarding their interactions with and interpretations of AI. Data was collected through semi-structured group interviews and analysed thematically, resulting in five key themes. The findings show that AI is widely integrated into multiple domains of children’s lives, and that children’s understanding of AI appears to be socioculturally constructed. Age-related differences in AI engagement were found and may reflect varying opportunities for participation and exposure, rather than developmental factors alone. Interactions were found to vary in terms of purpose of engagement, as well as the degree to which AI is visible or explicitly recognised in interaction. While children generally demonstrated high awareness of potential risks associated with AI use, their accounts also revealed ethical concerns related to possible long-term effects on well-being. Taken together, the findings provide insights into children’s lived experiences of AI, and also highlight the importance of situating children’s well-being at the centre of AI governance. Finally, the study provides a rich empirical foundation for future research, offering material for hypothesis generation and for further developing the understanding and mapping of children’s interactions with AI technologies. 

The physical environment plays an important role in shaping collaborative work. While previous research has examined creativity, collaboration, and distributed cognition across various settings, limited attention has been given to how music studio environments shape collaborative creativity in practice. This study explores how the physical environment of a music studio shapes creative collaboration in music production. Drawing on theories of distributed cognition and collaborative creativity, it investigates how music production processes are shaped by the studio environment. A qualitative field study was conducted at an independent music label. Empirical data consisted of video-recorded studio sessions and semi-structured interviews, which were analysed using multimodal interaction analysis, thematic analysis, and a subsequent Distributed Cognition for Teamwork (DiCoT) mapping. The findings from the video-observations demonstrate how participants navigated interaction based on access to resources, visibility, and opportunities for communication. Spatial organisation and the placement of artifacts influenced how participants coordinated actions, shared musical ideas, and maintained awareness of ongoing activities. Participants frequently relied on multimodal resources to communicate and develop ideas collaboratively. The thematic analysis further highlighted the importance participants attributed to flexibility, shared understanding, and accessible resources in supporting and constraining creative workflows. The DiCoT mapping conceptualised the studio as a distributed cognitive system and identified three recurring activity zones: the production zone, the collaborative zone, and the recording zone. Each zone both supported and constrained collaborative creativity in distinct ways. Further, the mapping revealed asymmetries between actors in how information and artefacts were coordinated across the different zones. Based on these findings, design implications are discussed regarding how music studio environments may be organised to better support collaborative creativity in music production.

Git is widely used in student course projects, but repository history can be difficultfor teachers to interpret when assessing individual contributions. This thesis investigateshow Git repository analysis and visualization can support assessment of division of laborin student group projects. As a result, a prototype tool was developed for C++ reposito-ries. A pre-study compared GumTree with Lines of Code (LOC), while a user study withfour teachers evaluated the tool’s usability and usefulness. The results show that GumTreecaptures structural changes not represented by LOC alone, and that teachers found the vi-sualizations useful for gaining an overview of contribution patterns. The tool received amean System Usability Scale score of 82.5, indicating good perceived usability. However,Git data cannot capture all forms of contribution, so the tool should be used as decisionsupport rather than as an automatic grading system.

High-fidelity nuclear core simulators are essential tools for reactor analysis and fuel management, but their computational cost limits their use in workflows requiring many repeated evaluations, such as screening and optimization of core designs. This thesis investigates the extent to which machine-learning surrogate models can approximate selected outputs of a high-fidelity core simulator for boiling water reactor applications and how known physics can be incorporated to improve robustness.

A modular surrogate-model framework was developed to predict burnup, void fraction, two-group neutron flux, and power distribution on a three-dimensional nodal core grid over an operational cycle. The models were primarily developed as convolutional neural networks, using reactor-state quantities available before running the reference simulator as input. In addition to data-driven training, selected physics-informed loss terms were investigated, including a monotonicity constraint for void fraction and neutronic loss terms based on diffusion-equation residuals and global neutron balance.

The results show that surrogate models can reproduce several spatially distributed reactor quantities with useful accuracy at substantially reduced computational cost. For the neutronic flux and power models, the 90th percentile of the absolute relative error was approximately 4–5% on the test dataset. The surrogate pipeline achieved a total wall-time speedup of approximately 350 times compared with the reference simulator, while the pure neural-network inference time corresponded to a speedup of approximately 16,000 times. The physics-informed monotonicity loss significantly improved the void-fraction model, whereas the neutronic loss terms did not lead to a clear improvement in final predictive accuracy.

The findings indicate that surrogate models can be useful as fast approximations of selected core-simulator outputs, particularly for exploratory analysis and design screening.

In the ever-growing technical society, our reliance on functioning software continues to grow. To protect our society, security professionals constantly combat malicious actors looking to abuse vulnerabilities in the systems. To help security professionals close the gap between vulnerability disclosure and the time that professionals start training for the vulnerability, this study performs an empirical analysis of data from public vulnerability databases. The analysis investigates the patterns and trends in vulnerability frequency, severity, and vulnerability types, and evaluate how they could be used to inform the focus of vulnerability selection. Several key phenomena were identified from the results of the thesis: first, a bleed-over property was found, which represents when a vulnerability is associated with multiple major versions of a product, indicating that the vulnerability has persisted through the previous major versions. An inconsistency in the severity data was identified for Microsoft products, where the version handling of the severity metric CVSS in the NVD leads to historical data that is hard to translate. A major increase in uninformative vulnerability types was also found after 2019, which were not present during the previous period of 1995-2018. Ultimately, this study showcases that despite inconsistencies existing in the historical data gathered from the NVD, it still provides valuable insight into the vulnerability history of products and allows for conditional utilization in product and vulnerability prioritization, by providing a methodological proposal, utilizing the bleed-over property and vulnerability type persistence.

In telecommunication sector, it is important to analyze the engagement of user with the network. With large volume of data generated, the essential part is to understand if the answer can be found in the underlying data. The aim of the study is to understand and assess the factors that impact user data volume download. This is then followed by using generalized least squares to estimate parameters of a linear model, while using an autoregressive process to estimate the covariance of error terms. (MSE) and R² score obtained by the two-step adaptive lasso and generalized least squares shows good performance on the test data. The significant variables obtained by the GLSAR model included streaming services such as Disney Plus, Twitch and network indicators such as Maximum Window Size. Finally, the reasons why these variables may be resulting in high user engagement is discussed. The inferences around the estimated parameters are useful in helping us ascertain the factors that impact data volume download.

The fragmented market for academic literature presents search friction for students, hinderingthem from finding the correct material in a reasonable timeframe. These inefficienciescould lower the chance of students purchasing said material, illustrating the need forbetter systems for this purpose. This work investigates the relationship between the implementationof a constraint-based knowledge-based recommender systems (KBRS) andusers’ likelihood of purchase. Through a controlled experiment, two online store versionswere compared: one search-based and one utilizing a KBRS. Tests involved students atLinköping University studying Industrial Engineering and Management, measuring findabilityand cognitive load via time-on-task and NASA-TLX, respectively. Results demonstratedthat implementing a KBRS increased the median likelihood of purchase by 10 percentagepoints, with 94% of participants preferring the store with a KBRS. Analysis revealsthat increased findability and decreased cognitive load each separately correlated positivelywith increased purchase likelihood (r = 0.6). Statistical analysis confirms that a positivecorrelation exists on a population level with 95% confidence. The findings indicatethat the implementation of a KBRS is associated with an increased likelihood of purchase,improved findability, and a reduction in cognitive load.

The performance impact of beginning of life cell-to-cell variation on a lithium-ion battery system using reduced-order pack models of different resolutions is investigated. The aim is to evaluate the effects of variance, how simplified models of the entire battery pack can reproduce certain key performance indicators, such as fast charge time or extractable discharge energy, under different operating conditions and levels of parameter dispersion. The aim also seeks to identify when higher model resolution is necessary and its subsequent effect on the computational time. The parameter dispersion in the system is introduced as variations in capacity, internal resistance, and state of charge imbalances between the individual cells, with varying degrees of parameter variation and combinations. Two simulation environments were used which both utilized an equivalent circuit model consisting of two RC-branches; one for fast charging procedures with a more refined thermal representation of the system, and one for discharge simulations with a less detailed thermal model. 

The results show that the influence of cell-to-cell variation depend strongly of both the parameter being varied and the operating mode. During fast charge, resistance variation has the strongest effect on the charging time. When only one parameter is varied, the lowest resolution model predicts similar performance indicators to that of the full-scale model. However, as more parameters are allowed to vary simultaneously, the reduced models deviate increasingly from the fully modelled system. During discharge, capacity and initial state of charge have the greatest impact on the usable energy in the pack. The different cell models produce minor differences in the performance indicators regardless of the amount of variation or the parameter combinations. 

The findings indicate that reduced order models can be suitable for certain analyses, particularly when variation is limited. The gain in computational runtime is however closely related to the level of spatial representation of individual cells used to capture temperature gradients in the system. Full scale modelling becomes more important, especially during fast charge simulations, when multiple sources of heterogeneity interact together. This is valid both on a system perspective as well as on a cell-to-cell perspective. Reduced order models could however be useful during discharge scenarios, both on a system and cell-to-cell perspective, if the discharging current is considered relatively low, with only minor losses in the predicted accuracy. This thesis therefore provides guidance for selecting the appropriate model resolution in battery pack simulations depending on the operating mode, and highlights the importance of accounting for cell-to-cell variations in both system design and performance evaluation.  

Är det bra att unga människor har inflytande i politiken, och i så fall från vilken ålder? I den här boken undersöker historikern och barnforskaren Bengt Sandin åldersgränser för rösträtt och valbarhet till riksdagen.    

Sverige hade i början på 1900-talet en unikt låg rösträttsålder. Samtidigt gjorde andra begränsningar att väldigt få män och kvinnor hade rösträtt. Så kallade rösträttsstreck uteslöt bland annat personer med låga inkomster eller obetalda skatter från politiskt inflytande. Också kön var ett kriterium för att uteslutas. De flesta gifta kvinnor hade exempelvis inte rösträtt, men ogifta kvinnor med egen inkomst kunde rösta i lokala val.    

När folkets krav på utökad demokrati växte lanserade liberala och konservativa politiker tanken om att höja rösträttsåldern för att inte ge inflytande till olämpliga medborgare. Med besluten om allmän och lika rösträtt 1918--1921 uteslöts de under fyllda 23 år i valen till andra kammaren och kommunerna och de under 27 år i valen till landstingen/första kammaren. Nu fick Sverige en hög rösträttsålder för att garantera att demokratin inte gick för långt och för fort.    

I Politikens åldersgränser granskas ålderns sociala och kulturella innebörder och hur dessa påverkade de politiska besluten. I förhandlingarna om rösträtten var valmanskårens ålder en nyckelfråga som möjliggjorde den slutliga kompromissen. Politiken utformades i ljuset av tidens dramatiska urbanisering och industrialisering och av den demografiska omvandlingens långsiktiga konsekvenser. Historien om politikens åldersgränser är en historia om ålder, klass, kön och plats.    

Bengt Sandin är professor emeritus vid Tema Barn, Linköpings universitet, och forskare vid Arbetarrörelsens arkiv och bibliotek. Han har spelat en viktig roll i utvecklingen av tvärvetenskaplig forskning om barn och barndom i Sverige. I sin forskning har han främst anlagt ett historiskt perspektiv på barn och barndom, inklusive tidigmodern utbildning, barnarbete, utbildningsmedier, välfärdspolitik och barns och ungas rättigheter.

SSAB in Oxelösund faces significant challenges with storage capacity connected to its transition to fossil-free steel production. This creates an urgent need for increased storage capacity in the Finished Goods Warehouse and the Central Warehouse, whose material flow already exceeds their current capacity, a situation further compounded by decades of gradual expansion without any fundamental restructuring of the layout. The purpose of this study is to analyse the current warehouse design at SSAB by evaluating work processes, warehouse equipment and warehouse layout, and to develop concrete improvement proposals that increase storage capacity and handling efficiency. The study is a case study with both qualitative and quantitative elements, conducted through a literature review, interviews, observations, a survey and quantitative data analysis.

The current-state analysis shows that the existing space shortage causes problems across multiple areas. Due to unclear routines in the way of working, uncertainty arises regarding where to place goods when areas are full, which is resource-intensive and diverts time from ordinary operations. Furthermore, both the dunnage placed between pallets and the use of counterbalance forklifts impose limitations on stacking height per storage location, contributing the high occupancy rate across the warehouse. In addition, the quantitative analysis shows that several storage areas are underutilised, while others lack the capacity to accomodate all material directed there by SSAB’s warehouse management system. The central finding is therefore that the space shortage is primarily not caused by insufficient total storage area, but by incorrect dimensioning of storage zones relative to the actual material flow. The study results in recommendations across three areas. Within work processes, recommendations include introducing a standardised way of working and a systematised naming and numbering of storage zones. Within warehouse equipment investments in more robust racking and dunnage are proposed, along with an investigation into alternative forklift solutions. Within warehouse layout, three layout proposals are presented with different focus areas, including the elimination of redundant transport routes, correct dimensioning of storage areas and the enclosure of the Central Warehouse. For each recommendation, the impact on storage capacity and handling efficiency has been assessed alongside its feasibility. The overall recommendation is that SSAB should implement all measures within work processes and warehouse equipment, and invest in the layout alternative featuring an indoor warehouse, as this is assessed to have the greatest positive impact on both storage capacity and handling efficiency.

The conclusion is that a sustainable warehouse design requires a well-balanced development of work processes, warehouse equipment and warehouse layout in combination, as the analysis has shown these to be closely interconnected. A well-designed warehouse creates the conditions for a structured and efficient way of working, as well as an facility dimensioned to meet future needs.

The aim of this thesis is to investigate the feasibility of improving road roughnessestimation using only vertical acceleration measurements in the presence ofunknown suspension parameters. An additional objective is to evaluate whethersuch estimation can be performed online, and whether reliable road roughnessestimation can be achieved across vehicles with different suspension systems.The study first evaluates the performance of a previously developed road roughnessestimation method under different suspension configurations in order to assesshow suspension characteristics affect the estimated International RoughnessIndex (IRI). Based on the identified limitations, an adaptive estimation frameworkis proposed to reduce the dependency of the estimated road roughness onvehicle-specific suspension properties.A quarter-car model with augmented suspension parameters was used, and bothan Extended Kalman Filter (EKF) and an Iterated Extended Kalman Smoother(IEKS) were applied for joint state and parameter estimation. The methods wereevaluated using pre-processed vehicle measurements collected under various drivingconditions.The results show that the available measurements generally do not provide sufficientexcitation for reliable estimation of the suspension parameters, resulting inpoor convergence and parameter drift. To mitigate this issue, physical constraintswere imposed on the parameter estimates. Despite the limited observability ofthe suspension parameters, stable and accurate International Roughness Index(IRI) estimation was achieved.Furthermore, the EKF demonstrated computational efficiency suitable for realtimeimplementation, whereas the IEKS provided improved robustness againstparameter drift at the cost of higher computational complexity. The proposedadaptive framework reduced the variation in IRI estimates between differentsuspension systems, although this improvement was achieved at the cost of aslight reduction in estimation accuracy compared with the previously developedmethod. Overall, the results indicate that reliable online road roughness estimationis feasible using vertical acceleration measurements, provided that limitationsrelated to system excitation are appropriately handled.

Dagens arbetsmarknad präglas av hög arbetsrörlighet och organisationer står inför utmaningen att behålla medarbetare för att bibehålla organisatorisk framgång. Denna case-studie syftar till att undersöka vilka aspekter medarbetare beskriver som viktiga respektive mindre viktiga för viljan att stanna kvar på arbetsplatsen, samt hur dessa aspekter synliggörs på arbetsplatsen. För att uppfylla studiens syfte genomfördes semistrukturerade intervjuer samt deltagande observationer på ett medelstort industriföretag i Sverige. Resultatet visar att sociala relationer, geografisk anknytning och ledarskap är de mest betydelsefulla aspekterna för medarbetares vilja att stanna kvar. Utvecklingsmöjligheter, fysisk arbetsmiljö, lön och arbetsuppgifter framstår däremot som mindre betydelsefulla. Tidigare forskning och studiens resultat understryker betydelsen av att främja medarbetares kvarstannande samt synliggör HR-praktikers behov av kunskap om de aspekter som redovisas i denna studie. Studiens resultat ligger till grund för de praktiska implikationerna för HR-arbete som presenteras i slutet av studien. 

Syftet med studien var att undersöka hur intraorganisatorisk samverkan i en kommun formas genom fyra strategiska nätverk, med fokus på deltagarnas beskrivningar av möjliggörande och begränsande faktorer samt på likheter och skillnader mellan nätverken. Studien genomfördes med kvalitativ ansats baserad på intervjuer, vilka analyserades med inspiration från Charmaz konstruktivistiska grundade teori.

Resultatet visade att nätverken fungerade i olika grad som arenor för samtal, samarbete och samverkan för gemensam förståelse av komplexa samhällsproblem. Samtidigt framträdde en spänning mellan denna funktion och nätverksdeltagarnas förmåga att omsätta lärandet. Faktorer som ledarskap och nätverkens sammansättning samt kontinuitet påverkade i vilken grad samtal och samarbete utvecklades till samverkan. Studien visar att nätverken i viss utsträckning fungerar som hängrännor mellan organisatoriska stuprör, genom att möjliggöra kunskapsutbyte över förvaltningsgränser.

This study explores gamification, the implementation of game elements in mathematics education, and its impact on students’ motivation to learn mathematics. This is done through a literature study where 24 articles are analyzed and coded according to the theoretical framework expectancy value-theory. The results show that gamification leads to a general increase in motivation but that in some cases it can have the opposite effect. The results also show some knowledge gaps in the subject regarding parts of the chosen framework and the lack of studies in the Western world and students in the upper secondary school.

Energy efficiency is recognised as an important strategy for reducing industrial energy use and supporting long-term sustainability. Despite this, many manufacturing companies continue to face challenges in translating energy data into practical actions and systematic energy management. Previous research has shown that barriers to energy efficiency are not only technical, but also organisational and behavioural. Difficulties related to prioritisation, lack of resources, limited use of energy data, and insufficient integration into daily operations continue to hinder systematic energy work. Against this background, the purpose of this study is to investigate how manufacturing companies can work systematically with energy management through the visualisation and practical use of continuous energy data. The study also aims to identify organisational, technical, and behavioural barriers and drivers that influence how energy data is used to support energy efficiency and operational decision-making. The study adopts a qualitative exploratory approach based on semi-structured interviews with representatives from three manufacturing companies and one expert within energy monitoring and enterprise systems. The empirical material was analysed using reflexive thematic analysis. The results show that energy data is often available within organisations, but that its operational use remains limited. A central finding is that energy management becomes more actionable when energy use is connected to production-related and normalised Key Performance Indicators (KPIs), such as energy use per produced unit. The findings also highlight that visualisation should be simple, role-adapted, and connected to metrics that employees can directly relate to, such as production output or economic cost. Furthermore, measuring baseload and idle energy consumption during non-productive periods was identified as an effective way to detect hidden energy waste. The study concludes that systematic energy management requires more than technical measurement systems alone. For energy data to influence behaviour and decision-making in practice, it needs to be integrated into existing organisational routines, operational meetings, and continuous improvement processes. Leadership support, clear prioritisation, and accessible visualisation are therefore identified as important prerequisites for making energy data actionable in manufacturing industries.

The ability to forecast risk is essential for all financial institutions, and indeed, all investors intending to manage their risk exposure. Two of the most common ways to do this, both in practice and in regulation, are Value at Risk (VaR) and Expected Shortfall (ES). Together they form vital measures to create an overview of an investor's potential losses across any number of investments, as well as a cornerstone to meet regulatory demands. It is therefore of great interest to build a comprehensive understanding of VaR-ES modeling to enable accurate VaR-ES forecasts, to ultimately improve the ability to adapt positions to available information.

One area that has received limited attention in the literature is the use of macroeconomic information to improve VaR-ES estimations. To investigate this possibility, the VaR quantile is estimated directly using a CAViaR based framework, which is then combined with a macro variable input and a volatility measure through VIX. The macro-variables are introduced via the intercept term. Five macro variables are proposed, Geopolitical Risk Index (GPR), Industrial Production Change (IP) in the US, inflation for the USD, default yield spread (Dfy), and Term Spread (TS). By utilizing loss score functions to estimate the parametric CAViaR-VIX-macro model, the potential of this information is examined through evaluation of VaR-ES forecast accuracy using the same loss scoring function, and backtesting of VaR and ES. Furthermore, the VaR level is estimated for four different assets, the S\&P500, the FTSE100, Brent crude oil, and gold.

It is found that macroeconomic variables have varied effects depending on asset coupled with. Generally, at least one macro-variable is found to improve backtesting results and to produce a more accurate forecast based on mean loss score in the out-of-sample. However, when using the Model Confidence Set test, it is found that there is no statistically significant difference in accuracy between the proposed CAViaR-VIX-macro model compared to a simpler CAViaR-VIX model based on loss scores. Furthermore, for the two commodities, it is also found that the CAViaR model, along with all of the proposed extensions, has only slightly more accurate forecasts compared to the benchmark model GARCH(1,1) at one of the tested quantile levels, implying a poor fit between these assets and the CAViaR framework. With that said, CAViaR does pass backtesting to a much larger extent than GARCH(1,1), signaling better statistical properties. Overall, it is found that CAViaR based models outperform GARCH(1,1), especially for stock indices when considering both forecast accuracy and statistical properties. Furthermore, macro-variables consistently rank as most accurate for all investigated assets and pass backtesting to a greater extent than the baseline CAViaR model.

This thesis investigates the feasibility of Quantum Key Distribution (QKD)-secured real-time voice communication using One-Time Pad encryption. While QKD enables theoretically secure key exchange, the limited key generation rate introduces challenges for bandwidth-intensive real-time applications such as voice communication.

To evaluate these challenges, a prototype voice communication system was designed and implemented using Opus audio compression, Real-time Transport Protocol-based transport, One-Time Pad encryption, and simulated QKD-generated keys. The system was experimentally tested and evaluated under varying audio bitrates and packet loss conditions. Performance was assessed using objective speech quality metrics, including STOI and PESQ, as well as latency, jitter, packet loss, and subjective intelligibility evaluations.

The results show that low audio bitrates between 5 and 8 kbps provided the best balance between speech intelligibility and cryptographic sustainability. At higher bitrates, the limited QKD key generation rate caused significant packet loss due to key starvation, resulting in substantial degradation of audio quality. The system also demonstrated moderate resilience to packet loss at the identified viable bitrate. Furthermore, the addition of Wegman-Carter authentication introduced measurable but limited performance overhead in terms of latency and jitter.

The findings indicate that QKD-secured real-time voice communication is technically feasible under constrained bitrate conditions, but that performance is strongly limited by the available key generation rate. The results further show that increasing bitrate or adding authentication overhead can lead to packet loss caused by cryptographic key starvation, which negatively affects speech quality and communication stability. The study highlights the trade-off between cryptographic security and real-time communication performance in QKD-based systems.

The growing use of unmanned areal vehicles (UAVs) for forestry monitoring has created a need for tree species and damage segmentation models. The lack of real world data for uncommon diseases, species and other conditions poses a significant bottleneck. This work investigates whether simulating a complete digital camera pipeline on synthetic images rendered in Blender of forest images can bridge the domain gap and improve instance segmentation performance on real 4K drone images. The project implements a modular pipeline and evaluate its impact through a series of ablation experiments.

The models are assessed on 127 manually annotated images using mean IoU, Brier score, AUROC, F1 score, and polygon recall as the evaluation metrics. All metrics are normalized to the baseline model that is trained on synthetic data not transformed through the pipeline.

The results show that the full camera pipeline reduces the performance of the baseline in all metrics. Omitting chromatic aberration from the pipeline is the only consistent improvement over the baseline in all metrics (mean IoU, Brier score, AUROC, F1, and recall) except for the Brier score, where a simple Gaussian blur is a marginal improvement over most models except for the chromatic ablated model, and with the best at polygon recall at +0.05. These findings suggest that an elaborate simulation of the camera pipeline may introduce elements that outweighs its benefits, and that simpler, targeted methods may outperform in utility at a lower engineering cost.

Positive human-animal relationships (HAR) are important for animal welfare in livestock and other captive hoofstock species. Research suggests that HAR can affect the development of personality-linked behaviours. This study explored whether early positive handling influenced dairy calves’ (Bos taurus) responses to personality tests. Twenty-four female calves were assigned to a treatment group (bi-weekly voluntary positive handling), or a control group (routine husbandry only). Personality tests were conducted at 5, 8, 12 and 15 weeks old using a novel object test, novel human test, activity test and social runway test. Measured variables included latency to approach novel stimuli, number of interactions with novel stimuli, locomotor activity and latency to reunite with conspecifics. Positive handling had limited but detectable effects. Treatment calves interacted less frequently with the novel object and showed longer latency to reunite with conspecifics at 12 weeks of age. No treatment effects were detected for latency to approach novel stimuli or for activity. However, age strongly influenced behavioural responses, with reduced latencies to touch novel stimuli, exploratory interactions and activity levels over time. Correlations between variables selected to represent different personality gradients were non-significant, showing no behavioural syndromes. These findings suggest early positive handling influences aspects of behavioural development and calves’ response to personality tests. However, age and developmental stage appear to be the primary behavioural response drivers. These results emphasise the importance of considering developmental stage when assessing calf personality and indicate that the effects of human–animal relationships on behavioural development warrant further investigation in welfare-oriented research.

 Recent evidence points to the idea that dog aggression is highly variable at the individual level and affected by various factors, such as the owner’s personality or dog-owner interactions. Additionally, studies on dog aggression show limited differences between dog breeds, or differences that are unrelated to the legislative status of those breeds, even though breed-specific legislation prohibits the ownership of so-called “dangerous” breeds. Here, I examined differences in aggression among breed groups in the Swedish dog population, using a combination of personality questionnaires and video analysis of dog-human play. Aggressive behaviour of dogs was assessed using the short version of the Canine Behavioural Assessment and Research Questionnaire, their owners’ personality was measured with the Big Five Inventory, and the play interactions were recorded by the participants at their homes. The results showed no significant differences in aggression based on the legislative status, and no single breed group could be identified as having significantly higher or lower aggression scores. More neurotic owners had more aggressive dogs, while the owners’ agreeableness and the dog’s engagement in keep-away play were both negatively associated with dog aggression. The results suggest that dog aggression is affected by a complex interplay between many variables, rather than being solely based on breed, thus providing further reason to question the existence of a scientific basis for breed specific legislation.  

Mervärdesskatt är en indirekt allmän konsumtionsskatt som utgår vid i princip all försäljning av varor och tjänster. Området är i stor utsträckning harmoniserat inom EU och svenska ML bygger till stor del på EU:s mervärdesskattedirektiv. En central del i det mervärdesskatterättsliga systemet är avdragsrätten, som innebär att beskattningsbara personer har rätt att dra av ingående mervärdesskatt hänförlig till inköp för att undvika dubbelbeskattning i produktionsleden.

Vissa företag bedriver en så kallad blandad verksamhet, vilket innebär att verksamheten omfattar både mervärdesskattepliktiga och undantagna transaktioner. Vid sådan blandad verksamhet kan svårigheter att fastställa den avdragsgilla delen av den ingående mervärdesskatten uppstå, varför det krävs tillämpning av fördelningsmetoder för att bestämma den avdragsgilla andelen.

Enligt de nuvarande bestämmelserna i ML ska fördelningen vid blandad verksamhet ske enligt skälig grund, om den avdragsgilla andelen inte kan fastställas. Det skiljer sig från mervärdesskattedirektivets bestämmelser, där huvudregeln är fördelning utifrån omsättning. I HFD 2023 ref. 45 fastslogs dock att den svenska regleringen inte införlivar de relevanta bestämmelserna i mervärdesskattedirektivet på ett korrekt sätt och att direktivets regler kan tillämpas med direkt effekt. Finansdepartementet föreslår därför lagändringar i en promemoria där omsättningsmetoden införs som en uttrycklig huvudregel i ML, med särskilda undantag för byggnader där en ytbaserad fördelningsmetod i stället ska användas. Skälet är att omsättningsmetoden inte alltid ger en rättvisande bild av resursförbrukningen i verksamheten.I uppsatsen undersöks konsekvenserna av de föreslagna ändringarna samt hur de påverkar avdragsrätten för företag inom fastighetsbranschen. Analysen visar att förslaget får en substantiell påverkan på företag som bedriver verksamhet där varor och tjänster avser byggnader, särskilt för bostadsrättsföreningar och företag med uthyrning av lokaler med frivillig skattskyldighet. Den ytbaserade metoden bedöms leda till en mer restriktiv, men mer rättvisande, avdragsrätt som bättre speglar hur verksamhetens resurser faktiskt förbrukas.

I svensk rätt föreskrivs det i 25 kap. 18 § första stycket aktiebolagslagen (2005:551) (ABL) att styrelsens ledamöter svarar solidariskt med bolaget för de förpliktelser som uppstår under medansvarsperioden vid kapitalbrist i aktiebolag. Genom NJA 2025 s. 485 utvidgade Högsta domstolen (HD) medansvaret i 25 kap. 18 § första stycket ABL till att även omfatta personer som utan att vara styrelseledamöter, utövar ett bestämmande inflytande över aktiebolaget. Rättsfiguren betecknas som faktisk företrädare och härstammar från den engelska rättens de facto director och shadow director. I engelsk rätt kan juridiska personer omfattas av ansvar som shadow directors, vilket aktualiserar frågan om även juridiska personer kan ansvara som faktiska företrädare enligt bestämmelsen i 25 kap. 18 § första stycket ABL. Frågan är särskilt relevant eftersom det enligt 8 kap. 10 § ABL föreligger ett förbud mot att ett aktiebolag utser exempelvis ett moderföretag, en kreditgivare eller annan juridisk person till styrelseledamot.

I uppsatsen behandlas frågan om juridiska personer kan omfattas av det personliga betalningsansvaret enligt 25 kap. 18 § första stycket ABL i egenskap av faktiska företrädare. Syftet med uppsatsen uppnås genom en rättslig undersökning av de kriterier som kan identifieras för faktiska företrädare. Därtill genom en diskussion om vilka rättsliga argument som talar för respektive emot en analog tillämpning av 25 kap. 18 § första stycket ABL till juridiska personer.

Analysen visar att tre kriterier kan identifieras för att en aktör ska anses utgöra en faktisk företrädare enligt 25 kap. 18 § första stycket ABL. För det första krävs att aktören saknar formell ställning som styrelseledamot enligt ABL under medansvarsperioden. För det andra krävs att aktören i realiteten har utövat ett bestämmande inflytande över bolagets verksamhet. För det tredje måste inflytandet avse bolagets ledning eller centrala beslut.

Slutsatsen är att juridiska personer inte på förhand bör uteslutas från kretsen av faktiska företrädare enligt 25 kap. 18 § första stycket ABL. Avgörande bör vara om den juridiska personen i praktiken har utövat ett tillräckligt långtgående bestämmande inflytande för att anses ha övertagit den beslutskontroll som enligt kapitalbristreglerna ligger hos styrelsen. Moderföretag och kreditgivare kan därför i kvalificerade undantagsfall omfattas av det personliga betalningsansvaret i 25 kap. 18 § första stycket ABL, särskilt när inflytandet inte endast utgör sedvanlig koncernstyrning eller legitim kreditgivning utan innebär faktisk styrning av bolagets centrala beslut under kapitalbristen. En sådan analog tillämpning kan bidra till att upprätthålla borgenärsskyddet och motverka kringgående av medansvarsreglerna, men bör tillämpas restriktivt med hänsyn till rättssäkerhets- och förutsebarhetsaspekter.

As computing efficiency and storage capacity become increasingly important to companies, modernizing database maintenance has emerged as a challenge. This thesis evaluates the feasibility of transitioning from a legacy static rule-based deduplication system to a machine learning approach to customer records. Utilizing real-world customer data from the UK and Belgium, the study compares supervised classification (Random Forest, XGBoost) and unsupervised clustering (DBSCAN, Graph-based transitive closure) against a legacy baseline. Given the extreme sparsity of the data and the high imbalance of duplicate records, performance was measured using Informedness and Markedness. 

The findings reveal that the primary challenges is utilizing real-world customer data are extreme sparsity and inconsistent formatting. Despite these hurdles, both models identified more suspected duplicates than the static rules and achieved high performance against the constructed labeled datasets with Random Forest and XGBoost emerging as the most reliable machine learning models. Unsupervised clustering, especially DBSCAN, offers a more scalable path by eliminating the need for labeled data, though it remains highly dependent on optimized parameters. However, the study also highlights that trained classifier models are region-specific, requiring localized training or a diverse global dataset for effective deployment.

The findings suggest that while machine learning noticeably improves suspected duplicate detection. algorithms behave fundamentally different depending on regional data entries. Therefore the most reliable operational solution is a probabilistic framework integrated with a Human-in-the-Loop system, offering the best balance of technical accuracy and business reliability.

Background: Goodwill represents a central and growing balance sheet item in listed companies’ financial reporting, based on management’s subjective assessments of future economic benefits in business combinations, creating uncertainty about whether goodwill represents real economic value or overly optimistic assumptions. 

Purpose & research question: This study examines whether recognized goodwill at acquisition relates to future operating performance, and whether this differs between industrial and service firms listed on Nasdaq Stockholm and Nasdaq Helsinki. The research question is: Does the relationship between the size of recognized goodwill at the time of acquisition and future operating performance differ between industrial and service firms listed on Nasdaq Stockholm and Nasdaq Helsinki? 

Method: The dataset comprises 32 firms observed over the period 2022-2024, corresponding to 96 observations. Data were analyzed through multiple linear regressions with EBIT and EBITDA margins as dependent variables and goodwill ratio as the main independent variable, supplemented by control variables for firm size, leverage, payment method and additional acquisitions. 

Results & contributions: The study contributes knowledge about goodwill’s informational content in a Nordic IFRS context and shows that initially recognized goodwill does not function as a reliable signal of future operating performance. For industrial firms, a negative statistically significant relationship was identified with EBIT, which did not persist in the robustness test with EBITDA, indicating that the effect is partly driven by accounting mechanics. The study further contributes the insight that goodwill’s informational value is industry dependent. In industrial firms, goodwill appears more as risk indicator than a signal of future value creation, while no corresponding relationship was identified in service firms.

This literature study examines students' attitudes towards formative assessment in mathematics. To examine this, searches for scientific articles have been carried out via ERIC and UniSearch. The search results resulted in 6 articles being selected for literature analysis. The selected literature was summarized, and these summaries were the basis for a thematic analysis. Six themes were identified from the thematic analysis, these themes were: 1) Students positive attitudes to formative assessment in theory, 2) Student have ambivalent attitudes to learning objectives, 3) Students have ambivalent attitudes to questioning techniques, 4) Students have ambivalent attitudes to feedback, 5) Students have ambivalent attitudes to self-assessment, and 6) Students have ambivalent attitudes to peer-assessment. Based on the results, It is concluded that students have complex attitudes to formative assessment in mathematics. Students wish to get Information about how they perform in mathematics, and they generally express positive attitudes to formative assessment. Students do however express negative attitudes to how formative assessment is used in practice.

The purpose of the study is to investigate the experiences and views of mathematics teachers' use of digital tools in their teaching. In addition, the study examines how the focus on the use of digital tools has varied between the reforms Gy11 and Gy25, based on mathematic teachers' experiences and in different mathematic textbooks. The data collection methods used in the study are textbook analysis and a qualitative interview study including eight practicing mathematics teachers at upper secondary schools. The analysis of the collected data resulted in four themes that answer one of the study's questions, which are related to the teachers' descriptions of the use of digital tools in teaching. The study´s results also show that there is less focus on digital tools in relation to the change from Gy11 to Gy25. This result is also shown in the textbook analysis, which shows that the new textbook has fewer tasks that require the use of digital tools compared to the previous edition.

Generative AI has rapidly become an increasingly integrated part of organizational work, offering significant opportunities for efficiency, innovation, and knowledge support. At the same time, the technology is evolving faster than the formal governance mechanisms intended to regulate its use, creating challenges for organizations seeking to monitor and control employee use of AI. These challenges are particularly relevant in small and medium-sized enterprises (SMEs), where resources and formal governance structures are often more limited than in larger organizations. 

The purpose of this essay is to examine how SMEs govern employees’ use of generative AI and how the relationship between formal governance and actual use is manifested in practice. The essay adopts a qualitative research approach based on semi-structured interviews with representatives from SMEs. The empirical material was analyzed using thematic analysis informed by Simons’ (1995) Levers of Control framework and Jensen and Meckling’s (1976) agency theory. 

The findings show that the governance of generative AI is largely characterized by informal forms of control. Belief systems and interactive control systems emerge as central mechanisms through which organizations influence AI use through values, dialogue, learning and trust. At the same time, boundary systems are often broad and loosely defined, while diagnostic control systems remain underdeveloped, limiting organizations’ ability to monitor and evaluate AI use in practice. The essay further demonstrates that shadow AI can be understood as a consequence of the interaction between encouraging attitudes toward AI, limited organizational visibility, and extensive employee autonomy. 

The essay concludes that governing generative AI in SMEs involves balancing control and autonomy, where trust, dialogue, and individual responsibility play a prominent role. The essay contributes to the emerging literature on generative AI governance by providing insights into how formal and informal governance mechanisms interact in practice and how information asymmetry and shadow AI emerge within the SME context.