Spatial transcriptomics (ST) revolutionized the study of gene expression within tissue sections, yet its application to clinically relevant material has remained limited by technical constraints related to sample characteristics and RNA quality. This thesis advances the use of spatial transcriptomics by establishing frameworks for profiling archival clinical specimens, ensuring tissue quality prior to ST, and combining spatial data and other complementary modalities to reveal the cellular, molecular and immune-clonal architecture of human cancer.

In Article I, we developed a method that adapted genome-wide spatial transcriptomics to formalinfixed paraffin embedded (FFPE) samples, which constitute the vast majority of clinical specimens, unlocking their potential. The workflow was validated on mouse brain tissue, showing high correlation with matched fresh-frozen data, and then applied on other various tissues to show its robustness across sample types. This development expanded spatial transcriptomics to previously inaccessible FFPE material. We also developed a TSO-based QC assay to assess spatial RNA accessibility directly in FFPE tissue sections, minimizing the risk of failed or biased spatial transcriptomics analysis.

In Article II, we developed an assay that enables evaluation of RNA integrity directly within tissue sections, the spatial RNA integrity number (sRIN) assay. Traditional RIN values are obtained from bulk tissue and therefore cannot reveal local variability in RNA quality. sRIN was developed as a practical quality-control step allowing users to identify well-preserved versus degraded regions before committing to costly downstream experiments.

In Article III, we analyzed genomic and clinical data from phase III melanoma trials and used NMF to define seven melanoma subtypes reflecting distinct differentiation states. By integrating bulk, single-cell, and spatial transcriptomics, we showed that these states coexist within tumors. Our analyses revealed that only differentiated melanoma becomes sensitized to immune checkpoint blockade therapy when combined with BRAF/MEK inhibition through enhanced antigen presentation, whereas undifferentiated states remain resistant, colocalize with CAF-rich niches, and could potentially be targeted by CDK7 inhibitors.

In Article IV, we combined single-cell RNA-seq, spatial transcriptomics and spatial V(D)J profiling to characterize the spatial and clonal organization of the immune landscape of sinonasal squamous cell carcinoma (SNSCC). Although immune infiltration was extensive, T- and B- cell clones were found preferentially within antigen presenting cell -rich stromal and peritumoral niches rather than undifferentiated tumor areas. We identified diverse CD8+ T-cell activation states that followed a bifurcated differentiation trajectory, and we also found an unusually large population of FOXP3+ regulatory T cells (Tregs), many expressing CXCR3 and TBX21 (T-bet). Integration of spatial gene expression with sV(D)J associated immune diversification and clonal expansion with CAF-associated matrix remodeling programs and interferon-activated antigen presenting cell programs. CXCL9+/CXCL10+ macrophages were found as drivers of lymphocyte recruitment and IDO1+ regulatory dendritic cells as immunosuppressive within the same niches.

Digital transformation has in recent years become a central feature of the development of the Architecture, Engineering, Construction, and Operations (AECO) industry. In large public client organizations, digitalization is often pursued through the introduction of digital work systems, such as Building Information Modeling (BIM), with the aim of improving coordination, information quality, and decision-making across long asset life cycles. At the same time, previous research shows that digital work systems are frequently used in fragmented ways and in parallel with established work practices, which limits their potential to support integrated and sustainable ways of working. These challenges have to a limited extent been analyzed from a coherent sociotechnical perspective, particularly in public infrastructure contexts characterized by formal governance, complex project- and line-based organizational structures, and long-term responsibility for critical societal infrastructure. Against this background, the aim of this thesis was to deepen the understanding of digital transformation in the AECO sector from a sociotechnical perspective by identifying which human, technological, organizational, and leadership-related factors, as well as the interactions between them, are associated with professionals’ attitudes toward, trust in, and use of digital work systems in practice. The thesis places particular emphasis on the role of leadership in shaping organizational conditions for digital work and in translating strategic digital ambitions into operational working conditions. The thesis is based on four constituent studies applying a mixed methods approach. An initial scoping review mapped prior research on interactions between humans, technology, and organization in the use of BIM. Two quantitative questionnaire survey studies examined associations between individual, social, and organizational factors, leadership-related aspects, and attitudes toward and trustful use of digital work systems in a large public client organization within the AECO industry. Finally, a qualitative interview study with managers at different organizational levels was conducted and analyzed using a grounded theory approach, to explore how conditions, opportunities, and constraints for digitally oriented leadership were perceived and managed in practice. The results showed that attitudes toward and trust in digital work systems are not solely related to technical system characteristics but are shaped through the interplay between technical and organizational conditions, social relations, and leadership practices. The quantitative analyses demonstrated that organizational and social conditions, including leadership quality and clarity, were associated with how digital work systems are perceived and used. The qualitative findings indicated that leaders often operate within narrow organizational constraints, where formal governance structures, unclear mandates, and fragmented processes limit opportunities to support integrated use of digital work systems across organizational levels and project phases. Overall, the thesis demonstrates that digital transformation in large and complex public AECO organizations should be understood as a sociotechnical process in which leadership constitutes a central mechanism for coordination, sensemaking, and the legitimation of digital work. The thesis contributes theoretically by further developing sociotechnical perspectives on digital transformation through empirical analysis of how leadership interacts with human, technological, and organizational factors. Empirically, the study contributes to in-depth knowledge of conditions for digital work in a public infrastructure context. Practically, the findings provide guidance on how governance, organizational design, and leadership practices may be developed to support more integrated, trustful, and sustainable use of digital work systems.

Organic electrosynthesis uses electricity as the “reagent” to drive redox reactionsinstead of relying on more traditional oxidants or reductants. Because electronsare supplied directly from an electrode, reactions can often be run underrelatively mild conditions and with less chemical waste. In this thesis,electrochemical methods are developed to target carbon-sulfur (C-S) bonds incommon sulfur-containing compounds of thioethers, thioacetals, disulfides, andthiols, and, in an analogous way, carbon-oxygen (C-O) bonds in esters.A major part of the work shows how aryl-alkyl thioethers can act as an alkylsource under electroreductive conditions. When electrolyzed the C(sp³)-S bondis cleaved selectively to form carbon centered radical, which can cross over to acarbanion. These intermediates can be converted into alkanes, or react withcarbon dioxide to form carboxylic acids, or add to electron-poor alkenes in aGiese-type reaction. Using the same activation concept, the thesis alsointroduces an electrochemical route to valuable alkylboronic esters by couplingthe carbanion with a boron reagent. Notably, this borylation strategy worksacross several classes of sulfur-containing motifs.Beyond developing new reactions, the thesis also addresses a practical challengein electrosynthesis. Many net-reductive electrochemical methods still rely onsacrificial metal anodes that are consumed during the reaction. Here,borohydride oxidation with inert anodes is evaluated as an alternative counterreaction across several net-reductive protocols, steering toward a moreoperationally convenient electrolysis setup.Finally, the thesis explores the electrochemical deoxygenation Markó-Lamreaction of esters using a computational approach. By mapping how variousdescriptors influence the C-O bond breaking step, the study connectsmeasurable properties such as reduction potentials with reaction barriers.

The transition toward high-efficiency electrified systems has accelerated the adoption of SiC MOSFET devices, whose performance benefits are often limited by package-related reliability challenges. This thesis investigates these challenges through two complementary research directions. The first focuses on the thermo-mechanical reliability of conventional, single-sided cooled (SSC), and double-sided cooled (DSC) SiC MOSFET packaging structures using finite-element modeling (FEM) in COMSOL Multiphysics. The impact of die placement, advanced interconnection technologies, solder and Ag-sinter materials, and Cu–Mo composite spacers is analyzed to understand temperature distribution, viscoplastic strain accumulation, and solder-layer lifetime under various power-cycling conditions. The results highlight important design trade-offs and identify advanced packaging configurations and materials that improve both thermal and mechanical performance.

The second part of this thesis develops experimental health-diagnostic methods using degradation data obtained from the power-cycling test (PCT) setup. Commercially available TO-247-3 packaged SiC MOSFET devices were degraded using inverse-mode and forward-mode PCTs, enabling a detailed investigation of body-diode forward-voltage reduction, package-related degradation, and ON-state resistance (R_dsON) drift in SiC MOSFETs. A compensated R_dsON-based diagnostic method is introduced and experimentally validated for the reliable detection of package-related degradation. Additionally, a diagnostic technique for early bond wire failure detection is proposed and experimentally validated.

Advances in miniaturized biomedical microsystems, ranging from in vitro microphysiological systems (MPS) to implantable devices, are enabling new modes of continuous, autonomous preclinical studies. This thesis presents a set of interconnected research contributions on millimeter-scale fluorescence-sensing and ultrasonic energy-harvesting microsystems, collectively advancing the development of integrated and miniaturized biomedical instrumentation.

The first part introduces an integrated microoptical system for fluorescence sensing in MPS, incorporating custom micro-optics and miniaturized excitation and detection units with tailored optical filters. This platform enables real-time, continuous fluorescence monitoring of microtissues under physiologically relevant conditions, strengthening the analytical capabilities of MPS for long-duration studies of drug delivery and cellular behavior.

The second part translates these sensing concepts to fully implantable microsystems capable of autonomous, long-term in vivo fluorescence recording. A compact 5 × 5 × 5 mm³ implant integrates a miniaturized optical module and low-power electronics to track fluorescence dynamics within living tissue. Validated across phantom, in vitro, ex vivo, and in vivo studies, the system demonstrates two-week continuous tracking of tumor-associated fluorescence, establishing its suitability for preclinical studies.

The final part focuses on ultrasonic energy harvesting to enable the autonomous operation of implantable devices. A MEMS-based piezoelectric ultrasonic energy harvester (PUEH) fabricated using a low-temperature bonding process allows integration of high-performance bulk PZT-5H, demonstrating the potential of MEMS architectures for efficient ultrasonic power transfer. An integrated energy-harvesting node, also in a 5 × 5 × 5 mm³ form factor, combines the MEMS-based PUEH with power management and storage to support autonomous operation of millimetric implants.

Together, these contributions advance miniaturized fluorescence sensing and ultrasonic energy transfer, enabling versatile microsystems for biomedical applications.

In this thesis, we address control problems arising in constrained dynamical systems and in systems subject to high-level control tasks. Our primary focus is on the efficient control synthesis for systems with time-varying constraints. We further extend the insights developed in this setting to systems subject to spatio-temporal logic constraints, a class of high-level control specifications, as well as to coordination problems in distributed systems.

In the first part of the thesis, we develop a systematic framework for synthesizing time-varying Control Barrier Functions (CBFs). While CBFs are a well-established tool for ensuring forward invariance, their design becomes challenging for time-varying constraints as their variations are, upon controller design, commonly not or only qualitatively known, e.g., in terms of their maximum rate of change. We address this challenge by decoupling the CBF synthesis into the design of a time-invariant value function and a time-varying transformation that captures constraint variations by uniformly shifting the CBF. This approach relies on a particular type of CBF, which we term shiftable CBF. It encodes the system’s dynamic capabilities with respect to a constraint, including its ability to react to constraint changes. As a result, the time-varying component can be adapted online without recomputing the CBF.We further introduce a predictive synthesis method for computing shiftable CBFs that allows the required time-varying capabilities to be specified explicitly as a design parameter. Moreover, to mitigate the computational cost of the CBF synthesis, we exploit equivariances in the system dynamics, showing how these can be leveraged to a simplified CBF computation and the construction of new CBFs from existing ones. Finally, we extend the decoupled design to more general time-varying transformations beyond uniform shifts using equivariance properties. Throughout this part, we employ nonsmooth CBFs defined in the Dini sense, which are less conservative than formulations based on generalized gradients and are well-suited for handling time-varying and logic-based constraints.

In the second part, we build upon the notion of nonsmooth CBFs in the Dini sense and leverage them to address high-level control tasks expressed through spatio-temporal logic specifications. We explicitly allow for disjunctions (logic or) in the specifications, which cannot be accommodated by smooth CBFs without resorting to high-order controller design methods. Moreover, we propose a systematic approach to evaluating nonsmooth CBFs in the Dini sense, avoiding the need for numerical approximations of directional derivatives.In the third part of the thesis, we shift our focus to a distributed setting and investigate state-coupled CBFs for coordination within a case study on vehicle coordination.

In the last part of the thesis, we depart from CBFs and present a parallelized distributed model predictive control (DMPC) scheme for systems subject to coupled state constraints. To guarantee constraint satisfaction even during the parallelized evaluation of the local optimal control problems, we introduce consistency constraints ensuring that the state trajectories remain within a neighborhood of a reference trajectory, both of which are known to neighboring subsystems. Thereby, the behavior of every subsystem remains predictable to its neighbors. Unlike existing approaches, we allow the reference trajectories to be updated at every time step. This design yields significantly lower computation times than sequential DMPC, while outperforming DMPC approaches based on fixed reference trajectories.

Elastoviscoplastic (EVP) fluids are ubiquitous in nature and engineering, appearing in biological systems such as blood flow and the cell cytoskeleton, as well as in geophysical phenomena like avalanches and mudslides. They also play a central role in applications ranging from the transport of waxy crude oil to additive manufacturing and drug delivery in the human body. A defining characteristic of these materials is the presence of a critical yield stress, below which the material behaves as a viscoelastic solid and above which it flows like a liquid. Many EVP fluids also contain additional phases, such as rigid particles, whose interactions significantly influence the flow dynamics. Predicting these flows requires understanding how the non-Newtonian properties of the carrier fluid influence particle distribution, how particles modify the surrounding flow field, and how particle–fluid interactions determine the overall behaviour of the suspension. The aim of this work is therefore to advance the physical understanding of multiphase flow dynamics by developing and employing high-fidelity numerical simulations to study the individual and collective behaviour of finite-size particles in EVP carrier fluids.

The results demonstrate the strong influence of particle shape and fluid rheology on suspension behaviour. For instance, EVP suspensions can exhibit significant drag reduction compared with Newtonian suspensions of the same viscosity. Particles are also shown to migrate across streamlines in ways that depend on both their shape and the non-Newtonian properties of the fluid. The simulations of EVP suspensions are validated against available experimental measurements of finite-size spherical particles in Carbopol duct flows. Additional simulations of droplet-laden EVP turbulent flows reveal that elasticity and yield stress of the carrier fluid strongly influence morphology, size, and spatial distribution of the dispersed droplets. Moreover, numerical simulations and microfluidics experiments show that adjusting channel geometry and fluid elasticity can achieve precise particle focusing at the centre of microchannels. Finally, an efficient immersed boundary method is developed to model viscoelastic flow around static boundaries, improving the accuracy of stress computations near the solid boundaries. 

Hierarchical porous materials yield versatile functionalities by combining pores across multiple length scales, whereas their controlled bottom-up synthesis remains a challenge. This thesis presents a biomimetic strategy to fabricate hierarchical porous metal and mineral composites by utilizing and exploring the naturally developed hierarchical structure of wood. Direct use of wood as template is also environmentally and economically friendly due to its renewable source, low cost, and scalable processability. 

A sequential methodology was developed, beginning with cell wall engineering to overcome the limited accessibility and mass diffusion of bulk wood. This was first achieved by programmed removal of cell wall components. Reassembly of intrinsic biopolymers into lumina fibril networks was then investigated to create wood aerogels with high specific surface area. The engineered wood scaffolds were subsequently functionalized via metallization or mineralization. Electroless Cu plating produced compressible, electrically conductive templates, while MTMS condensation imparted hydrophobicity. ZnCl2 was also explored to simultaneously fabricate wood aerogels and precipitate ZnO in situ. The resulting composites combined the structural advantages of engineered wood scaffold (large surface area, aligned channels, mechanical robustness) with the functionality of guest materials. This synergy enables applications in pressure sensors, thermal insulation in energy-efficient buildings, and photocatalytic dye degradation. This work established a versatile and sustainable platform for transforming renewable resources into high-performance functional composites. 

Our inhabitable world is heavily threatened by multiple ecological crises that are directly related to humanity’s use of resources and our fossil-fuelled energy systems. Transitioning to a system powered by renewable energy will also have social and political consequences. Sweden is a relevant context for studying these dimensions, as a nation with ambitious sustainability targets and a steady supply of hydro, nuclear, bio-energy and wind, while also supporting end-consumers through warm-rent apartments, district heating and smart meters. 

The residential sector accounts for a significant amount of global energy consumption and associated emissions. Households are also highly affected by technologies such as smart meters, expectations of flexible energy use, and rising energy costs. This thesis studies the roles of households in the future Swedish electricity grid. This involves exploring policy and industry expectations of households, how these expectations relate to households’ everyday lives, and how understandings of household roles can be renegotiated to be more just and inclusive. The empirical material was gathered within two research projects studying the roll-out of new smart meters in Swedish households and the development of a Swedish energy community. The material was mainly collected through a literature review of policy documents and interview studies with industry, households and energy community stakeholders. 

This thesis consists of a cover essay and four appended papers. Paper A critically analyses policy expectations on households to contribute to demand flexibility in the future smart grid. Expectations of policy and stakeholders on households are also examined in papers B, C and D. In papers B and C, stakeholder expectations are contrasted with household everyday lives and experiences of the smart meter roll-out. Paper D focuses on the framing and prefiguration of an energy community, and its proposed roles for households. Papers B, C and D aim to suggest how the roles of households can be renegotiated to be more inclusive and just. 

This thesis contributes by illustrating how Swedish policy and industry envision households as active and motivated actors in the smart grid. Narratives of desired energy futures describe aware and active customers on the one hand, and a willingness to automate consumption on the other. Households are expected to prioritise comfort, convenience and simplicity. Similar expectations exist in an energy community setting, where households are portrayed as consumers and shareholders, not to be disturbed. 

Household everyday life is incompatible with these visions, as the concept and importance of demand flexibility is unfamiliar to households. Second, households show scepticism towards using smart technology that potentially affects their everyday routines or gathers sensitive data. The energy community is primarily framed as an energy efficiency project and as a grid alleviator, prioritising financial benefits. These gaps and mismatches have several implications to be addressed for a just transition. First, a diversity within and between households needs to be acknowledged. Second, demand flexibility implemented through demand tariffs and automation risks excluding and punishing those with less capacity to be flexible. While energy communities are suggested as a way of decentralising power, our findings illustrate how such structures are governed by a small group of energy experts, echoing the centralised view of the system and households in it. This raises questions about what values drive the energy transition, which households are recognised, how they are invited to participate in the energy transition and how burdens and benefits can be distributed more justly.

Sepsis is a life-threatening condition affecting an estimated 49 million people annually and causing approximately 20% of the deaths worldwide. Survival in septic shock decreases by about 8% per hour of delayed or inappropriate treatment, making rapid diagnosis critical. Consequently, patient outcomes strongly depend on the rapid initiation of appropriate antimicrobial therapy, making sepsis diagnosis a fight against time. However, current blood culture-based workflows typically require several days to deliver actionable results, largely due to the extremely low bacterial concentrations in blood (1-100 CFU/mL) that necessitate time-consuming culture steps. There is therefore a pressing need for diagnostic protocols capable of rapidly isolating and characterizing bacteria directly from blood.

In this work, we address a key limitation in current diagnostic pipelines by developing and evaluating culture-free approaches for the rapid isolation, detection, species identification, and antimicrobial susceptibility testing (AST) of bacteria directly from blood, starting at clinically relevant concentrations. Two centrifugation-based sample preparation strategies were developed: one compatible with samples drawn into blood culture bottles and one designed for whole blood. Using the first approach, we demonstrated the isolation and identification of five common sepsis-causing bacteria within 12 hours. This approach relies solely on standard laboratory equipment, which facilitates direct translation to clinical laboratories. The whole-blood approach combines centrifugation and selective blood cell lysis with microfluidic trapping and deep learning-based automated detection, and enables culture-free detection of bacteria from blood within 2 h. Building on this foundation, the workflow was further extended to integrate real-time automated detection, single-cell phenotypic AST, and species identification by fluorescence in situ hybridization (FISH), directly from uncultured blood in under 7 h. 

The sample preparation steps of these protocols rely heavily on manual processing. Therefore, subsequent work focused on the development of a one-step centrifuge device that automates bacterial isolation and up-concentration while maintaining compatibility with downstream processes, such as subculturing, mass spectrometry-based identification, and microfluidic single-cell analysis. All approaches were evaluated using healthy human blood samples spiked with common sepsis-causing bacteria, and serve as proof-of-concept of rapid, culture-free bacterial characterization directly from blood.

Together, the results presented in this thesis demonstrate the potential of combining centrifugation-based sample preparation, microfluidics, and automated image analysis to substantially shorten diagnostic turnaround times for sepsis and bloodstream infections. Although further validation with clinical samples and increased automation are required, this work provides experimental and methodological advances toward faster sepsis diagnostics.