Maneuvering a fighter jet is not easy, and new methods for minimizing the risk of pilots experiencing information overload are constantly under development. Saab is currently looking into the possibilities of creating a decision support system (DSS) for pilots in situations where multiple independent system failures occur simultaneously. In today’s JAS 39 Gripen E such failures generate multiple simultaneous alerts for the pilots to act upon, with each alert proposing a set of actions for the pilot to handle the current situation. These actions are displayed on separate pages for each of the alerts, requiring the pilot to manually swap between pages of actions to get an overview of what to do. When pilots must use a significant part of their cognitive abilities to maneuver the aircraft in critical situations, a DSS is needed to apprehend the information and guidelines from the alerts more quickly.

Our approach to developing such DSS is by representing each of the individual actions as nodes in a network, with links between nodes providing information about the relations between actions. The purpose of mapping the problem to become a networking problem is to use label propagation algorithms to divide the network into communities. With each node being assigned to a community and having the communities sorted on priority, getting a first draft of what a sorting algorithm can accomplish should be easy given a complex fault situation. We use rule mining to extract rules from the system as it is currently implemented to create a rule-based sorting within communities.

The conclusion regarding label propagation algorithms is that although they are great for prototyping, propagation algorithms have no place in creating a DSS with high reliability. We also conclude that inconsistencies in the data that yield cycles in the created networks limit the sorting algorithms since there is no way of knowing where the cycle begins, hence no way of knowing how to sort actions being part of a cycle. Despite this, we argue that mined rules can be very helpful for engineers at Saab to be more consistent in their future work. Because of this, the conclusion is that our prototype of the DSS is better suited for the engineers working with providing pilots with the correct information than for the pilots directly. Lastly, we provide suggestions for future work, focusing much on possible ways of dealing with the cycles. Suppose Saab wants to pursue further research into whether creating a good enough DSS the way we propose is possible. In that case, some filter has to be developed to reduce the amount of information in complex fault situations.

We report results from a study of the local structure of hydrated nanocrystalline 2 �m films of the well known proton conductor BaZr1-xScxO3-x/2 with x = 0.45, 0.54 and 0.64, using infrared (IR) spectroscopy. The films were prepared by magnetron sputtering. Analysis of the IR spectra focused on the O–H stretching region (2000—3700 cm-1), which reveals the presence of several distinct O–H stretching bands for which the intensity and frequency of each band vary in an unsystematic manner with Sc concentration. The spectra for the two higher Sc concentrations, x = 0.54 and 0.64, exhibit a distinct, highly intense O–H stretching band centered at around 3400–3500 cm-1, which is assigned to relatively symmetric, weakly hydrogen-bonding, proton configurations. The spectrum for the lower Sc concentration, x = 0.45, does not feature such a band but a broader, weaker, O–H stretching band between approximately 2500 and 3700 cm-1, suggesting that the protons are more homogeneously distributed over a range of different local proton coordinations in this relatively weakly doped material. A comparison to the IR spectra of powder samples of similar compositions suggests that for x = 0.45, the spectra and proton coordination of films and powder samples are similar, whereas for x = 0.54 and 0.64, a larger fraction of protons seems to be located in weakly hydrogen-bonding proton configurations in the films compared to the respective powder samples.

Denna rapport ger en kunskapsgrund om de praktiska förutsättningarna, kravbild, och forskningsläge för utformning av underhållsområden på större driftplatser. Rapporten inleds med en bakgrund och motivering till behovet av underhållsområden, samt en beskrivning av hur studien har genomförts. En genomgång av förutsättningar och begränsningar visar bland annat att de tekniska delsystemen (spår-, signal-, och elkraftsystem) måste beaktas eftersom de har olika sektionering, gränspunkter och skyddsgivning för de arbeten som behöver utföras, samt att trafikeringsbehoven och dess variation behöver beskrivas på en generell nivå (oberoende av en specifik tidtabell), både vad gäller linjetrafik, växling och uppställning. 

Det centrala kapitlet är en krav- och behovsanalys. Där dokumenteras först vilka allmänna egenskaper som fördefinierade underhållsområden behöver uppfylla, varefter tre avsnitt följer som diskuterar specifika behov som ställs av de tre verksamhetsgrenarna underhåll, planering, och trafikledning. Ett viktigt resultat är att inga stora målkonflikter har identifierats vad gäller utformningen av underhållsområden samt att en samstämmighet råder om att trafikpåverkan bör vara den huvudsakliga värderingsgrunden för områdenas utformning. Den genomförda litteraturstudien har identifierat en relativt omfattande forskning om olika partitioneringsproblem, men bara ett fåtal publikationer inom rälsbundna transporter. För hantering av kapaciteter på driftplatser finns det metoder som kan hantera en övergripande trafikbild, men ännu inget bra stöd för analys av restkapacitet vid olika typer av tidsbegränsade spårreduktioner. Någon forskning om kombinationen av partitionering, eller indelning i underområden, av en driftplats bestående av flera delsystem där målet är att kunna hantera trafikbelastningen så bra som möjligt på den resterande spårkapaciteten har vi inte kunnat finna. 

Vi rekommenderar att Trafikverket vidareutvecklar sitt metodstöd för utformning av underhållsområden inom ramen för målområdet som arbetar med servicefönster. Både i detta metodstöd och för framtida forskning tror vi att den identifierade probabilistiska kapacitetsmodellen för driftplatser kan vara en lämplig grund. 

Arbetet har utförts i förstudieprojektet UFO (Utformning av underhållsområden på större driftplatser), finansierat av Trafikverket (FoI-portfölj Vidmakthålla, ärende-ID 7742, diarienummer TRV2022/138570) via branschprogrammet KAJT, Kapacitet i järnvägstrafiken (www.kajt.org).

Skolfrånvaro är ett omdebatterat ämne som i olika rapporter och i forskning lyfts fram som ett samhällsproblem. Forskningen är omfattande, både nationellt och internationellt. Eftersom tillräckliga kunskaper saknas om elevers erfarenheter av skolfrånvaro så är det ett perspektiv som behöver belysas mer. Studiens syfte är att bidra med kunskaper om hur skolan kan arbeta för att främja skolnärvaro genom att undersöka problematisk skolfrånvaro ur ett elevperspektiv. Studien tar sin utgångspunkt i en narrativ metod. Genom livsberätteler bidrar ett antal elever med kunskap om närvarofrämjande insatser utifrån egna erfarenheter av skolfrånvaro inom gymnasieskolan. Jag intervjuade sex elever från fyra olika kommuner samtliga med erfarenheter av skolfrånvaro i gymnasieskolan. Eleverna studerade inom både yrkesförberedande och studieförberedande program. En elev hade erfarenhet av gymnasieskolans introduktionsprogram. Studien fokuserar på tre huvudsakliga frågeställningar: Vilka orsaker till skolfrånvaro framträder i elevernas berättelser, vilka erfarenheter har elever av närvarofrämjande insatser samt vilka insatser väljer elever själva att lyfta fram som viktiga i ett närvarofrämjande arbete? Jag valde en kvalitativ forskningsansats och utgick från en tematisk ostrukturerad intervjuguide då det därigenom fanns en större möjlighet för informanten att själv förmedla den bild de vill ge av sitt liv.

Studiens teoretiska ansats utgår från specialpedagogiska teorier och innefattas av det kompensatoriska och relationella perspektivet. Därutöver tillkommer de teoretiska begreppen; inkludering, delaktighet och exkludering. Studiens teoretiska ram har även utvidgats med begreppet KASAM. Känslan av sammanhang är grundläggande inom Antonovskys salutogena teori om hälsa.

Resultatet visar att det finns många orsaker till elevers skolfrånvaro och att orsakerna är komplexa. Elevers erfarenheter av närvarofrämjande insatser ser olika ut eftersom arbetet skiljer sig åt både mellan och inom skolor. Elever har förslag på hur skolor kan arbeta för att främja skolnärvaro.

Denna studie undersöker förskollärares uppfattningar om sitt arbete med pedagogisk dokumentation. Datamaterial har samlats in med hjälp av semistrukturerade intervjuer av förskollärare. Studiens utgångspunkt är fenomenografiska teoretiska perspektiv.

Studiens resultat utgörs av tre kategorier av uppfattningar, där den första är innehåll i förskollärares arbete med pedagogisk dokumentation. Förskollärarna i denna studie uppfattar pedagogisk dokumentation som ett styrningsverktyg utifrån styrdokument, en arbetsmetod för att synliggöra lärande samt som ett sätt att synliggöra förskollärarens profession och praktik. I den andra kategorin, pedagogisk dokumentation som svårt och komplext uppdrag, lägger förskollärarna i denna studie fokus på yttre- och praktiska förutsättningar. Det handlar om innehållsmässiga svårigheter kring vad som ska dokumenteras, arbetsbörda på grund av saknad kompetens och tid, samt svårigheter att hantera teknik och digital dokumentation. Den tredje kategorin, barns delaktighet i arbete med pedagogisk dokumentation, fokuserar förskollärarna i denna studie på barns kompetens. Förskollärarna uppfattar ofta barnen som inkompetenta och passiva, med begränsad rätt till inflytande och integritet i pedagogisk dokumentation.

Studien bidrar med kunskap kring förskollärares uppfattningar om sitt arbete med pedagogisk dokumentation i förskolan. Att belysa variationer i förskollärares uppfattningar skapar möjlighet till yrkesmässig reflektion och fördjupning. Resultatet av den här studien kan ge förskollärare och rektorer verktyg för reflektion för att utveckla arbete med pedagogisk dokumentation i sin praktik.

This thesis uses vacancy chain analysis to investigate the complex dynamics of residential segregation within Stockholm County. Residential segregation has been a longstanding concern due to its implications for social inequality and community cohesion. While previous research has explored various factors contributing to segregation, this study focuses on understanding the intricate processes that drive neighborhood-level changes in occupancy patterns by analyzing the role of newly built dwellings. By studying the characteristics of the people that first move to the new dwellings and then the chains they create, the aim is to uncover segregating or desegregating patterns, which could prove essential for future residential planning.

The findings presented in this thesis shed light on the interconnected roles of individual preferences, socio-economic factors, and neighborhood characteristics in shaping segregation patterns and provide important insights for designing targeted interventions to promote more equitable and integrated communities. Neighborhoods that fall into the fourth income decile exhibit the most considerable desegregating effect both for first and subsequent moves. Knowing this, targeting housing construction for lower-income neighborhoods could produce the best results.

Diplomatic relations between Sweden and South Korea enabled international adoption. It progressed mostly between the 1960s and the 1980s. Concerning the aim for both countries, Sweden needed clear-cut and positive evidence to demonstrate the following social change: From race biology to multiculturalism. South Korea needed the foreign capital for national development. Adoptees were adopted without any appropriate support and deprivation of self determination, and they had to situate the discrimination and identity problem in Swedish society because of the absence of whiteness. This study is not only unpacking problems of identity for Korean transnational adoptees in Sweden but also deducing meaningful outcomes by looking into their stories through an in-depth interview.

Carbon capture and utilization has been proposed as an essential climate change mitigation strategy, but only a few implemented cases exist. During biomethane production from anaerobic digestion, CO₂ is commonly separated and emitted into the atmosphere, which can be utilized as raw material for various products. This research aims to identify and assess CO₂ utilization alternatives for possible integration with biogas upgrading from anaerobic digestion by developing a soft multi-criteria analysis (MCA). A literature review complemented with stakeholder participation enabled the identification of relevant alternatives and criteria for assessment. Potential alternatives for CO₂ utilization include methane, mineral carbonates, biomass production, fuels, chemicals, pH control, and liquefied CO₂. Results show that although no alternative performs well in all indicators, there is an opportunity for short-term implementation for methane, biomass production, mineral carbonates, liquefied CO₂, and pH control. Moreover, the uncertainty analysis reveals that even though the technologies have a high technological development, more information on critical aspects is still required. The soft MCA provides information to decision-makers, practitioners, and the academic community on learning opportunities of the alternatives and indicators to step from development into implementation. For instance, the method can be used to assess more specific systems with different locations and scales or to direct efforts to ease the implementation of CCU.

Allergy to pollen and animal dander is a major public health problem. Close to 30% of the population have symptoms from the upper and/or lower respiratory tract when they meet fur animals or pollen. Whereas symptom-relieving medications have a good to sufficient effect on about 80% of those affected, a large group of 10–20% have severe symptoms, despite medication, with an impact on well-being and ability to work. In Sweden, the annual cost of allergy was calculated at €1.3 billion in 2014.

Immunotherapy is effective in treating and preventing pollen allergy and allergic asthma, but is expensive, complicated, requiring 40 injections, and takes more than three years to complete if subcutaneous injections are used. Tablets placed under the tongue are another method, with one tablet taken every day for three years. Only 1.5‰ receive such treatment, yet just over 3% would need it.

With intralymphatic immunotherapy, a small dose of allergen is given in a lymph node in the groin on 3 occasions, one month apart. As this method takes only eight weeks, it is a much faster and less costly treatment. However, although several studies have shown that the treatment is safe, its efficacy remains the subject of doubt.

Our pilot study in 2012, with a 3-year follow-up to 2015, showed encouraging results, and was followed by a double-blind randomised study with 72 participants from 2014 to 2018. The research subjects then received treatment with birch and grass pollen extract or one extract and a placebo. Regardless of treatment, symptoms, quality of life and medication consumption improved during the birch and grass pollen seasons in the 3 years after treatment. Increased frequencies of T-regulatory lymphocytes may explain the non-specific effects.

In 2017 to 2018, we conducted a double-blind study with 38 participants, half of whom received placebo and half, active treatment. In this study, we saw no difference between the treatment groups in the first year after treatment. However, after discontinuation and unblinding in 2019, i.e., two years after treatment, the actively treated group improved in terms of symptoms, and quality of life was improved compared with the placebo group despite less need for medication. T-regulatory lymphocytes increased one year after treatment only in the actively treated group.

A long-term follow-up of the research subjects from our two larger studies in 2022, i.e., five to eight years after treatment, showed in the double-blind study without a pure placebo that the scores for symptoms, medication use, and quality of life remained as low as after the first three years. In the placebo-controlled study, a statistically significant improvement in symptoms remained during the grass pollen season. Analysing the two studies together, symptom improvement was significant even during the birch pollen season. Thus, although the effect does not seem to diminish, those who did not receive birch, but only grass, needed to use more medication during the birch pollen season in 2022, seven to eight years after treatment. Moreover, those who did not receive grass but only birch needed more medication during the grass pollen season. This may suggest that the non-specific effect begins to wane after seven to eight years.

Allergy to pollen is a major problem for individuals and society, where symptom-relieving treatment with drugs is not enough for many. They can be helped with immunotherapy, which takes at least three years, is expensive and fraught with side effects. In contrast, intralymphatic immunotherapy involves three injections over eight weeks. Our three studies show that the treatment is safe and indicate that it has a clinical effect up to eight years after treatment. T-regulatory cells appear to be important to the immunological mechanism, leading to tolerance to pollen.

Denna kvalitativa studie syftar till att undersöka specialpedagogers uppfattningar omelevhälsans främjande och förebyggande arbete utifrån deras yrkesroll. Uppsatsen fokuserar påframgångsfaktorer och specialpedagogens roll i ett hälsofrämjande och förebyggande samt vadbegreppet elevhälsa uppfattas stå för. För att skapa förståelse för det specialpedagoger berättarligger ett relationellt specialpedagogiskt perspektiv till grund för studiens analys. Arbetetinspirerades av grundad teori och genomfördes som en intervjustudie med semistruktureradeintervjuer, bestående av fem enskilda intervjuer med specialpedagoger. Intervjuerna ochtranskriberingarna av dem pågick till dess att mättnad uppnåtts. Grundad teori är en induktivmetod och studien har kommit fram till att genom att ha ett relationellt specialpedagogisktförhållningssätt i elevhälsoarbetet ökar möjligheten till ett mer främjande och förebyggandearbete.

Skollagen och läroplanen för grundskolan slår fast att det i varje svensk skola ska finnas enelevhälsa. Däremot beskrivs det inte någonstans hur ett sådant arbete ska organiseras, det liggerpå varje huvudman eller skola att besluta om. Informanterna i denna studie uttrycker att det ärotydligt vad elevhälsobegreppet står för. Det kan syfta till professionerna, insatserna, elevernashälsa eller den samlade elevhälsan. I studien framkommer att elevhälsoarbetet är hela skolansansvar och för att lyckas med det behöver det finnas en samsyn kring hur begreppet ska förståssamt en tydlig och strukturerad organisation av arbetet. Informanterna poängterar vikten av entydlig ledare i elevhälsoarbetet och beskriver rektor som den givna ledaren som ska organiseraför ett främjande och förebyggande elevhälsoarbete som genomsyrar hela verksamheten. Detframkommer tydligt att rektors arbete påverkar hur väl skolan lyckas i sitt elevhälsoarbete. Iresultatet framträder specialpedagogen som en nyckelperson i elevhälsoarbetet genom att isamverkan med andra upptäcka, göra bedömningar och analysera samt planera och genomföraåtgärder på både organisations-, grupp- och individnivå. Vidare framkommer att rektor ochspecialpedagog kompletterar varandra och att det är framgångsrikt för elevhälsoarbetet när dearbetar nära varandra. Resultatet visar att detta sammantaget ger implikationer för detspecialpedagogiska arbetet på skolorna. Studien kan därför inspirera specialpedagoger i detfrämjande och förebyggande elevhälsoarbetet. 

The uncertainty in the prediction calculated using the delta method for an over-parameterized (parametric) black-box model is shown to be larger or equal to the uncertainty in the prediction of a canonical (minimal) model. Equality holds if the additional parameters of the overparameterized model do not add flexibility to the model. As a conclusion, for an overparameterized black-box model, the calculated uncertainty in the prediction by the delta method is not underestimated. The results are shown analytically and are validated in a simulation experiment where the relationship between the normalized traction force and the wheel slip of a car is modelled using e.g., a neural network.

Society today brings a high pace development and demand of Artificial intelligence systems as well as robotics. To further expand and to take one step closer to have Unmanned Aerial Vehicles (UAVs) working in the cities, the European Union Aviation Safety Agency launched a project that introduces U-space airspace, an airspace where UAVs, for instance, are allowed to operate for commercial services.The problems defined for U-space airspace resemble problems defined in the area of multi-agent path finding, such as scaling and traffic etc., resulting an interest to research whether MAPF-solutions can be applied to U-space scenarios. The following thesis extends the state-of-the-art MAPF-algorithm Continuous-time Conflict based search (CCBS) to handle simplified U-space scenarios, as well as extend other A*-based algorithms, such as a version of the Receding Horizon Lattice-based Motion Planning named Extended Multi-agent A* algorithm with Wait-Time (EMAWT) and an extended A* named Extended Multi-agent A* algorithm (EMA) to handle them. Comparisons of the three algorithms resulted in the EMAWT being the most reliable and stable solution throughout all tests, whilst for fewer agents, the CCBS being the clear best solution.

Atrial fibrillation (AF) is the most common arrhythmia seen in clinical practice. In cardiac surgery, the negative influence of AF on short- and long-term outcomes has made concomitant ablation procedures more common. The indications, clinical aspects, results, risks, and benefits of the additional surgical ablation are still valuable topics for discussion. This compilation thesis consists of four papers aiming to investigate some of the clinical, biochemical, and echocardiographic aspects of surgical ablation for AF (Cox-Maze IV) when performed concomitant to mitral valve surgery (MVS).

Through a retrospective, case-control, single-center study, we described the impact of the Cox-Maze IV procedure added to MVS with focus on postoperative heart failure (paper I).

Cryoenergy (cryo) and radiofrequency (RF) are the two different energy sources mainly used in Cox-Maze IV for AF ablation. To achieve linear scars in the atrial wall, the RF procedure uses heat damage, whereas the cryo method freezes down to -150°C. Through a prospective, randomized, longitudinal, controlled study, we compared the biochemical responses of the two ablative methods in concomitant MVS and the release of enzymes expressing myocardial injury, as well as inflammatory, cell stress, and apoptosis-specific proteins. We could show that cryo results in a larger release of markers for myocardial damage but has no impact on the early inflammatory response (paper II).

Extended scar lesions resulting after maze may influence atrial function. As the left atrium plays a key role in the altered cardiac hemodynamics in AF, an echocardiographic analysis of the effects of the Cox-Maze IV procedure concomitant to MVS on the left atrium was carried out. The impacts of the two energy sources (cryo and RF) on left atrial remodeling and function had not been compared previously. Their direct effect on left atrial remodeling and mechanical function were assessed 1 year after surgery in patients with restored sinus rhythm. Sinus rhythm restoration after MVS concomitant to Cox-Maze IV results in a reduced left atrium size regardless of the energy source used. Three-dimensional echocardiography showed that, compared to RF, the extension of the ablation area produced by cryo implies major left atrium structural remodeling affecting systolic function. The negative effect on left atrium remodeling seems to be linear with the duration of the AF (paper III).

An overview of the pacemaker implantation rate after the Cox-Maze IV procedure concomitant to MVS was obtained in a multicenter study using national qualitative registers (SWEDHEART, Carath, Svenska ICD- och Pacemakerregistret) (paper IV, sumbitted).

Our results contribute to optimizing surgical indications and patient selection, providing a deeper understanding of the biochemical and echocardiographic changes during and after surgical ablation.

_{This study aims to provide insights into the factors shaping electricity demand in Swedish industrial sectors using the nonlinear version of the autoregressive distributed lag model (NARDL). This approach captures the complex short- and long-run relationships between uncertainty and electric power use in Swedish industrial sectors. The results reveal sector-specific responses to uncertainties and asymmetries in electricity use patterns. By examining the entire industrial sector in Sweden, this approach uncovers underlying issues and hidden patterns, while also providing insights into the functioning and behaviour of industrial systems. The rapid electrification and new green industrialisation initiatives in Sweden, coupled with the integration of a circular economy, underscore the importance of understanding the dynamics of electricity use in the face of uncertain shocks. This knowledge is vital for ensuring, amongst other things, grid stability, mitigating the need for costly peaking capacity, and identifying potential challenges in the interconnection of energy and material circular flows}

Micro-Doppler effects are phenomena that occur because of micro-motion. A micro-motion is either a vibration, rotation, or acceleration which is small relative to the motion of the target. These effects can be used in order to characterize a target through their signature movement. These effects were captured using a Frequency Modulated Continous Wave (FMCW) radar on several targets with a distinct signature. The targets were a four-armed drone, a cyclist, and a pedestrian. Using conventional- and super-resolution algorithms allows the user to process the captured data. To best be able to determine these signatures, different algorithms were used, Short-Time Fourier Transform (STFT), Smoothed Pseudo-Wigner-Ville Distribution (SPWVD), Pade Fourier approximation (PFA), and MUltiple SIgnal Classification (MUSIC). The comparison of the algorithms on the measured data was done in MATLAB where the best possible scenario was taken. From the comparison, it was noticed that in order to capture the most details, the MUSIC, PFA, STFT, and SPWVD performed the best with a decreasing order.

Background: Increasing demand for sustainability information during the last two decades has led to enactment of mandatory sustainability reporting, for example through Directive 2014/95/EU. As a result of mandatory sustainability reporting, companies must integrate sustainability management control systems to comply with reporting requirements. 

Purpose: The purpose of this paper is to explain how sustainability management has been affected due to mandatory reporting on sustainability and how sustainability management has affected the quality of sustainability reporting.

Research method: The study applies a quantitative method through content analysis and quasi-experiments. The content analysis is carried out on ten Swedish listed companies’ annual- and sustainability reports for the fiscal years 2013-2022.

Results: The result shows that mandatory regulation has a positive relationship with sustainability management. Cultural-, administrative- and cybernetic controls have had the greatest increase due to mandatory regulation. Furthermore, there is a positive relationship between sustainability management and reporting quality. 

Contributions: This study contributes to the literature on the relationship between sustainability management and sustainability reporting. It also makes a methodological contribution through a constructed sustainability management control index.

This master thesis work has been executed at Volvo GTT in Gothenburg. Focus has beenlaid on implementing a hydraulic front wheel drive (HFWD) system on a battery electricvehicle (BEV). The earlier concept builds have been performed on internal combustionengine (ICE) driven trucks at Volvo Trucks. The main difference in implementing thesystem on a BEV lies in the change of power take-off (PTO) which on a BEV is totallyindependent of the driving engine and cannot use the idle for rotating the charge pumpduring the inactive mode of the HFWD system. On the other hand, this opens up increasedcontrollability with many possibilities for improving the efficiency of the system. 

Using efficiency maps of selected components, simulations have been performed tofind out the final energy consumption. Those are partly for the engaged mode where theHFWD is active and partly for when it is inactive. Different control strategies are comparedfor the active mode, including variating the electric motor, hydraulic pump, or both. Forthe inactive mode, one concept using a separate electric motor for a separate charge pumpand one concept removing the charge pump and running the main pump in cycles arecompared with the reference concept.

The work resulted in a component- and CAD specification for a reference concept readyto be built within the near future, together with two concepts that can improve the energyefficiency of the HFWD system when operating in the disengaged mode. Results are alsoachieved for the active mode. Simulations show that controlling the pressure and flowby both the electric motor and the hydraulic pump is theoretically the most efficient, butmight bring difficulties in practice. The simulation analysis of the inactive mode showsthat fitting a separate DC motor for the charge pump will lower the disengaged energyconsumption by around 50%. Simultaneously, investigations show that removing thecharge pump completely might be an interesting way of designing the system, dependingon what temperature conditions the application will be used it may decrease the energyconsumption. 

Our recommendation is to first build the reference concept according to the specificationpresented in the report on an actual truck to be able to validate the simulations. Thereafter the practical results can be evaluated and solutions from the alternative concepts beinserted with improved efficiency as a preliminary outcome.

The 3rd Swedish Symposium on Furniture Technology& Design was held in Stockholm the 16th through the19th of September 2022, this time arranged by MalmstensAlumni in collaboration with the Swedish History Museum,Skokloster Castle and LiU Malmstens.

Contents:

Foreword page 6Ulf Brunne, Chairman, Malmstens Alumni

Woodworking Tools and Techniques – Technical and Aesthetical Aspects of Furniture Design and Cabinetmaking through the Ages page 7Johan Knutsson, Professor in Furniture Culture LiU Malmstens, Sweden

From Tool Marks to Work Practises page 14Hans Piena, Curator of Domestic Culture, Dutch Open Air Museum, The Netherlands

Characteristics of Japanese Woodworking Tools page 21Kenji Komatsu, Woodworker/Artist, Wood Workshop BYHAND, Japan

A Reconstruction of an Early 16th Century Tondo Frame page 29Iskander Breebaart, Senior Furniture Conservator Rijksmuseum, The Netherlands

Wave Mouldings and Ornamental Lathe page 37Josephine Erckrath, Cabinetmaker and Furniture Conservator Møbelarkitekt Tyge Axel Holm, Denmark

Dutch Moulding Planes from Skokloster Castle, Sweden page 42Jaap Boonstra, Furniture Conservator, Amsterdam Museum, The Netherlands, Pol Bruijs, Furniture Conservator, Private Practise, The Netherlands

Mahogany Spheres – Reconstruction of an Artistically Crafted Element of a Writing Cabinet by the Berlin Ebenist Joseph Schneevogl (1795–1864) page 54Prof. Dr. Angelika Rauch, University of Applied Sciences, Potsdam, GermanyDipl.-Rest. Jörg Weber, Head of Workshop, University of Applied Sciences Potsdam, Germany

Construction Features that are Typical for Marquetry Cabinets by Jan van Mekeren page 60Paul van Duin, Head of Furniture Conservation, Rijksmuseum, The NetherlandsIskander Breebaart, Senior Furniture Conservator, Rijksmuseum, The Netherlands

Australian Timbers and Contemporary Woodworking page 68Evan Dunstone, Dunstone Design, Australia

Woodworking as Means for Understanding and Developing the Human-Technology Relationship – Discussed Through the Work of Cabinet Maker Thomas Tempte page 74Andreas Nobel, Professor in Furniture Design LiU Malmstens, Sweden

The Future of Furniture Craft Education – a Churchill Fellowship page 80Joseph Bray, Head of Wood School Sylva Foundation, UK

Applied Information Technology and Mathematics in Woodturning page 86Ulf Jansson, Engineer and Woodturner Private Practise, Sweden

OpenAI GPT-4 was used to generate a hypothetical scenario for the development of a hypothetical new multi-role airlift. A dataset containing the conversation leading up to this document is available under "Conversation history from Scenario Generation with OpenAI GPT-4"

This dataset contains the conversation history where OpenAI GPT-4 is asked to generate a hypothetical scenario for the development of a new hypothetical multi-role tactical airlift. The dataset contains all user input and the OpenAI GPT-4 output, including the graphical representations of the ontology. The generated word-file, containing the generated scenario, is stored in a separate dataset: "CHAMP Operational Scenario generated from OpenAI GPT-4"

Compilers, complex programs with the potential to greatly facilitate software and hardware design. This thesis focuses on enhancing the Spade hardware description language, known for its user-friendly approach to hardware design. In the realm of hardware development data size - for numerical values data size is known as "wordlength" - plays a critical role for reducing the hardware resources. This study presents an innovative approach that seamlessly integrates wordlength inference directly into the Spade language, enabling the over-estimation of numeric data sizes solely from the program's source code.

The methodology involves iterative development, incorporating various smaller implementations and evaluations, reminiscent of an agile approach. To assess the efficacy of the wordlength inference, multiple place and route operations are performed on identical Spade code using various versions of nextpnr. Surprisingly, no discernible impact on hardware resource utilization emerges from the modifications introduced in this thesis.

Nonetheless, the true significance of this endeavor lies in its potential to unlock more advanced language features within the Spade compiler. It is important to note that while the wordlength inference proposed in this thesis shows promise, it necessitates further integration efforts to realize its full potential.

Chromium-based nitrides are used in hard, resilient coatings and show promise for thermoelectric applications due to their combination of structural, thermal, and electronic properties. Here, we investigate the electronic structures and chemical bonding correlated to the thermoelectric properties of epitaxially grown chromium-based multicomponent nitride Cr(Mo,V)Nx thin films. The small amount of N vacancies causes Cr 3d and N 2p states to appear at the Fermi level and reduces the band gap in Cr0.51N0.49. Incorporating holes by alloying of V in N-deficient CrN results in an enhanced thermoelectric power factor with marginal change in the charge transfer of Cr to N compared with Cr0.51N0.49. Further alloying of Mo, isoelectronic to Cr, increases the density of states at the Fermi level due to hybridization of the (Cr, V) 3d and Mo 4d-N 2p states in Cr(Mo,V)Nx. This hybridization and N off-stoichiometry result in more metal-like electrical resistivity and reduction in Seebeck coefficient. The N deficiency in Cr(Mo,V)Nx also depicts a critical role in reduction of the charge transfer from metal to N site compared with Cr0.51N0.49 and Cr0.50V0.03N0.47. In this paper, we envisage ways for enhancing thermoelectric properties through electronic band engineering by alloying and competing effects of N vacancies.

This study belongs to the research tradition Participatory Action Research (PAR) in the form of a Research Circle. The task was to describe and analyse the process and content of knowledge development within a Research Circle. The participants in this circle were nine teacher who work at komvux, and teach adult students in subject such as SFI, SVA and English. In this circle with participating teachers, issues of individually adapted teaching in adult education have been in focus. In this circle, empirical data has been highlighted by having the participants tell life stories and in group interviews about the individualized teaching. In an interaction between the participants´ experiences of individually adapted teaching and previous research in this area, we in the circle developed methods for individually adapted teaching in adult education. The participants tried these methods in their teaching. The methods that were developed for individually adapted teaching were both broadly and comprehensive designed, which was positive because then the teacher can adapt the teaching methods to each student group and individual adult student. The result indicate that the individually adapted teaching needs to be designed based on individual teaching, one to one teaching between teacher and adult student. Then the adult student can receive individual support in their studies and receive tasks that are individually adapted to the student´s ability to study. It is also important that the teaching is designed based on relational teaching, were the adult student both meets the teacher and other students during the course of study. This means different working methods in teaching that are individually adapted based on relational teaching. Relational teaching is especially important in language teaching. It has also been highlighted methods for individually adapted teaching based on digital teaching which is both based on individual teaching and relational teaching. This digital teaching is based on different working methods that are highlighted in this study. 

Everything should come together, and everything should permeate everything. Trends in governance and policy areas have come to encompass increasingly broader and more diverse issues. For example, sustainable development should guide all parts of government, but there is often little guidance on what this means in practice and how organizations should tackle the diverse issues and challenges of sustainability. Overall, much indicates that the challenges and problems faced by decision-makers in public administration have become increasingly difficult to manage. Some of these problems are particularly challenging and cannot be solved with a short term solution, by a single actor, or by an established method. These problems can only be managed and are referred to as "wicked problems" in the literature.

The dissertation focuses on two wicked problems: sustainability and a pandemic. The analysis address how these wicked problems are handled by local public authorities in Sweden. Both problems have an unclear scope, a vague definition, and no definitive solution within reach. The overshadowing argument is that wicked problems need to be framed to be managed through policy mechanisms and implementation processes. The thesis argues that a frame determines and delimits the issue at hand, thus configuring what becomes manageable or not in practice.

The dissertation is based on a selection of empirical case studies aimed at observing how governments translate the problems they face by handling both the need to become more sustainable and balancing the needs during a pandemic through changes and modifying the discourse. The study employs an interpretive and constructivist analysis of document studies and interviews with key stakeholders.

The overarching conclusions indicate that framing is a central process necessary to move wicked problems forward on the political agenda and make them manageable. In this way, framing helps to delimit the problems; the framing becomes crucial for what becomes manageable and what is left out. Frames have different characteristics, which then influence how the problem is addressed. The conclusions suggest a continued need to make the wickedness of policy problems visible, to consider the larger and more complex aspects of certain political issues, and to strive to identify different mechanisms for managing them. We can see that framing is not just about coping with wicked issues but also about redefining the understanding of wicked problems to align more closely with an organization's limitations and possibilities. Framing offers the possibility to bridge, merge, or even transform our understanding of the wicked problem through the social reality of the organization.

This dataset contains the conversation history where OpenAI GPT-4 is asked to analyze a text, is asked to create an ontology and then visualize it in a graph. The dataset contains all user input and the OpenAI GPT-4 output, including the graphical representations of the ontology. The dataset also contains a JSON file that was generated that describes the ontology.

The primary objective of this study is to examine the viability of developing a chair with a significantly reduced carbon footprint. The research explores two distinct approaches for achieving minimal material usage in the construction process: one involving a minimal amount of wood, and the other utilizing solely wooden waste. By employing the technique of steam bending, a robust, lightweight, and durable structure can be achieved. Additionally, by harnessing the binding properties of mycelium, waste wood materials can be molded together to form a solid composite. This thesis will document the design process of two chairs that employ these two methods.

Complex autoimmune diseases, such as multiple sclerosis (MS), develop as a result of perturbations in the regulatory system controlling the function of immune cells. The disease course of MS is heterogeneous but is characterised by chronic inflammation in the central nervous system causing neurodegeneration resulting in gradual disability worsening. Disease biomarkers which are present at early stages of a disease can help clinicians to tailor treatment strategies to the expected disease course of individual persons. Gene products, i.e. RNA and proteins, serve as promising disease biomarkers due to the possibility to detect changes in abundance at early stages of a disease. Putative biomarkers can be identified by modelling different levels of gene regulation from high-throughput measurements of gene product abundance. Extracting information of disease relevance from high-throughput data is a complex problem which requires the use of efficient and targeted computational algorithms. 

The aim of this thesis was to develop and refine methods for identifying key biomarkers involved in the development and progression of complex diseases, with the main focus on MS. In Paper I, we used a machine learning approach to identify a combination of protein biomarkers, present in the cerebrospinal fluid, which could predict the disease trajectory of persons in the early stages of MS. The abundance of proteins is a result of an intricate network of multiple regulatory factors controlling the expression of genes. A large part of the expression of genes is controlled by a few key regulators, which are believed to be crucial for the development of diseases. In addition, disease-associated genes are believed to colocalise in these networks forming so called disease modules. In Paper II, we developed a method, named ComHub, for extracting the key regulators of gene expression. In Paper III, we combined ComHub with the tool MODifieR, for disease module predictions, in a network analysis pipeline for identifying a limited set of disease-associated genes. Using this network analysis pipeline we identified a set of MS-associated genes, as well as a promising key regulator of MS. 

The work performed in this doctoral thesis covers development of new and refined methods for modelling complex diseases, while simultaneously utilising these methods to identify disease biomarkers important for the development and progression of MS. The identified biomarkers can be used for understanding the pathology of MS, as candidate drug targets, and as promising biomarkers to aid clinicians in tailoring treatment strategies to individual persons. 

Sensitive and reliable protein biomarkers are needed to predict disease trajectory and personalize treatment strategies for multiple sclerosis (MS). Here, we use the highly sensitive proximity-extension assay combined with next-generation sequencing (Olink Explore) to quantify 1463 proteins in cerebrospinal fluid (CSF) and plasma from 143 people with early-stage MS and 43 healthy controls. With longitudinally followed discovery and replication cohorts, we identify CSF proteins that consistently predicted both short- and long-term disease progression. Lower levels of neurofilament light chain (NfL) in CSF is superior in predicting the absence of disease activity two years after sampling (replication AUC = 0.77) compared to all other tested proteins. Importantly, we also identify a combination of 11 CSF proteins (CXCL13, LTA, FCN2, ICAM3, LY9, SLAMF7, TYMP, CHI3L1, FYB1, TNFRSF1B and NfL) that predict the severity of disability worsening according to the normalized age-related MS severity score (replication AUC = 0.90). The identification of these proteins may help elucidate pathogenetic processes and might aid decisions on treatment strategies for persons with MS.

The retinal ganglion cell is situated in the inner retina and its axons, composing the retinal nerve fiber layer (RNFL), leave the eye to form the optic nerve. These cells develop embryologically from the forebrain and later during development re-establish connections with different parts of the brain serving different purposes. This unique position and connections make it possible to be investigated with different methods. Optical Coherence Tomography (OCT) is an accessible and easily operated clinical device that can provide a detailed image of this layer at a few micrometers level of precision in measurements. In this thesis we aimed to see whether examining these cells with OCT could reflect physiological and pathological changes in the eye and brain.

In cases of optic neuritis (Paper I), the OCT examination showed early thickening of the peripapillary (pRNFL) followed by thinning which takes 6-9 months to reduce to below normal thickness without the ability to distinguish between the real from pseudo thinning. The ganglion cell -inner plexiform layer (GCL-IPL) layer, however, showed a thickness reduction within a few weeks to 3 months without pseudo thinning.         

In cases of Idiopathic Intracranial Hypertension (IIH) (Paper II), the GCL-IPL remained unchanged and there was no difference in pRNFL thickness compared to healthy controls, whereas  the optic disc parameters of rim thickness, rim area, cup volume and cup/disc ratio differed significantly (P<0.05).

In cases of benign multiple sclerosis (Paper IV), the OCT could detect that eyes which are not affected by optic neuritis had an annual thinning rate of the RNFL and GCL-IPL similar to a healthy population (P>0.05) which may indicate the benign course of the disease.       

In cases of physiological factors affecting the GCL in healthy population (Paper III) the OCT examination showed that there was a significant thinning rate of the layer with age (P<0.05), but the thinning was not significant when sex and axial length of the eye were taken into consideration. Males had a thicker GCL volume than females and with age a significant reduction in GCL volume was noted in females but not in males. A Longer axial length of the eye found to be associated with thinner GCL volume.     

In conclusion retinal ganglion cell changes detected with OCT can reflect physiological and pathological changes in the eye and brain.   

This dissertation presents empirical research in the field of multilingual communication in residential homes of people living with dementia.  

Prior research has emphasised the crucial function of a common language and culture between care workers and residents in such settings. It has been argued that a shared language is essential for fostering mutual understanding between care workers and residents with dementia. The absence of a common language can result in significant issues, such as creating misconceptions about the capabilities of multilingual residents, potentially preventing care workers from recognising the residents' communicative abilities. This can prevent residents with dementia from participating in social activities, leading to social isolation and negatively impact their well-being. This, in turn, increases costs for all parties involved, including residents, care workers, and residential homes.  

While the significance of a shared language for mutual understanding is undeniable, it's not always feasible to match care workers and residents linguistically and culturally in a multilingual society with diverse ethnic groups. This situation prompts questions about how to achieve mutual understanding in the absence of a shared language in residential homes. This dissertation investigates how care workers and residents from various linguistic and cultural backgrounds in dementia care achieve mutual understanding during task-oriented communication, despite the absence of a shared verbal language.  

Employing a micro-analytic perspective, this research delves deep into instances of multilingual communication within residential homes to uncover the function of linguistic features such as sound prolongation in task-oriented communication. Additionally, the study explores how forms of address contribute to achieving mutual understanding in dementia care when there's no shared verbal language in multilingual communication. These questions are addressed using data obtained through a combination of ethnography, video recordings, and interviews. The study involves participants, including residents from ethnic minorities displaying symptoms of dementia and care workers from diverse linguistic backgrounds.  

Conversation analysis is employed for transcribing and analysing interactions among participants, while thematic analysis is applied to the interview data. The results suggest that in the absence of a common verbal language, participants recycle each other's verbal and nonverbal actions to foster mutual understanding. This process relies heavily on the actions of care workers. The findings also underscore the importance of care workers’ knowledge of residents' life histories, including their preferred forms of address, as a valuable resource for establishing rapport with residents.  

In conclusion, this dissertation highlights that the effectiveness of specific linguistic resources in multilingual communication not only varies among individuals but is also contingent on the particular situations in which a resident is involved. 

Machine-learning potentials provide computationally efficient and accurate approximations of the Born–Oppenheimer potential energy surface. This potential determines many materials properties and simulation techniques usually require its gradients, in particular forces and stress for molecular dynamics, and heat flux for thermal transport properties. Recently developed potentials feature high body order and can include equivariant semi-local interactions through message-passing mechanisms. Due to their complex functional forms, they rely on automatic differentiation (AD), overcoming the need for manual implementations or finite-difference schemes to evaluate gradients. This study discusses how to use AD to efficiently obtain forces, stress, and heat flux for such potentials, and provides a model-independent implementation. The method is tested on the Lennard-Jones potential, and then applied to predict cohesive properties and thermal conductivity of tin selenide using an equivariant message-passing neural network potential.

With optical techniques, we refer to a group of methods that use of light to perform measurements on matter. Spatial frequency domain imaging (SFDI) is an optical technique that operates in the spatial frequency domain. The technique involves using sinusoidal patterns of light for illumination, to study the reflectance of the target based on the spatial frequency (ƒ_x) of the patterns. By analysing the frequency-specific response with the aid of light transport models, we are able to determine the intrinsic optical properties of the material, such as the absorption coefficient (μ_a) and reduced scattering coefficient (μ'_s) In biological applications, these optical properties can be correlated to physiological structures and molecules, providing a useful tool for researchers and clinicians alike in understanding the phenomena happening in biological tissue. The objective of this work is to contribute to the development of SFDI, so that the technique can be used as a diagnostic tool to study the process of wound healing in tissue. In paper I we introduce the concept of cross-channels, given by the spectral overlap of the broadband LED light sources and the RGB camera sensors used in the SFDI instrumentation. The purpose of cross-channels is to improve the limited spectral information of RGB devices, allowing to detect a larger number of biological molecules. One of the biggest limitations of SFDI is that it works on the assumption of light diffusing through a homogeneous, thick layer of material. This assumption loses validity when we want to examine biological tissue, which comprises multiple thin layers with different properties. In paper IV we have developed a new method to process SFDI data that we call multi-frequency SFDI. In this new approach, we make use of the different penetration depth of the light patterns depending on their ƒx to obtain depth-sensitive measurements. We also defined a 2-layer model of light scattering that imitates the physiology of a wound, to calculate the partial volume contributions to μ's of the single layers. The 2-layer model is based on analytical formulations of light fluence. We compared the performance of three fluence models, one of which we have derived ourselves as an improvement over an existing formulation. In paper II we were able to test our new multi-frequency SFDI method by participating in an animal study on stem-cells based regenerative therapies. We contributed by performing SFDI measurements on healing wounds, in order to provide an additional evaluation metric that complemented the clinical evaluation and cell histology performed in the study. The analysis of the SFDI data at different ƒx highlighted different processes happening on the surface compared to the deeper tissue. In paper V we further refine the technique introduced in paper IV by developing an inverse solver algorithm to isolate the thickness of the thin layer and the layer-specific μ's. The reconstructed parameters were tested both on thin silicone optical phantoms and ex-vivo burn wounds treated with stem cells. 

Wnt/β-catenin signalling, also referred to as canonical Wnt signalling, is a critical regulator of tissue homeostasis and of the differentiation of cells during development. The outcome of canonical Wnt pathway activity is defined by the regulation of target gene transcription, which ultimately determines cell identity and proliferation. How multiple proteins coordinate to modulate Wnt signalling in numerous tissues is an evolving question.

Over the years, FOX transcription factors have been emerging as modulators of Wnt signalling in a variety of tissue and cell-specific contexts. Nevertheless, the function of each FOX protein in the pathway as well as their role in different pathophysiological contexts is an open matter.

The overall aim of this thesis was to investigate two FOX family members, FOXB2 and FOXQ1, to uncover their roles in Wnt/β-catenin signalling. Additionally, in the last work, I aimed to investigate how the FOXQ1 oncogene is transcriptionally regulated in cancer.

In the first paper, we uncovered FOXB2 as a new potent activator of Wnt signalling via the induction of agonistic Wnt ligands, particularly WNT7B. In addition, FOXB2 is induced in aggressive prostate cancer where it is associated with a neuroendocrine differentiation program and poor prognosis.

In the second paper, we explored the molecular mechanisms used by the carcinoma oncogene FOXQ1 to drive Wnt signalling activation. Our results showed that FOXQ1 has a major role in tuning the Wnt transcriptional output and, in synergy with active Wnt signalling, converged on a transcriptional program linked to epithelial-to-mesenchymal transition (EMT) and cell migration, which has important implications for cancer biology.

In the third paper, we reveal that p53 functions as transcriptional repressor of FOXQ1 in cancers. Loss of p53 is present in the majority of human cancers and, in synergy with activation of Wnt signalling, could boost FOXQ1 expression, thereby affecting the progression of cancer.

Overall, this thesis provides a better understanding of the complexity of Wnt signalling on the molecular level and newly elucidates the function of these two FOX proteins as drivers of oncogenic Wnt pathway activation. Additionally, this new evidence highlights the importance of further in-depth investigation of FOX transcription factors in cancer biology. The relevant role of FOX proteins in the development and progression of cancer is increasingly evident, and in the long run, it will be valuable to characterize the role of FOX factors in a tissue-specific context for the development of targeted cancer therapies.

Most research on emotions, including that which takes a social perspective, is directed at negative emotions and their manifestation in social situations that involve conflicts, disputes, and arguments. This thesis instead aims to address children’s heightened positive emotions and their interactional functions within the peer group and in learning encounters with teachers in preschool. Theoretically and methodologically, the thesis adopts a multimodal interaction analysis perspective. The data comprises 40 hours of video-ethnographic recordings of everyday activities conducted in a regular preschool in Sweden. The participants include 6 teachers and 50 children (ages 1-5, girls and boys). The following research questions underpin the thesis: How do young children invite co-participation and reciprocate laughter in multiparty interactions with peers and teachers? How do young children invoke excitement displays to initiate joint attention in multiparty peer settings in preschool? How do teachers choreograph suspense practices as a means to organize participation in educational activities? The thesis highlights the communicative and social affordances and challenges that young children encounter when interacting in large groups in preschool settings. The thesis contributes with knowledge in a largely unexplored area, i.e., heightened emotional displays in children’s peer groups, and adult-child interactions.

Background: Heart failure (HF) is a common condition, and its prevalence is expected to increase. The illness trajectory is unpredictable, and its effects will include a potential impact on informal carers, i.e., family, friends, and significant others. Sometimes these persons are affected by the help and care they provide in such a way that they might themselves need support. However, they may be unrecognised in their endeavours, and might also experience a lack of support, especially from healthcare. Online solutions are considered to have the potential to provide accessible support to carers that is also anticipated to be cost-effective.   

Aim: This thesis focuses on support to informal carers to persons living with HF, but also take the viewpoint of the person with HF by exploring social supports associations with their health and well-being. The overall aim was to explore perceptions, development, and experiences of online support for informal carers.  

Method: This thesis comprises four studies. Study I had a cross-sectional design using self-reported data and data from the Swedish Pace-maker and ICD Registry. Data from 1,550 persons with HF who were living with an ICD and who had complete data on the outcome variable were utilised for both descriptive analysis and logistic regression. The outcome variable, perceived social support, was measured using the questionnaire Multidimensional Scale of Perceived Social Support (MSPSS), which includes measuring support from significant others, family, and friends. The logistic regression was conducted to compare those dichotomised as having low/medium perceived social support to those having high levels of support. Study II had a qualitative design, and data were collected through 8 focus groups with 23 informal carers of persons with HF to explore their perceptions of how online solutions could be of value for support. Data were analysed using qualitative content analysis. Study III had a descriptive design. It describes the co-design process of an online support pro-gramme for carers through three phases. In phase I, topics and content that reflected carers needs and preferences were identified. In phase II, the content for the support programme was developed and through phase III the content was refined and finalised. Informal carers participated in every phase, and the co-design process also involved professionals with expertise in, for example, HF and caregiving, for the development of content. It was an iterative process, moving back and forth between phases, and the re-search group acted as coordinators and ensured that carers’ voices were kept central to the process. Study IV had a qualitative design, and data were collected through individual semi-structured interviews with 15 carers. Interviews were analysed using qualitative content analysis. The study focused on informal carers' experiences of online, co-designed support pro-gramme while being participants in a randomised controlled trial (RCT) that has the aim of studying the effects of engaging with the programme.  

Results: The findings show that one in five diagnosed with HF and living with an ICD reported low/medium levels of social support and that these persons had higher odds of negative psychosocial outcomes. This un-derscores the value and importance of support from informal carers for the well-being of those with HF. The thesis focused on perceptions, development, and experiences of online support for informal carers. The findings suggest that a co-designed support programme has the potential to be usable and useful for carers considering the online format and its content. It may provide insights, preparedness, and validation in relation to being a carer of a person with HF. However, carers may have an ‘ambiguous stance’ towards the online format and going online for support may not be the preferred form of support for all carers.   

Conclusion: A co-designed online support programme, when built on a trusted platform within a healthcare context, may be considered both usable and useful for carers. The online format and content also provide the potential to offer timely and adaptable support. The content, developed in a collaboration between carers and professionals, offers evidence-based, relevant information, thereby possibly avoiding seeming impersonal, which can also be beneficial. The programme acknowledges the intertwined lives of carers and those with HF, and its content reflects this, potentially also enhancing its perception as usable and useful for carers. Still, the potential of the support programme depends on carers being aware of its existence, or being made aware, and can further recognise its value. The support programme is considered to have the capacity to be relevant for a broad group of carers, and therefore efforts may be of importance to ensure it is accessed and utilised. However, it is also important to take into account that not everyone may be willing or able to go online for support, or may wish to stay in a caring role. Healthcare also needs to recognise this when offering support to carers and the online support may be regarded an option among several. 

Most commodity processors available today provide hardware-supported security extensions. Remote attestation has been declared an important step towards providing security to users through such solutions, yet remote attestation has seen limited deployment in practice. For existing protocols, analysis of the protocol security is not always publicly available. This thesis utilises formal methods in order to investigate an existing remote attestation protocol in the form of Samsung Knox Enhanced Attestation V3 developed by Samsung for Samsung Knox devices. Requirements are formalised into verifiable security properties. Formal verification reveals a minor weakness when considering strong adversarial models that can control parts of the device through run-time attacks. Such adversarial models are generally stronger than what is typically considered for Knox devices. This thesis also develops general remote attestation protocols which remedy the found weakness with a simple mechanism. Our developed protocols are formally verified, showing that they are suitable for platforms with Trusted Execution Environments even when considering strong adversarial models.

Training a deep neural network is computationally expensive, but achieving the same network performance with less computation is possible if the training data is carefully chosen. However, selecting input samples during training is challenging as their true importance for the optimization is unknown. Furthermore, evaluation of the importance of individual samples must be computationally efficient and unbiased. In this paper, we present a new input data importance sampling strategy for reducing the training time of deep neural networks. We investigate different importance metrics that can be efficiently retrieved as they are available during training, i.e., the training loss and gradient norm. We found that choosing only samples with large loss or gradient norm, which are hard for the network to learn, is not optimal for the network performance. Instead, we introduce an importance sampling strategy that selects samples based on the cumulative distribution function of the loss and gradient norm, thereby making it more likely to choose hard samples while still including easy ones. The behavior of the proposed strategy is first analyzed on a synthetic dataset, and then evaluated in the application of classification of malignant cancer in digital pathology image patches. As pathology images contain many repetitive patterns, there could be significant gains in focusing on features that contribute stronger to the optimization. Finally, we show how the importance sampling process can be used to gain insights about the input data through visualization of samples that are found most or least useful for the training.

High performance computing is a topic that has risen to the top in the era ofdigitalization, AI and automation. Therefore, the search for more cost and timeeffective ways to implement HPC work is always a subject extensively researched.One part of this is to have hardware that is capable to improve on these criteria. Different hardware usually have different code languages to implement theseworks though, cross-platform solution like Intel’s oneAPI framework is startingto gaining popularity.In this thesis, the capabilities of Intel’s oneAPI framework to implement andexecute HPC benchmarks on different hardware platforms will be discussed. Using the hardware available through Intel’s DevCloud services, Intel’s Xeon Gold6128, Intel’s UHD Graphics P630 and the Arria10 FPGA board were all chosento use for implementation. The benchmarks that were chosen to be used wereGEMM (General Matrix Multiplication) and BUDE (Bristol University DockingEngine). They were implemented using DPC++ (Data Parallel C++), Intel’s ownSYCL-based C++ extension. The benchmarks were also tried to be improved uponwith HPC speed-up methods like loop unrolling and some hardware manipulation.The performance for CPU and GPU were recorded and compared, as the FPGAimplementation could not be preformed because of technical difficulties. Theresults are good comparison to related work, but did not improve much uponthem. This because the hardware used is quite weak compared to industry standard. Though further research on the topic would be interesting, to compare aworking FPGA implementation to the other results and results from other studies. This implementation also probably has the biggest improvement potential,so to see how good one could make it would be interesting. Also, testing someother more complex benchmarks could be interesting.

Sales forecasting is an important aspect of business strategy, as it helps companies make informed decisions for their business development. With the rise of machine learning and AI, companies are using statistical and machine learning models to forecast short-term and long-term sales more accurately. In addition, it is important for companies to be able to estimate the impact of advertising on sales for different markets in order to optimize ad campaigns and make informed decisions about their advertising strategies. To address the former problem, ARIMA and LightGBM models with and without feature selection using Lasso regression are used to forecast revenue of an airline across different markets. The performance of the models is measured using Mean Absolute Error (MAE) and Symmetric Mean Absolute Percentage Error (sMAPE) metrics and both of them are compared to a simpler naïve approach called baseline. As for the impact of advertising, CausalImpact package is used to estimate the effect of non-advertising on revenue for each market for a specific period.

LightGBM models without feature selection performed better in terms of error metrics for the majority of markets with improvements ranging between 41%-77% for sMAPE score and 30%-81% for MAE score when compared with baseline approach. While feature selection aided some markets in achieving lower error scores, it did not consistently improve performance across all markets. As for the effect of non-advertising on revenue, the analysis could not show a negative effect on revenues in all markets. It is difficult to say whether the effect was solely positive or negative for every market, because the results were not statistically significant for most markets, except one.

Using sensors to observe real-world systems is important in many applications. A typical use case is target tracking, where sensor measurements are used to compute estimates of targets. Two of the main purposes of the estimates are to enhance situational awareness and facilitate decision-making. Hence, the estimation quality is crucial. By utilizing multiple sensors, the estimation quality can be further improved. Here, the focus is on target tracking in decentralized sensor networks, where multiple agents estimate a common set of targets. In a decentralized context, measurements undergo local preprocessing at the agent level, resulting in local estimates. These estimates are subsequently shared among the agents for estimate fusion. Sharing information leads to correlations between estimates, which in decentralized sensor networks are often unknown. In addition, there are situations where the communication capacity is constrained, such that the shared information needs to be reduced. This thesis addresses two aspects of decentralized target tracking: (i) fusion of estimates with unknown correlations; and (ii) handling of constrained communication resources. 

Decentralized sensor networks have unknown correlations because it is typically impossible to keep track of dependencies between estimates. A common approach in this case is to use conservative estimators, which can ensure that the true uncertainty of an estimate is not underestimated. This class of estimators is pursued here. A significant part of the thesis is dedicated to the widely-used conservative method known as covariance intersection (CI), while also describing and deriving alternative methods for CI. One major result related to aspect (i) is the conservative linear unbiased estimator (CLUE), which is proposed as a general framework for optimal conservative estimation. It is shown that several existing methods, including CI, are optimal CLUEs under different conditions. 

A decentralized sensor network allows for less data to be communicated compared to its centralized counterpart. Yet, there are still situations where the communication load needs to be further reduced. The communication load is mostly driven by the covariance matrices since, in this scope, estimates and covariance matrices are shared. One way to reduce the communication load is to only exchange parts of the covariance matrix. To this end, several methods are proposed that preserve conservativeness. Significant results related to aspect (ii) include several algorithms for transforming exchanged estimates into a lower-dimensional subspace. Each algorithm corresponds to a certain estimation method, and for some of the algorithms, optimality is guaranteed. Moreover, a framework is developed to enable the use of the proposed dimension-reduction techniques when only local information is available at an agent. Finally, an optimization strategy is proposed to compute dimension-reduced estimates while maintaining data association quality. 

Cauchy problems for elliptic equations arise in applications in science and engineering. These problems often involve finding important information about an elliptical system from indirect or incomplete measurements. Cauchy problems for elliptic equations are known to be disadvantaged in the sense that a small pertubation in the input can result in a large error in the output. Regularization methods are usually required in order to be able to find stable solutions. In this thesis we study the Cauchy problem for elliptic equations in both bounded and unbounded domains using iterative regularization methods. In Paper I and II, we focus on an iterative regularization technique which involves solving a sequence of mixed boundary value well-posed problems for the same elliptic equation. The original version of the alternating iterative technique is based on iterations alternating between Dirichlet-Neumann and Neumann-Dirichlet boundary value problems. This iterative method is known to possibly work for Helmholtz equation. Instead we study a modified version based on alternating between Dirichlet-Robin and Robin-Dirichlet boundary value problems. First, we study the Cauchy problem for general elliptic equations of second order with variable coefficients in a limited domain. Then we extend to the case of unbounded domains for the Cauchy problem for Helmholtz equation. For the Cauchy problem, in the case of general elliptic equations, we show that the iterative method, based on Dirichlet-Robin, is convergent provided that parameters in the Robin condition are chosen appropriately. In the case of an unbounded domain, we derive necessary, and sufficient, conditions for convergence of the Robin-Dirichlet iterations based on an analysis of the spectrum of the Laplacian operator, with boundary conditions of Dirichlet and Robin types.

In the numerical tests, we investigate the precise behaviour of the Dirichlet-Robin iterations, for different values of the wave number in the Helmholtz equation, and the results show that the convergence rate depends on the choice of the Robin parameter in the Robin condition. In the case of unbounded domain, the numerical experiments show that an appropriate truncation of the domain and an appropriate choice of Robin parameter in the Robin condition lead to convergence of the Robin-Dirichlet iterations.

In the presence of noise, additional regularization techniques have to implemented for the alternating iterative procedure to converge. Therefore, in Paper III and IV we focus on iterative regularization methods for solving the Cauchy problem for the Helmholtz equation in a semi-infinite strip, assuming that the data contains measurement noise. In addition, we also reconstruct a radiation condition at infinity from the given Cauchy data. For the reconstruction of the radiation condition, we solve a well-posed problem for the Helmholtz equation in a semi-infinite strip. The remaining solution is obtained by solving an ill-posed problem. In Paper III, we consider the ordinary Helmholtz equation and use seperation of variables to analyze the problem. We show that the radiation condition is described by a non-linear well-posed problem that provides a stable oscillatory solution to the Cauchy problem. Furthermore, we show that the ill–posed problem can be regularized using the Landweber’s iterative method and the discrepancy principle. Numerical tests shows that the approach works well.

Paper IV is an extension of the theory from Paper III to the case of variable coefficients. Theoretical analysis of this Cauchy problem shows that, with suitable bounds on the coefficients, can iterative regularization methods be used to stabilize the ill-posed Cauchy problem.

Battery electric trucks (BETs) offer environmental benefits in terms of reduced carbon emissions and enhanced energy efficiency but have been challenged with economic viability compared to conventional internal combustion engine trucks (ICETs) caused by substantial acquisition costs, limited charging infrastructure, and concerns regarding range and payload capacity. 

Previous studies focus on TCO at the vehicle or policy level but overlook the system and firm-level impacts. Operational aspects like vehicle utilization, battery utilization, charging planning, and route optimization are often ignored, potentially underestimating electric freight cost-competitiveness.The research gap does not address the practical needs of fleet operators, especially in scenarios where charging infrastructure is lacking. There is therefore a need to consider the complex system level interactions, market dynamics, technology developments, and operational processes involved in freight shipping.

By applying a decision-making under deep uncertainty (DMDU) framework, this study enables informed decisions in unpredictable scenarios, bridging the gap between strategic choices like battery capacity and operational optimization like route planning. This study identifies the most significant factors that affect the TCO of BET fleets and cost-competitiveness relative to ICET fleets, taking into account market-operational interfaces between unpredictable market dynamics and operational processes such as stochastic demand and feature selection from a strategic and operational perspective. 40 tonne truck-trailers for freight distribution networks with distances up to 250 km are considered in the study. 

A TCO model of BET and ICET fleets was developed taking into account vehicle route optimization, vehicle selection, and vehicle utilization which was then programmatically iterated by sampling and simulating optimized vehicle routes for a total of 220 224 iterations. The parameter space was screened and reduced with Feature Scoring using Extra Trees approximation of 1st order Sobol Indices. The reduced parameter space was then sampled using Sobol sampling to conduct a Sobol Global Variance decomposition Analysis of TCO, TCO delta, and service level in order to identify the most significant factors affecting BET fleet TCO and cost-competitiveness.To identify cost-competitive scenarios, the Patient Rule Induction Method (PRIM) was used to identify parameter sub spaces to determine scenarios where BET fleets have a lower TCO than ICET fleets. Further visual analysis was done using linear and polynomial regression and kernel density estimation.

The analysis shows that both TCO and cost-competitiveness of BETs are primarily affected by shipment demand, distance between distribution center and delivery sites, and battery size, and that a trade-off is made between cost-competitiveness and service level. The results show that cost-competitiveness of electric freight scales with demand, with larger fleets being better able to optimize routing and shipment allocation; balancing the shipment demand to minimize charging times that otherwise would make the fleet less competitive than their fossil-fuel counterparts. This, paired together with higher degrees of vehicle utilization and appropriate battery sizing, allow for electric freight to be cost-competitive even for long-haul distances up to 250 km. 

Furthermore, optimization of the Electric Vehicle Routing Problem (E-VRP) with shifts and time windows is shown to have a highly significant effect when minimizing TCO on a fleet level, with the vast majority of optimal ICET routes not being optimal for BETs.The benefits of E-VRP optimization scales with demand and fleet size, indicating that large-scale electrification is required to make BETs cost-competitive.Electrification of road freight is therefore highly contingent on effective route planning and charging scheduling with E-VRP optimization in order to be cost-competitive, which has not been considered in previous literature. Thus previous literature have therefore likely underestimated the cost-competitiveness of electric freight, particularly at medium-long haul distances. 

Water pollution has long been considered a challenge in urban areas. Urban wastewater and stormwater act as transport pathways for pollutants from urban areas to receiving waters. Microplastics are a pollution problem of growing concern. As part of the zero-pollution action plan for 2050, the European Commission has set the target to reduce emissions of microplastics to the environment by 30% from 2016 to 2030. The majority of the microplastics originate from sources on land, and urban areas are viewed as particular hotspots. More knowledge is needed on the sources and pathways of microplastics within the urban area, such as to and from urban water systems. To be able to reduce microplastics pollution, there is also a need to understand where control measures can be introduced and make an impact in terms of reduced loads to the environment. For control measures to be implemented, there is also a need to understand the incentives and challenges that the actors, who have a responsibility related to the flows, encounter when working with pollution control.   

The aim of this thesis was to contribute to enhanced understanding of flows of microplastics in urban water systems and how the flows can be controlled, in order to facilitate mitigation actions for these flows. This aim was addressed by identifying and quantifying sources with emissions to urban wastewater and stormwater and pathways from the urban water system, with inspiration from the method substance flow analysis. The estimated sources were also compared to measurements in raw wastewater and stormwater from four different catchments to identify matches and differences. Further, control measures were introduced to the quantified sources and pathways. Municipal officials, who can implement the control measures, were also interviewed about their incentives and challenges when controlling microplastics and other pollutants in the urban water system.   

The emissions of microplastics to stormwater were estimated to be much higher than those to wastewater. Tyre wear particles and cigarette butts were estimated to be the largest sources. While stormwater measurements confirmed tyre wear particles, cigarette butts, and paint particles, which was another large source according to the source estimates, could not be confirmed. Instead, the samples contained other types of microplastics. These mismatches indicate that large flows of microplastics may come from sources that have yet to be identified and quantified. The largest source to wastewater was estimated to be synthetic fibres (mainly polyester) released during laundry washing. Polyester also had the largest share in the wastewater measurements. Untreated stormwater was the largest pathway to receiving waters, followed by treated stormwater. Treated wastewater and overflows had comparatively small emissions. The measures introduced to wastewater had the potential to reduce the load of microplastics in the wastewater by half. However, as wastewater treatment retain most of the microplastics, and because the largest emissions came from stormwater, this reduction made a small difference in terms of total loads to receiving waters. Reduced urban traffic, changed driving behaviour, and more stormwater treatment, were also required to reduce emissions of microplastics from the urban water system to receiving waters by 30% in accordance with the EU target.   

Three types of incentives for pollution control among the municipal officials were identified. One incentive was that pollution control positively affected other aspects that were seen as important, such as that it had economic benefits or increased water- and sludge quality. Another incentive was a perceived responsibility for water quality, for the environment, or to be role models. A third incentive was a “pressure” to act from the local environmental control authorities or through local politics. The challenges for pollution control were primarily related to insufficient resources in terms of time, finances, and knowledge. Changing, limited, or lack of legislation was also identified as a challenge. Other identified challenges, such as unclear responsibilities and unclear expectations of the work, can be alleviated with a strategy or plan, but a plan did not ease all challenges. Support, in terms of financial means and guidance, is also needed so that actions set out in the plans can be implemented.  

So far, the control measures for microplastics related to urban water systems have primarily been preventive and focused on restricting use of microplastics in certain applications. There are no restrictions on emissions yet. If such restrictions come, where they are placed will impact the type of measures that will be introduced. This, in turn, will have consequences at the system level: for example, if it will lead to emissions in another part of the system, and which actors will be responsible for managing the pollution. 

Syftet med den här studien är att bidra med kunskap om hur bildstöd används både i förskolan inne- och utemiljö. Utifrån två frågeställningar vill vi ta reda på hur bildstöd används i de olika miljöerna, samt hur det skiljer sig åt. Vi har genomfört en studie med både kvantitativ- och kvalitativ metod, genom observationer och intervjuer, för att kunna ge ett bredare perspektiv på vår studie. Genom observationerna fick vi ett sammanställt resultat med antal för bildstödets användande, medan intervjuerna gav oss en mer djupgående bild för hur verksamheterna arbetar med bildstöd. Utifrån våra frågeställningar samt vårt insamlade material skapade vi sex stycken teman för att kunna genomföra en grundlig analys. Resultatet genom observationerna visar att det finns tydliga skillnader mellan inne- och utemiljöer, vilket också intervjuerna bekräftade. Genom citat från intervjuerna har analys och tolkning gjorts för att kunna få ökad förståelse för varför bildstöd inte finns i lika stor mängd utomhus. Slutligen diskuterar vi resultatet för att sammanställa studiens slutsatser och genom dessa besvara frågeställningarna.

Chronic pain and emotional problems are common, often co-occur, and result in substantial suffering and social costs. Cognitive Behavioral Therapy (CBT) is a family of treatments that have been extensively studied and has empirical support for its effectiveness in treating both conditions. However, CBT show small benefits for patients with comorbid pain and emotional disorders, and treatments are mostly adapted for one condition or the other. Hence, there is a need for transdiagnostic interventions, targeting both problematic pain behaviors and emotional components. In this thesis, I present results from three experimental studies investigating possibilities to refine and enhance CBT for chronic pain patients with emotional distress by using emotion regulation strategies and skills training from mindfulness-based interventions.

In Study I the aim was to evaluate the efficacy of a tailored transdiagnostic hybrid treatment, integrating basic CBT principles with strategies from Dialectical Behavior Therapy (DBT), an acceptance and mindfulnessbased approach developed for individuals with difficulties regulating emotional responses. The hybrid treatment was compared in a randomised controlled trial to an internet-delivered active control condition (iCBT). Intent-to-treat analyses showed that the hybrid treatment had positive long-term effects 9 months after treatment on outcomes such as pain interference and symptoms of depression compared to the control condition. We concluded that the hybrid treatment may be considered an acceptable, credible, and efficacious treatment approach.

In Study II the aim was to investigate the importance of hypothesized treatment processes of the hybrid treatment, specifically pain-related dysregulation (catastrophizing, fear-avoidance, and non-acceptance of pain), and general emotion dysregulation (difficulties to regulate a wider range of emotional responses). Mediation analysis within the framework of structural equation modelling (SEM), using the full intention-to-treat sample, showed that decreased pain-related dysregulation mediated the effects of the hybrid treatment on both pain interference and symptoms of depression. Furthermore, indirect effects through pain-related dysregulation were more evident for participants scoring higher on this variable at baseline. In addition, decreased general emotion dysregulation mediated effects on symptoms of depression. We concluded that these findings provided further support for the conceptual principles of the hybrid treatment.

The aim of Study III was to investigate the effects of components of mindfulness-based interventions, specifically looking at the importance of attentional focus during mindfulness exercises on experiences of experimentally induced pain using the Cold Pressor Test (CPT). In a mixed experimental design, healthy participants were randomly assigned to brief mindfulness exercises with internal focus (body scan), external focus (mindful listening), or a control group using spontaneous coping. Compared to spontaneous coping the mindfulness exercises had positive effects on pain tolerance, pain threshold, pain unpleasantness, frequency of negative thoughts, and belief in thought content during the CPT. While our results showed that changes in attentional focus were consistent with the experimental manipulation, no significant differences were found between internal and external focus on any outcome measure. We concluded that the results did not support the notion that attentional focus would be essential for benefits of mindfulness, and that exercises with both external and internal focus could be beneficial when coping with pain.

In conclusion, the results from these studies support integrating basic CBT principles with emotion regulation strategies and skills training from mindfulness-based approaches to enhance treatments for patients with chronic pain and emotional distress. In addition, our findings provide some insights for future research regarding the importance of targeting pain-related dysregulation, and the possibilities of using mindfulness exercises with different attentional focus.

The sustainability goals of the modern world and the fascinating properties of sub-micron scale materials promote development of materials in thin film form. Thin films are materials that have thicknesses ranging from sub-nanometer to several micrometers, synthesized by various deposition techniques. They are used for diverse applications, such as light emitting diodes, solar cells, semiconductor chips, etc. The primary objective of this research project is to develop a chemical vapor deposition (CVD) process for conformal boron carbide thin films. Since boron carbide is a promising neutron converter material for solid-state neutron detectors, the process was validated by depositing on prototype detector chips.  

In this study, triethylboron (TEB) was used as single source CVD precursor to deposit boron carbide thin films. The initial experiments focused on low reaction rate deposition by depositing in a kinetically limited regime. The films deposited at ≤450 °C in 8:1 aspect ratio micro-trench structures were highly conformal and show a stoichiometry of about B5.2C. We attribute this observed conformality to the slow reaction kinetics of the TEB at the low deposition temperature enabling the diffusive transport of the precursor molecule down the trench. The depositions carried out on the prototype detector-chips show promising results.  

We expand our studies to investigate a new strategy with the prospect of improving the step coverage at higher temperatures for better film properties. We hypothesize that adding a suitable heavier molecule, diffusion additive, with an appropriate partial pressure can enhance the step coverage by pushing the lighter precursor molecule via competitive co-diffusion. It was tested by adding Xe gas to the boron carbide CVD from TEB. The result shows that with this diffusion additive the step coverage was improved from 0.71 to 0.97. From our experimental results, we suggest a competitive diffusion model that can be adapted to other CVD processes to enhance the film step coverage.  

The CVD process is further validated by depositing onto carbon nanotube membranes. The initial results show that the process was able to afford evenly deposition around the individual nanotubes in the carbon nanotube membrane. Raman spectroscopy measurements show a similar D-band to G-band intensity ratio before and after the deposition indicating that no defects were induced in the nanotubes.