Topological quantum materials host electronic states protected by topology and symmetry, giving rise to robust surface or edge states and unconventional electronic properties. Understanding how their electronic band structures respond to external perturbations is essential for both fundamental physics and potential applications. This thesis investigates the electronic structure of topological materials and its evolution under controlled perturbations by combining static angle-resolved photoemission spectroscopy (ARPES) and time-resolved ARPES (tr-ARPES).

First, chemical doping is an effective method for manipulating the electronic structure of materials. Cl-doped Bi₂Se₃ is systematically studied here. Chlorine incorporation acts as an effective electron donor, shifting the Fermi level while preserving the topological band structure and reinforcing the intrinsic n-type character through heterovalent substitution at Se sites. The time evolution of the band structure reveals a strongly reduced energy shift under prolonged extreme ultraviolet radiation (XUV) exposure compared to pristine Bi₂Se₃, indicating suppressed adsorption-induced band bending and a modified near-surface defect landscape. Together, these results demonstrate that chemical doping can simultaneously tune the bulk carrier density and stabilize the surface electronic environment, providing a controlled strategy to engineer the electronic structure of topological insulators without compromising their topological character.

Second, optical excitation with femtosecond laser pulses is employed as a route to investigate topological phases in the topological crystalline insulator (TCI) Pb_1-xSn_xSe. By combining time-resolved ARPES and static X-ray diffraction, we demonstrate that the lattice constant serves as the fundamental control parameter of the normal-insulator-to-topological-crystalline-insulator transition. tr-ARPES measurements reveal that optical excitation, generating electronic temperatures far above the topological-to-normal transition temperature T_c, unexpectedly drives the system deeper into the TCI phase. Analysis of the transient electronic structure shows that the excitation induces an ultrafast lattice contraction on a sub-picosecond timescale. This contraction originates from an electronically induced strengthening of bonds in the inverted band-gap regime. These results show that the TCI phase is robust against optical excitation.

Finally, a spatially structured optical pump, realized using a transient optical grating geometry, is combined with tr-ARPES to investigate ultrafast dynamics in quasi-free-standing bilayer graphene. Although this approach enables spatially and temporally modulated excitation, efficient strain-wave generation requires high pump fluence, leading to enhanced space-charge and surface photovoltage effects. These effects distort photoelectron trajectories and shift measured energies, thereby limiting the sensitivity to subtle band-structure changes. This highlights important experimental constraints in high-fluence ultrafast photoemission measurements.

From a methodological perspective, we optimized the spot sizes of both the pump and probe beams in the tr-ARPES setup, thereby improving the spatial resolution and reducing the influence of sample inhomogeneity. A smaller spot size also increases the achievable upper limit of the pulse fluence for a given laser power, providing greater flexibility for different experimental conditions. In parallel, we employ ultrafast laser-assisted scribing to guide the cleavage process along a desired crystallographic plane, which enhances the reliability and reproducibility of sample preparation. In addition, comprehensive data processing and electron-optics-assisted conversion of raw data from a time-of-flight photoelectron analyzer are implemented to reconstruct the electronic structure in energy–momentum space.

Overall, this thesis demonstrates how static and time-resolved ARPES can be used to probe the electronic structure of topological materials and their evolution under controlled perturbations, highlighting general strategies for tuning electronic states as well as key experimental challenges in exploring the dynamic properties of quantum materials.

According to the principle of conferred powers, a core principle of European Union (EU) constitutional law, the EU may only regulate in areas where the Member States have conferred it competencies to do so. While the EU has used its legislative power in wider areas over time, two traditional fields that for a long time have remained mainly within the national legislative area are tort law and general administrative law. For the last decade, there has been an increasing interest from the EU legislator side to make use of these national tools to ensure a uniform and effective implementation of EU law. Through thematic legislation on sector-specific matters, EU law today impacts legal areas further from the core of EU law—such as tort law and general administrative law. The reason for the EU legislator’s interest in these areas can be explained by the function, within these areas, of realizing EU legislation. In relation to the regulatory framework for the EU digital economy, the EU legislator has explicitly underlined the importance of developing trustworthy governance schemes for EU citizens to overcome their hesitancy to use digital tools and share their data. This development can be contrasted with the development within United States administrative law, which seems to be guided by distrust and limitations of the powers of the administrative organs.  This Paper will examine EU mechanisms for implementation through tort and general administrative law actions in the areas of data protection, artificial intelligence (AI), and PFAS chemicals, with a special focus on the Swedish legal setting.

Consensus protocols are a cornerstone of distributed systems. They enable multiple, independent nodes to reach an agreement that cannot be overturned. This is fundamental in building replicated services that appear as a single system with strong consistency and high availability guarantees. Today, consensus protocols are central to many critical services, from cluster orchestration systems to global-scale distributed databases. However, despite their widespread adoption across diverse systems, the consensus protocols used in practice typically adhere to a general-purpose design that is agnostic to the execution environment in which they operate. As a result, significant optimization opportunities are left unexploited across the network, workload, and storage layers. These opportunities have become increasingly important to leverage as modern applications and infrastructures demand higher performance, stronger resilience, and more flexibility than a one-size-fits-all design can provide.

This dissertation explores how consensus protocols can be made context-aware to derive optimizations from their execution environment that improve resilience, performance, and adaptability. We present four such mechanisms, each addressing a different layer of the consensus stack. Omni-Paxos provides a principled approach to handling partial connectivity failures at the network layer. UniCache reduces redundant communication by learning from recurring patterns in the application workload. Metronome leverages the characteristics of persistent storage to expose a fine-grained trade-off between runtime and recovery performance. AutoQ continuously adapts critical configuration parameters to sustain high performance under changing workloads in multi-region deployments. Crucially, these improvements are realized as bolt-on mechanisms that attach to protocols commonly used in practice, avoiding the burden of designing a new protocol from scratch. Together, these contributions demonstrate that embedding context-awareness into consensus allows established protocols to effectively meet the performance and resilience demands of modern distributed systems.

Local governments responsible for welfare provision regularly outsource information and communication technology (ICT) development and services. Despite the reliance on private-sector ICT firms, little attention has been paid to the capabilities of these firms and their perspective on public-sector digitalization. This paper addresses this research gap by examining how ICT-supplier firms view 1) what constitutes their most important capabilities in the context of public-welfare digitalization and 2) what factors influence their creation and character. The study employs an interpretative research design, using semi-structured interviews and thematic analysis. The results indicate that ICT suppliers rely on higher-order relational capabilities to enable them to deploy value-adding capabilities. Additionally, the results show that inadequate municipal ICT governance, public-sector coordination, and insufficient procurement practices cause systemic uncertainty, which ICT suppliers are required to manage.

Charged-hadron distributions in heavy-flavor jets are measured in proton-proton collisions at a center-of-mass energy of √s=13 TeV collected by the LHCb experiment. Distributions of the longitudinal momentum fraction, transverse momentum, and radial profile of charged hadrons are measured separately in beauty and charm jets. The distributions are compared to those previously measured by the LHCb collaboration in jets produced back-to-back with a Z boson, which in the forward region are primarily light-quark-initiated, to compare the hadronization mechanisms of heavy and light quarks. The observed differences between the heavy- and light-jet distributions are consistent with the heavy-quark dynamics expected to arise from the dead-cone effect, as well as with a hard fragmentation of the heavy-flavor hadron as previously measured in single-hadron fragmentation functions. This measurement provides additional constraints for the extraction of collinear and transverse-momentum-dependent heavy-flavor fragmentation functions and offers another approach to probing the mechanisms that govern heavy-flavor hadronization.

Recently, IceCube reported neutrino emission from the Seyfert galaxy NGC 1068. Using 13.1 yr of IceCube data, we present a follow-up search for neutrino sources in the northern sky. NGC 1068 remains the most significant neutrino source among 110 preselected gamma-ray emitters while also being spatially compatible with the most significant location in the northern sky. Its energy spectrum is characterized by an unbroken power-law with spectral index γ = 3.4 ± 0.2. Consistent with previous results, the observed neutrino flux exceeds its gamma-ray counterpart by at least 2 orders of magnitude. Motivated by this disparity and the high X-ray luminosity of the source, we selected 47 X-ray-bright Seyfert galaxies from the Swift/BAT spectroscopic survey that were not included in the list of gamma-ray emitters. When testing this collection for neutrino emission, we observe a 3.3σ excess from an ensemble of 11 sources, with NGC 1068 excluded from the sample. Our results strengthen the evidence that X-ray-bright cores of active galactic nuclei are neutrino emitters.

This article emerges from a sustained transnational dialogue between two cisgender female, first-generation immigrant scholars of Japanese origin – one identifying as Nikkei in Sweden and the other as mixed-race Japanese (white) in Canada. Through collective autobiographical inquiry, we explore what we term a middle space – a site of ambiguity, tension, and transformation where intersectionality is both theorized and embodied. We situate our personal narratives within broader structural frameworks to contribute to scholarship that treats intersectionality as both theory and praxis – a tool for critical reflection and social transformation. Guided by critical feminist and collective methodologies, our writing emphasizes reflexivity, dialogue, and the interrogation of power dynamics in knowledge production. Our lived experiences reveal how positionalities shaped by sociocultural and institutional contexts resist binary categorizations of privilege and marginalization. These identities are continuously negotiated and inform our academic and personal engagements. We underscore the importance of collective methodologies in illuminating complex positionalities and advancing intersectional feminist scholarship. By inviting readers into our middle space, we offer a site of intersectional engagement, activism, and reflexivity where theory meets lived experience, and where shifting dynamics of power and identity are critically examined.

Introduction People living with HIV (PLWH) may be exposed to harmful political, social, economic and environmental factors that exacerbate their risk of mental health conditions. Such factors can interact synergistically to worsen HIV and mental health-related outcomes, creating a syndemic. This study aims to review existing literature on mental health-related syndemics and their impact on HIV and mental health outcomes.Methods CINAHL, Embase, MEDLINE, PsycInfo, Scopus and ProQuest were searched. We included observational studies that investigated a potential mental health-related syndemic and/or reported the impact of a syndemic on HIV outcomes (antiretroviral therapy [ART] adherence or viral suppression), or mental health outcomes (mental health-related quality of life, depression, anxiety, schizophrenia, bipolar disorder, post-traumatic stress disorder or psychological distress) among PLWH. Screening, data extraction and quality assessment were conducted by two independent reviewers. The Newcastle-Ottawa Scale (NOS) was used to assess the quality and risk of bias. The impact of syndemic count on ART adherence and viral suppression was pooled using random effects using STATA and the remaining findings were synthesised narratively. PRISMA guidelines were followed.Results 32 studies were included with sample sizes ranging from 51 participants to 14,261. Six studies reported on mental health-related syndemics among PLWH, four of which found depression or distress to be the most influential syndemic factor. Mental health conditions within syndemics often cluster and are significantly associated with socioeconomic factors such as food insecurity, stigma and violence. Fifteen of 16 studies found a significant association between adherence and the number of mental health-related syndemics. Pooled odds ratio of seven studies showed a significant reduction in adherence (OR = 0.73; 95% CI = 0.55 - 0.96); heterogeneity was high (I2 = 98.58%). Eleven of 13 studies found a significant association between the number of mental health-related syndemics and being virally suppressed. Four studies resulted in a significant pooled odds ratio for having detectable viral load (OR = 1.26; 95% CI = 1.10 - 1.44); heterogeneity was moderate (I2 = 52.38%).Conclusion Despite wide variation in how syndemics were defined and measured across studies, our findings suggest that mental health conditions, particularly depression, strongly influence synergising syndemics among PLWH, and mental health-related syndemics negatively impact ART adherence and viral load. These findings underscore the need for syndemic-informed holistic care models to address the intersecting burden of mental health conditions and psychosocial factors among PLWH.

Industrial tightening processes play a central role in ensuring the reliability, repairability, and resource efficiency of products that rely on threaded fastener joints. The primary functional quantity in such joints is the clamp force, which governs joint reliability but is normally not measured directly during industrial tightening. Instead, tightening systems are predominantly controlled using torque and angle, so that the achieved clamp force must be inferred indirectly. This relation is strongly influenced by friction in the threads and under-head contact, as well as by structural compliance, embedment, and other internal process conditions. Friction varies between specimens and across operating conditions, which limits the robustness of conventional tightening strategies and poses a central challenge for clamp-force-oriented control. These challenges create a need for physically grounded, dynamic simulation models that explicitly account for the coupled behavior of the tightening system and remain suitable for control-oriented analysis.

Dynamic, control-oriented simulation models are developed and assessed for threaded fastener tightening. The tightening system is represented as a coupled rotational and translational dynamic system, in which thread kinematics, frictional losses, joint compliance, phase-dependent joint behavior, and embedment interact during the tightening process. Particular attention is given to the transition from rundown to seating and elastic clamping, and to transient operating conditions such as acceleration, deceleration, dwell phases, break-away, and motion near zero relative velocity. A structured system-level model is first established to capture the dominant torque–angle–clamp-force behavior of the tightening process, including embedment as an explicit internal state. This framework is then used to compare representative friction-model formulations under tightening-relevant conditions, with emphasis on transient dynamic response, numerical robustness, computational effort, and the practical distinguishability of model responses.

The results show that the dynamic model reproduces the principal qualitative features of realistic tightening processes, including the build-up of torque and clamp force across process phases and the influence of phase transitions and friction on the overall response. The friction-model comparison demonstrates that the influence of model formulation is strongly regime-dependent: differences between formulations are small during continuous relative motion, but become pronounced near zero relative velocity, during break-away, and in stick–slip-prone conditions. Several friction-model formulations can reproduce experimentally observed tightening behavior with comparable accuracy when appropriately parameterized. This indicates that the practical predictive limits of dynamic tightening simulations are constrained not only by friction-model structure, but also by parameter uncertainty, calibration ambiguity, process variability, and limited measurement-based distinguishability. The models are therefore most effective as structured simulation environments for analysis, comparison, and method development rather than as exact specimen-specific predictive twins. Overall, the results provide a foundation for future work on clamp-force estimation, observer design, and model-based tightening control.

The ATLAS experiment has performed a measurement of coherent exclusive J/ψ → μ⁺μ⁻ production in ultraperipheral Pb+Pb collisions at √sNN=5.36 TeV. The data was recorded at the Large Hadron Collider (LHC) during 2023, and corresponds to an integrated luminosity of 79 μb⁻¹. Exclusive J/ψ candidates were selected with a dedicated track-sensitive trigger based on the ATLAS transition radiation tracker. The analysis involves reconstruction of the dimuon invariant mass based on muon tracks from the inner detector, as the muon transverse momentum range of interest precludes the use of the standard muon reconstruction and identification algorithms. Differential cross sections are measured as a function of J/ψ rapidity and are compared with theoretical predictions. After extrapolation to √sNN=5.02 TeV, they are also compared with previous measurements performed by other experiments using data from LHC Run 2. While the results agree reasonably well with theoretical predictions, they are in tension with previous Run-2 results for the central rapidity region.

By exploiting quantum mechanical behavior, quantum computers have the potential to carry out classically hard computations, such as the prime factorization of integers, with disruptive, exponentially better efficiency, yet they struggle with classically simple task like integer addition. Hybrid applications, combining both quantum and classical computations, attempt to take advantage of the strength of both approaches while avoiding their weaknesses. In such applications, the design of the interface between quantum and classical computers deserves attention as a potential performance bottleneck.

In this thesis, the design of a modular software stack for hybrid quantum/classical applications that is agnostic to the used quantum technology platform is developed both for high-level application-oriented as well as high-performance low-level use-cases. A hardware description language for quantum circuits derived from the industry standard VHDL language is proposed, and its usage in tightly-coupled hybrid applications, where quantum and classical computations overlap in time, is discussed. To enable low-latency coupling, the proposed hybrid architecture connects quantum computations to hardware implementations of timing critical classical computations and utilizes established hardware/software co-design patterns to interface higher-level classical computations.

Experimental evidence of noise effects on state-of-the-art quantum hardware is presented for the case of solving partial differential equations. This supports the conclusion that frequent interaction between short and shallow quantum and classical computations is necessary even for loosely-coupled hybrid applications under these circumstances, strengthening the case for a low-latency, high-bandwidth quantum-classical interface as proposed in this thesis.

Throughout life, cells undergo cell-state transitions, such as changing cell identities or adapting to environmental stress. Because cells in an organism contain the same set of genes, distinct cell-state transitions arise from differences in gene expression. Gene expression is primarily regulated at the level of transcription, a complex process driven by RNA Polymerase II (Pol II). Beyond Pol II, transcription is coordinated by numerous transcription factors and at regulatory genomic regions, such as promoters and enhancers. By tracking transcription and its regulation upon cell-state transitions, basic biological principles can be identified and leveraged when studying diseases.

The papers presented in this thesis trigger and track transcriptional responses upon two types of cell-state transitions: stress and differentiation. Differentiation is a slow, controlled process that permanently alters the transcriptional program. In contrast, stress induces rapid, transient changes to the transcriptional program, keeping the cell alive and enabling recovery once the stress ends. A classic example of a stress response is the heat shock response (HSR), which is activated by elevated temperatures and other stressors that cause protein misfolding. The HSR represses thousands and activates hundreds of genes, some of which encode chaperones that assist in the correct folding of other proteins.

Across the papers, cell-state transitions are triggered mainly by elevated temperatures or chemical components. After a trigger, the transitions are explored primarily with mRNA-seq and PRO-seq, two genome-wide sequencing techniques. mRNA-seq tracks steady-state levels of mature mRNA, while PRO-seq tracks transcription of nascent RNAs. Paper I provides a computational workflow to generate maps of functional genomic regions, such as promoters and enhancers, from mapped PRO-seq reads. Such maps are central to studying transcriptional responses, and the workflow was used to generate results in Papers II–IV. In Paper II, transcriptional responses and master regulators that drive differentiation in human erythroid cells are explored. A brief signal causes slowly propagating and long-lasting transcriptional changes that prepare cells for future tasks involving oxygen transport. The paper also provides the first direct comparison between induced differentiation and stress in a cell model, revealing drastically distinct coordination of transcriptional responses.

Paper III–V focus on transcriptional responses upon stress. In Paper III, transcription in golden retriever macrophages is tracked under normal conditions and upon heat stress. The first complete transcriptional profiling of the dog genome and characterization of the HSR in dog are provided. In Paper IV, transcription is tracked in fly, mouse, dog, and human upon heat stress. The paper uncovers that intron length is an evolutionarily conserved regulatory mechanism that times the production of heat-induced chaperones. This finding addresses the broader question of why any genome has introns that span hundreds of kilonucleotides. In Paper V, transcriptional programs of three distinct forms of protein-damaging stressors are compared: heat shock (HS), HSP90 inhibition, and polyglutamine (polyQ) aggregation. PolyQ aggregation is a feature of Huntington’s disease (HD), for which no cure exists. The paper reveals that transcriptional responses are fundamentally different for the three stressors. PolyQ aggregation is linked to impaired acute stress responses, which could explain why previous attempts to ameliorate the disease by inducing the HSR have not been successful. There is also a lack of commonly induced or repressed genes across mouse brain tissues under polyQ stress, which suggests that therapeutics targeting pathways rather than specific genes should be explored. Overall, this thesis expands current knowledge of transcriptional responses upon cell-state transitions in health and disease.

We investigate the non-Gaussian features in the distribution of the matter power spectrum multipoles. Using the COVMOS method, we generated 100 000 mock realisations of dark matter density fields in both real and redshift space across multiple redshifts and cosmological models. We derived an analytical framework linking the non-Gaussianity of the power spectrum distribution to higher-order statistics of the density field, including the trispectrum and pentaspectrum. We explored the e ffect of redshift-space distortions, the geometry of the survey, the Fourier binning, the integral constraint, and the shot noise on the skewness of the distribution of the power spectrum measurements. Our results demonstrate that the likelihood of the estimated matter power spectrum significantly deviates from a Gaussian assumption on non-linear scales, particularly at low redshift. This departure is primarily driven by the pentaspectrum contribution, which dominates over the trispectrum at intermediate scales. We also examined the impact of the finiteness of the survey geometry in the context of the Euclid mission, and we find that both the shape of the survey and the integral constraint amplify the skewness.

The ongoing digitalization of industrial systems is transforming maintenance practices by enabling continuous monitoring and data collection. This creates the foundation for data-driven approaches and enables advanced diagnostics through the use of machine learning methods in maintenance applications. To achieve reliable diagnostic performance, supervised machine learning methods rely on representative training data covering diverse operating conditions and characteristic signatures of different failure modes, with sufficient data quality, accurate labels, and proper annotations. However, in industrial maintenance, these requirements are commonly not satisfied due to heterogeneous operating regimes, harsh data acquisition conditions, and the inherently rare occurrence of faults. At the same time, maintenance applications are often safety-critical and associated with significant operational and economic risks, which motivates the need for reliable diagnostics even under data-constrained conditions.

This thesis treats data scarcity as an inherent and largely unavoidable constraint of industrial maintenance and develops a structured approach to characterize it, assess its effects on diagnostic reliability, and identify effective strategies to operate under such limitations. Data scarcity is formally defined as a multidimensional concept encompassing five dimensions: availability, coverage, representativeness, usability, and quality, establishing a framework for systematically assessing data-related limitations in industrial monitoring. Diagnostic reliability is characterized along three properties: accuracy, generalization, and robustness, which together define the basis for evaluating machine learning-based diagnostics under data scarcity.

The effects of data scarcity on diagnostic reliability are investigated through structured empirical studies that systematically vary controlled data scarcity factors, including data volume, fault sample ratio, and measurement degradation, across three transfer scenarios with increasing domain shift. Within these scenarios, classical machine learning and deep learning methods are combined with different knowledge transfer strategies, including domain adaptation, transfer learning, and joint learning, to examine how individual factors, their interactions, and the choice of learning strategy jointly determine diagnostic performance. This factorial approach connects the conceptual characterization of data scarcity directly to empirical evaluation, enabling quantitative assessment and analytical interpretation of model behavior under realistic industrial constraints.

The results establish that model effectiveness is regime-dependent: no single learning strategy is universally optimal, and diagnostic performance is governed by the interaction between data characteristics, domain conditions, and the learning strategy employed. The findings are consolidated into practical insights for scarcity-aware machine learning, providing actionable guidance for data acquisition, model selection, and the design of reliable fault detection systems for condition-based maintenance in industrial environments.

Utvärdering i praktiken – en handbok för praktiker och studenter är en engagerande och handfast guide för alla som vill genomföra såväl som förstå utvärderingar. I ett samhälle där krav på evidens, kvalitet och ansvar genomsyrar offentlig verksamhet räcker det inte att bara mäta – vi måste också förstå, värdera och förbättra. Denna bok visar hur utvärdering inte enbart behöver vara ett kontrollinstrument, utan kan bli ett kraftfullt verktyg för lärande, utveckling och kritiskt tänkande. Boken förenar teoretisk fördjupning med konkret vägledning. Den fungerar som en pedagogisk guide genom hela utvärderingsprocessen, med sitt steg-för-stegupplägg som ger en tydlig struktur och stöd i det praktiska utvärderingsarbetet.Samtidigt ges en refekterande och kritisk belysning av evidensbasering, granskningssamhället och utvärderingens roll i modern styrning.Det dubbla perspektivet gör boken till ett stöd för att genomföra genomtänkta, relevanta och användbara utvärderingar – och för att förstå utvärderingens betydelse i ett större samhälleligt sammanhang. Bokens utgångspunkt är enkel: målet är inte fler utvärderingar – utan bättre utvärderingar.

Nickel-based superalloys are indispensable for hot structural components in aeroengines due to their exceptional high-temperature strength and oxidation resistance. Alloy 718 has been the industry standard for decades; however, its application is limited to temperatures below approximately 650°C. The continued drive toward higher engine operating temperatures to improve fuel efficiency and reduce emissions has motivated the development of next-generation superalloys with greater temperature capability. VDM Alloy 780 and G27 are recently introduced wrought Ni-based superalloys designed for service temperatures approaching 750°C and are promising candidates for aeroengine components fabricated by fusion welding. The successful implementation of these new superalloys in fabrication depends critically on weldment integrity, which is influenced by factors such as the fusion zone (FZ) microstructure, base material (BM) grain size, and susceptibility to weld hot cracking.

In the first part of the thesis, microstructural characterization reveals that weld solidification in both superalloys results in Nb-rich MC carbides and irregularly shaped Laves phase as the major interdendritic constituents in the as-welded FZ microstructure, mainly due to Nb microsegregation. Because the Laves phase is inherently brittle and generally detrimental to the mechanical performance of superalloys, its removal through post-weld solution heat treatment (PWSHT) is essential. A PWSHT at 1060°C for 1h is identified as optimal, achieving complete dissolution of Laves phases without promoting η-phase formation.

Importantly, this heat treatment results in only relatively moderate BM grain growth in both alloys, with slower grain coarsening kinetics relative to Alloy 718. This retarded grain growth behavior is beneficial for preserving a relatively fine-grained BM microstructure while enabling complete removal of the detrimental Laves phases inthe FZ through PWSHT.

In the second part of the thesis, hot cracking susceptibility was systematically investigated using Varestraint and Gleeble hot-ductility tests. Solidification cracking in both alloys is found to be largely insensitive to pre-weld solution heat treatments (SHTs). In contrast, heat-affected zone (HAZ) liquation cracking is strongly influenced by pre-weld SHTs, through altering the grain size and the magnitude of boron segregation at grain boundaries. When optimized, both alloys exhibit hot-cracking susceptibility comparable to, and in some cases superior to, that of Alloy 718. Overall, the results demonstrate that VDM Alloy 780 and G27 possess viable weldability for aeroengine fabrication, provided that pre-weld SHTs are carefully tailored to control microstructure, particularly grain size and grain boundary boron segregation, to minimize HAZ liquation cracking susceptibility.

The 2nd MObility for Vesicle research in Europe (MOVE) Symposium, held in Belgrade-Serbia, from October 8 to 11, 2024, showcased the dynamic and interdisciplinary nature of extracellular vesicles (EVs) research in Europe. Organized by eight National EV Societies under the MOVE initiative, the event gathered over 280 attendees from 28 countries, promoting collaboration and scientific exchange. The symposium featured eight keynote lectures, 48 oral and 126 poster presentations, and sessions dedicated to EV-related tools and industry innovations. The scientific program was structured around seven core themes: EV biogenesis and signal transmission, roles of EVs in health and disease, EV-based biomarkers, interspecies communication, novel EV preparation and analysis techniques, therapeutic and regenerative applications, and the manufacturing of native and engineered EV products. Supported by 18 sponsors and the Ministry of science, technological development and innovation of the Republic of Serbia, the symposium also highlighted the MOVE Fellowship Program and offered rich networking opportunities. This landmark event reinforced MOVE's promising mission to promote excellence, mobility, and resource sharing in EV research across Europe.

Background: The rising prevalence of pediatric obesity is a critical public health issue linked to lifelong metabolic and cardiovascular risks. Identifying early-life predictors is essential for effective prevention.

Aim: This thesis aimed to identify pre- and perinatal factors associated with early childhood growth and the development of overweight and obesity.

Methods: Four studies were conducted using the Uppsala County Mother and Child (UCMC) cohort, including up to 57,000 mother-child pairs born between 2000 and 2015. Data were integrated from several Swedish national registers. Study I examined maternal random capillary glucose levels; Study II investigated maternal pre-pregnancy BMI and gestational weight gain (GWG); Study III compared elective Caesarean section (CS) with vaginal delivery using propensity score matching; and Study IV evaluated the interaction between birth size (Large-for-Gestational-Age, LGA) and infancy growth patterns (0–1.5 years). Analyses included mixed regression models for growth trajectories and logistic and Poisson regression for overweight and obesity risk.

Results: Higher maternal glucose levels were associated with increased birth size, though these effects diminished by age five (Study I). In contrast, maternal pre-pregnancy BMI and excessive GWG were strongly associated with size at birth and sustained higher BMI trajectories and increased odds of childhood obesity at age four. While GWG significantly influenced growth up to 18 months maternal pre-pregnancy BMI emerged as the dominant factor for growth between 1.5 and 5 years (Study II). Mode of delivery did not significantly influence growth trajectories or obesity risk when adjusted for baseline characteristics (Study III). Study IV revealed that children born LGA with accelerated infancy growth faced the highest risk of obesity (RR ~5.0–7.9). Children born Appropriate-for-Gestational-Age (AGA) who experienced accelerated infancy growth had a higher risk of obesity than children born LGA who experienced decelerated infancy growth.

Conclusions: Prenatal and early postnatal factors are significant predictors of childhood adiposity. While elective CS does not appear to increase risk, maternal BMI and GWG, maternal glucose levels, and infancy growth velocity are critical markers. These findings can help refine child healthcare guidelines to mitigate the long-term adverse health outcomes associated with accelerated BMI trajectories.

We show the reinterpretation of existing searches for exotic decays of the Standard Model (SM)-like Higgs, H -> aa (hh), in various final states, in the framework of the 2-Higgs Doublet Model (2HDM) Type-I. We then explore a new search for such light Higgses, a and h, at the Large Hadron Collider (LHC) Run 3 for an integrated luminosity of 300 fb(- 1). After performing a scan over the model parameters, we found that the inverted scenario of Type-I offers a new promising signal in the form of the following cascade decays: H -> Z*a -> Z*Z*h -> b (b) over bar mu(-)mu(+)jj. We investigate then its significance through a full Monte Carlo (MC) simulation down to the detector level.

In this study, we explore the possibility of using a 'd.et + dilepton + Missing Transverse Energy' (MET) signature to measure the neutrino Yukawa couplings in the Next-to-Minimal Supersymmetric Standard Model with right-handed neutrinos (NMSSM) when the lightest Supersymmetric partner (a right-handed sneutrino) is the Dark Matter (DM) candidate. We demonstrate that, unlike the minimal realization of Supersymmetry (MSSM) in which the DM candidate is a much heavier neutralino, the NMSSM model allows for a much lighter sneutrino to be the DM candidate, which can be produced at future e(+)e(-) colliders with energies up to around 500 GeV. The resulting signal from chargino pair production and subsequent decay is very pure, providing the potential to extract the Yukawa parameters of the (s)neutrino sector. These findings may motivate searches for light DM signals at such accelerators, where the mass of DM candidate is around the Electro-Weak (EW) scale.

Using tools for deductive verification, such as Frama-C, typically imposes substantial work overhead in the form of manually writing annotations. In this chapter, we investigate techniques for alleviating this problem by means of automatic inference of ACSL specifications. To this end, we present the Frama-C plugin Saida, which uses the assertion-based model checker TriCera as a back-end tool for inference of function contracts. TriCera transforms the program, and specifications provided as assume and assert statements, into a set of constrained Horn clauses (CHC), and relies on CHC solvers for the verification of these clauses. Our approach assumes that a C program consists of one entry-point (main) function and a number of helper functions, which are called from the main function either directly or transitively. Saida takes as input such a C  program, where the main function is annotated with an ACSL function contract, and translates the contract into a harness function, comprised mainly of assume and assert statements. The harness function, together with the original program, is used as input for TriCera and, from the output of the CHC solver, TriCera infers pre- and post-conditions for all the helper functions in the C program, and translates them into ACSL function contracts. We illustrate on several examples how Saida can be used in practice, and discuss ongoing work on extending and improving the plugin.

The immune system protects against disease, injury, and mortality, with the intravascular innate immune system (IIIS) playing a central role. It consists of plasma cascade systems and circulating blood cells that enable rapid and amplified responses through interconnected pathways. While normally well regulated, dysregulation—whether hereditary, congenital, or acquired—can cause excessive activation and lead to thromboinflammation, ie interconnected activation of coagulation and complement system. Components and activation products of these cascades can serve as biomarkers for diagnosis, disease monitoring, and treatment evaluation.

In Paper I, a magnetic bead-based immunoassay was developed to measure complement factor C1q in plasma and cerebrospinal fluid, showing reduced levels in systemic lupus erythematosus (SLE), especially patients with nephritis, and correlating with disease activity.

In Papers II-IV, we examined the thromboinflammatory response in the first 66 critically ill COVID-19 patient admitted to the ICU at Uppsala University Hospital, using newly developed assays targeting IIIS functions.

Paper II linked elevated mannose-binding lectin (MBL) to thromboembolic events (TE). 

Paper III found that blood groups A and AB were associated with increased risk of severe COVID-19.

In Paper IV we analyzed samples both cross-sectionally on day 1 and longitudinally for up to one month. The assessed IIIS biomarkers were compared with biochemical parameters, clinical outcome and death. Longitudinal analyses showed widespread activation of cascade systems, associated with multi-organ damage and predictive of clinical outcomes, highlighting potential therapeutic targets.

In Paper V, we conducted longitudinal analyses of Swedish and Norwegian COVID-19 cohorts, with milder disease, demonstrated early, sustained activation of innate immune pathways, including the complement and contact systems, supporting their role in disease progression and prognosis. Our findings corroborate previous reports demonstrating concurrent activation of innate inflammatory pathways.

Taken together, the studies in this thesis highlight the importance of having a broad panel of assays to monitor IIIS activation markers, both to improve understanding of disease mechanisms and to support the development of targeted therapies. They also leave us better prepared to refine and expand our analytical toolkit for investigating and monitoring IIIS responses in the next pandemic.

Thromboinflammation is the description of an unwarranted immune response coinciding with thrombosis. Often leading to serious disorders like ST-elevated myocardial infarction (STEMI), stroke or complications associated with COVID-19. The factors instigating such disease pathogenesis revolve around the innate immune system. The innate immune components involved are platelet activation, the complement system, the coagulation cascade and the contact system. This thesis navigates the pathways involved by redefining their initiating mechanisms and sources on biological and material surfaces, presenting novel pathway crosstalk and avenues for future therapeutics. 

This thesis begins by revisiting the activation of the alternative pathway (AP) of complement through the relevance of C3(H₂O). In paper I we present that the central complement component, C3 is activated on the surfaces of cells expressing distress patterns of altered self. This redefines the conventional idea of the alternative pathway simply being an amplifier of the classical and lectin pathways. Moving forth, paper II describes AP interactions with biomaterials. Now, at the forefront of medicine, applied in dialysis tubing and implants, we look into the toxic effects posed by nanoparticles leaking into the body. With C3 under the microscope, we identify a specific binding of Titanium dioxide nanoparticles to a region within the molecule responsible for AP convertase assembly.

This thesis proceeds then to investigate the contact system as in paper III, we pursue the natural physiological activator of Factor XII (FXII). Here, we present fibrin as an activator of the contact system initiating protein, FXII but also as a procoagulant surface. To deepen the understanding of innate immune pathway crosstalk, we aimed to link comeplement activity to coagulation by investigating the activity of the lectin pathway complement proteases, mannose associated serine proteases (MASPs) on FXII. In paper IV we discovered recombinant catalytic fragments of MASP-1 and MASP-2 enable activation of FXII, causing cleavage into beta FXIIa, a potent catalytic activator of the kallikrein-kinin system. 

In conclusion, we underline the importance surfaces have in our fundamental understanding of protein activation and inhibition and that moreover, crosstalk of plasma cascade systems unlock opportunity for therapeutic intervention.

This study investigates the impact of fiber composition and fabric structure on the liquid absorption and retention performance during pressure of weft-knitted fabrics designed for reusable incontinence products. Twelve fabric samples, made from polyester, polyamide (6.6), and viscose, were knitted in two structures—1 × 1 interlock and 1 × 1 rib—with varying stitch lengths. Key parameters such as porosity, air permeability, liquid absorption capacity (LAC), and retention capacity during pressure (RCDP) were measured and analyzed. Results showed that viscose fabrics demonstrated superior LAC (up to 312%) and RCDP due to their high hydrophilicity, fiber swelling, and porosity. Polyester and polyamide had lower LAC, with polyester performing better due to higher porosity despite its hydrophobic nature. Increasing stitch length reduced fabric density and increased porosity and air permeability, thereby enhancing LAC but decreasing RCDP. Rib structures consistently exhibited higher LAC, while interlock structures offered better RCDP due to smaller, more uniform pores. The findings highlight the importance of optimizing the porous structure by altering knitting parameters and fabric structure to develop reusable absorbent textiles that balance high absorption and retention capacity during pressure.

This paper examines the impact of renovations in the rental sector on tenants’ relocation patterns in Sweden between 1995 and 2019. The study’s aim is to explore and analyse individuals’ likelihood of relocation surrounding the years of renovation. We use register data to address the two questions: Are low-income households more prone to relocate when their building undergoes renovation? Are tenants in the private rental sector more likely to relocate during renovations? The findings indicate that tenants tend to relocate around the time of a renovation. However, it is not low-income individuals who tend to relocate; rather, they remain in place, which may indicate displacement lock-in, in which disadvantaged households are unable to relocate due to housing shortages and limited opportunities. The study also reveals that tenants in the private rental sector are more likely to relocate than those in the public rental sector, possibly reflecting different renovation strategies employed by these actors. Overall, the study contributes to the discussion on whether renovations lead to renoviction and displacement within a Swedish context.

Advances in AI hold considerable promise for organ transplantation. While every transformation brings change, not all change is transformative. Despite the rapid growth of AI in medicine, most applications remain in developmental or experimental stages, with relatively few having been successfully integrated into routine clinical practice. As a professional society, ESOT recognises that achieving meaningful impact will require more than technical progress. This position paper outlines five critical domains for successful implementation. (1) High-quality development: Coordinated collaboration and methodological rigour are prerequisites for trust; AI is only as robust as the data used to train it. (2) Ethical considerations: We must address risks to equity and access to care, and move from generic ethical principles to transplantation-specific ethical guidance. (3) Regulatory landscape: AI in transplantation is regulated under both EU medical device and AI legislation; compliance is central to stakeholder trust. (4) Responsible adoption: AI should augment, not replace, human expertise. Strengthening AI literacy is essential for meaningful adoption. (5) Participatory design: Active involvement of transplant professionals and patients is essential to address real clinical needs. These statements serve as a strategic framework to guide clinicians, researchers, and policymakers in making AI a genuine force multiplier for the transplant community.

Rift Valley fever virus (RVFV) is a mosquito-borne Phlebovirus and zoonotic pathogen affecting maternal-fetal health. Vertical transmission is linked to miscarriage and severe fetal outcomes, but mechanisms of placental pathogenesis remain unclear. We used first-trimester human trophoblast stem cells (hTSCs) to model infection at the maternal-fetal interface. Immunofluorescence, qRT-PCR, western blotting, and single-cell transcriptomics showed that hTSCs are highly susceptible to RVFV. Strand-specific viral transcriptomics confirmed the ambisense S segment and revealed preferential transcription of the M and S segments over L. RVFV induced G1 arrest, impairing trophoblast proliferation and differentiation, and drove widespread transcriptional reprogramming, including strong interferon lambda 1 (IFNL1) but modest type I interferon responses, and dysregulation of inflammatory and preeclampsia-associated genes such as RUNX1 and TGFBRAP1. Recombinant IFN-λ pretreatment reduced RVFV protein expression, highlighting hTSCs as a robust model and IFN-λ as a promising antiviral strategy.

Tofu and tempeh, derived from soybeans, are widely consumed for their nutritional value and high protein content. However, the production of these foods generates nutrient-rich wastewater that poses environmental challenges while offering opportunities for valorization. This study investigates the production of volatile fatty acids (VFAs) and acetic acid from tofu and tempeh wastewater via batch anaerobic digestion, utilizing various pretreatment methods. The pretreatments included adjustment of the pH to 6 and inoculum treatments with and without heat shock under mesophilic and thermophilic conditions. Results demonstrated that the highest average total VFA concentrations of 10.08 and 9.79 g L−1 were achieved for tempeh at T3 (tempeh wastewater + pH 6 + thermophilic + heat shock) and tofu wastewater at TF3 (tofu wastewater + pH 6 + thermophilic + heat shock), respectively. The highest acetic acid concentrations were observed under mesophilic conditions, reaching 77.32% for tempeh wastewater at T7 (tempeh wastewater + unadjusted pH + mesophilic + heat shock) and 92.40% for tofu wastewater at TF10 (tempeh wastewater + pH 6 + mesophilic + non-heat shock). Notably, increased VFA production was associated with reduced cumulative methane yields, such as 3.65 mL g−1 volatle solid (VS) for tempeh at T3 and 25.23 mL g−1-VS for tofu wastewater at TF3. These findings indicate the effectiveness of the pretreatment strategies in enhancing VFA and acetic acid production, suggesting significant potential for industrial applications. Further research is recommended to optimize production processes and explore the broader utilization of VFAs and acetic acid in the bioeconomy, promoting sustainability.

Background: Neonatal hypothermia remains a leading yet preventable contributor to morbidity and mortality among preterm and low birthweight (LBW) neonates, particularly in low- and middle-income countries where access to conventional thermal care technologies is severely constrained. While Kangaroo Mother Care (KMC) remains the cornerstone of thermal care in resource-limited settings, structural, logistical, physical, and social barriers significantly impede its consistent practice. This thesis presents the development and phased clinical evaluation of the Thermal Jacket, a reusable, electricity-independent neonatal thermoregulatory device designed to supplement KMC for managing hypothermia among preterm or LBW neonates in Bangladesh.

Methods: The thesis comprises four sequential studies conducted aligned with the WHO four-phase clinical trial model at different tiers of healthcare facilities in Bangladesh. Study I was a laboratory preclinical trial (81 mannequin events), which tested the device’s thermal performance across ambient conditions and reusability. Study II was a single-arm open-label safety trial (68 events among nine neonates) at a tertiary hospital. Study III was a stepped-wedge cluster-randomised trial (854 events among 150 neonates) across three secondary-level hospitals. Study IV was an exploratory qualitative study using in-depth interviews (n=30), focus group discussions (n=3), and key informant interviews (n=12).

Results: The Thermal Jacket maintained the target temperature range (36-38°C) for over 120 minutes in 98% of laboratory events, with no significant effect of ambient temperature or reuse up to 9 times on performance (Study I). In the safety trial, euthermia was maintained in 96% of events with no adverse clinical signs (Study II). The effectiveness trial showed that the Thermal Jacket, adjunct to KMC, significantly improved euthermia maintenance compared with KMC alone (91% vs. 77%; adjusted OR 2.65), with the largest gains observed among hypothermic neonates (Study III). Bayesian mediation analysis revealed that 37% of the intervention effect was mediated through increased thermal care duration. Study IV found that caregivers and healthcare providers navigated thermal care as a situated, morally informed practice, positioning the Thermal Jacket as an institutionally legitimate supplement that extended caregiving agency without displacing KMC.

Conclusions: Collectively, the evidence establishes that the Thermal Jacket is effective and clinically safe in managing hypothermia and contextually acceptable within Bangladesh's public health system, providing a strong empirical foundation for its integration into national neonatal care guidelines and scaled implementation.

Despite a growing interest in collaborative writing at primary school, comparative studies of young English as a foreign language (EFL) learners’ individual and collaborative texts are scarce. Previous research has primarily25explored how collaborative writing affects complexity, accuracy and fluency, that is, CAF measures, in learner texts, but such measures alone cannot capture the complexities of writing. This presentation thus reports on the results of a study informed by systemic functional linguistics (SFL), aiming to map and compare linguistic resources employed in narrative texts written individually and collaboratively in pairs by young EFL learners (aged 12). More specifically, the study illuminates linguistic resources expressing experiential meanings and evaluation by using transitivity analysis and the Appraisal framework.The tentative results indicate similarities between individually and collaboratively written texts. For example, young learners express similar experiential meanings, operationalised as six different types of process cores, when they write individually and in pairs. Individual and collaborative texts were also found to resemble each other when it comes to linguistic resources for evaluation, which frequently concern feelings and emotions. Moreover, the texts generally draw on a wide array of experiential and evaluative resources, irrespective of their length and whether they were written individually or collaboratively. This suggests that collaborative writing may not necessarily provide enrichment to young learners’ texts, at least not in terms of linguistic resources for representing and evaluating the world.

The human metabolome reflects contributions from host metabolism, microbial activity, environmental factors, and analytical methodology. Metabolites provide a direct readout of biochemical processes and their alterations under different physiological and pathological conditions. Liquid chromatography-mass spectrometry (LC-MS)-based metabolomics enables the detection and comparison of these molecules across complex biological systems.

In this thesis, global LC-MS metabolomics was applied to investigate methodological and biological determinants of metabolite profiles across controlled experimental systems and human studies. The effects of sample preparation and storage on the fecal metabolome were systematically evaluated. Metabolite recovery depended on the combination of extraction strategy and storage conditions rather than a single optimal method. Double liquid extraction (DLE) using DMSO-containing solvents improved recovery of small polar metabolites, including amino acids and peptide derivatives. Methanol-based extraction methods performed well under fresh sample conditions, while specific combinations, including methanol extraction of lyophilized samples and prolonged methanol storage, reduced detection of nucleobase- and vitamin-related metabolites. Fecal metabolomics was applied to autoimmune and chronic pancreatitis. Metabolic differences were observed across metabolite classes, including amino acids, peptide derivatives, and microbiota-associated metabolites, indicating shifts in gut-associated metabolic processes.

The analysis was extended to feces, plasma, and urine in individuals at high risk of developing pancreatic cancer. Metabolic alterations were not uniformly reflected across matrices. In urine samples, broad variation with limited consistency were observed, while plasma had less changes, and fecal samples exhibited the most structured alterations across diverse metabolite classes. Metabolomics analysis was further applied to a controlled co-culture system of commensal vaginal bacteria with pathogens. Metabolite increases depended on specific bacterial combinations and were not resolved by global multivariate analysis alone. Pairwise contrast analysis between co-cultures and corresponding mono-culture controls identified interaction-dependent metabolites, including proline-containing dipeptides and heterocyclic compounds such as β-carboline derivatives and urocanic acid, which demonstrated bioactivity by modulating the growth of Lactobacillus crispatus, Gardnerella vaginalis, Prevotella bivia, Candida albicans, Escherichia coli, and Staphylococcus aureus.

In summary, the results in this thesis from metabolomics analyses of different biological sample types define methodological constraints affecting metabolite detection and characterize context-dependent metabolic patterns across biological systems, biospecimens, and microbial interactions.

This study directs its focus to citizen education matters within the subject of social science taught in upper primary school in Sweden. The main focus is to examine teacher conceptions of teaching democracy to children of the ages 10-12, aiming to better understand aspects concerning the tensions between normative ideals, curricular expectations and classroom practice. Democracy is a complex concept containing both fundamental values and explicit subject matter, difficult to define without losing complexity and meaning. Relatively few studies have examined how teachers in upper primary school understand and enact democracy education in social science.

The study is theoretically informed by distinctions between procedural and substantive conceptions of democracy (Held, 2006), thin and thick democracy (Carr, 2008) and different citizenship ideals (Westheimer & Kahne, 2004) as to what content is taught and how it is taught. The analytical framework also contains the educational aspects of teaching about, for and through democracy, aiming to examine how these aspects are expressed and discerned in classroom practice. To examine this, interviews were conducted aiming for more knowledge concerning didactical choices of content and on what grounds teachers make their choices.

Although Swedish students demonstrate relatively good knowledge about societal structures and democracy according to ICCS surveys, other surveys indicate declining trust in democratic solutions and institutions among young people in Sweden. Previous research has raised concern that an overly thin, procedural conception of democracy in education may limit students’ opportunities to develop a deeper, more substantive understanding of democratic values, which might be more engaging and better support the formation of active, value-oriented democratic citizenship.

Against the backdrop of an ongoing worldwide democratic backslide, the study explores and conceptualizes how democracy teaching in upper primary school can be conceived and discusses its potential development. How the classroom is affected by the development of society and how teaching could relate to this, calls for attention at all levels of society, not at least by civic education for young learners.  

Introduction: Episodes of apnoea are common in extremely preterm infants (EPIs) and usually treated with caffeine and respiratory support. Understanding differences in apnoea definitions, monitoring practices, and use of respiratory stimulants is essential to improve future treatment.

Methods: Between March and July 2024, one lead consultant at European tertiary neonatal intensive care units (NICUs) was invited to complete a web-based survey on respiratory practices in EPIs. We sought information how they defined apnoea and monitored for it, and how they treated it with caffeine, doxapram, and non-invasive respiratory support.

Results: We received replies from 447/721 (62%) NICUs across 24 European countries. Most NICUs (74%) use both electrocardiogram electrodes and pulse oximetry for apnoea monitoring. All NICUs reported using caffeine citrate, with 102 centres (23%) starting it in the delivery room. The median loading, maintenance and maximum maintenance doses used are 20 mg/kg, 5 and 10 mg/kg/day, respectively. Caffeine is occasionally given twice daily in some NICUs (30%) and stopped at 34–35 weeks of postmenstrual age at most of them (74%). Doxapram is used at 111 (25%) NICUs, with geographical differences. Strategies for the use and escalation of non-invasive respiratory support in case of persistent apnoea are not clearly defined. Automatic closed-loop oxygen delivery is used at 25% of NICUs.

Conclusion: Despite consistency in the dosing and weaning of caffeine, there is much variation in the management of apnoea in preterm infants across Europe. Future research should focus on timing and dosage of caffeine, the use of doxapram, and strategies for optimising non-invasive respiratory support. 

Using population-wide administrative data, we study industry persistence in career transitions, focusing on entrepreneurial entry. We document that individuals who enter entrepreneurship are significantly more likely to remain in the same industry as in their prior employment compared to individuals who change workplace but remain in paid employment. This persistence is particularly strong among individuals with longer prior industry experience. We further show that entrepreneurs who remain in their prior industry have higher post-entry incomes and income growth than those who switch industries. The results suggest that entrepreneurship largely reflects industry-specific career continuation rather than broad occupational reallocation. 

Security Chaos Engineering (SCE) is a proactive approach to identify vulnerabilities and enhance security of systems. It embraces continuous security experimentation to build confidence in the capability of systems to withstand malicious conditions. Different SCE techniques are proposed for enhancing the resilience of software systems. The diversity of SCE techniques indicates the need for their collective analysis to uncover valuable practices and potential research opportunities. To fulfill this need, we consolidate and unify the knowledge on SCE practices through a systematic literature review. The results show that there has been limited and unsystematic investigation of SCE by the community, highlighting the importance of creating and promoting guidelines for SCE practices. Therefore, we create SCENE, a comprehensive set of guidelines for systematically reporting SCE. The goal is to support the clarity, consistency, and reproducibility of SCE practices. SCENE guidelines are evaluated by cybersecurity practitioners and active researchers in the field, and is mapped to established methodological guidelines. The results indicates that SCENE is perceived positive in terms of usefulness, understandability, practicality, and completeness. SCENE is also found to complement established experimental reporting guidelines and bridge the gap between academic studies and industrial use.

Colorectal cancer (CRC) is one of the leading cancers worldwide, with prevalence and mortality increasing in younger people. Intestinal inflammation and sex are emerging as risk factors for this disease, with patients with inflammatory bowel disease (IBD) showing increased appearance of intestinal tumors and males showing a higher incidence compared to age-matched pre-menopausal women. Sex hormones could play a role in this difference, especially estrogens, due to the natural difference in the endogenous abundance. Estrogen signaling, mediated through nuclear estrogen receptors alpha (ERα), beta (ERβ), or transmembrane receptor GPER1, is shown to regulate intestinal homeostasis, such as cell proliferation, apoptosis, differentiation, and adherence, making it necessary for the normal functioning of the intestine. As part of its functions, it also showed involvement in regulating microbial composition, immune signaling, and even circadian rhythmicity. However, the effects of sex and estrogenic signaling, although identified, are yet to be fully understood.

Therefore, the overarching aim of this thesis was to characterize the effect of the loss of ERβ in the intestinal epithelium and its influence on gut microbiome, intestinal rhythmicity, and immune microenvironment in response to inflammation.

In paper I, we aimed to identify the effect of estrogens in low-grade inflammatory conditions. In there, we identified that male and female mice obtained distinct microbial responses to the high-fat diet-induced intestinal inflammation. We also found that estrogen was able to modestly influence microbiota, highlighting two species, Collinsella aerofaciens and Ruthenibacterium sp., which correlated with inflammation.

In paper II, we utilized the spatial proteomics platform COMET to visualize the main immune cell populations in the mouse intestine. This multiplexed method allowed us to spatially characterize the immune cell infiltration throughout the length of the colon, giving us a chance to identify possible cell-cell interactions. We found that upon inflammation, males presented greater changes in immune cell infiltration, especially B cells and anti-inflammatory-like macrophages in the distal region.

Building on these results, in paper III, we investigated whether ERβ influences the infiltration of the immune cells. We found that loss of ERβ affects macrophage infiltration, with especially strong effects in males, as well as antigen-presenting cells and natural killer cells showing sex-specific responses to colitis. Additionally, immune cell colocalization was analyzed, and we found that upon loss of ERβ male immune cell interaction pattern in colitis was affected much more and became more similar to females. Finally, by plasma cytokine assay and tissue RNA sequencing, we have shown that intestinal-specific ERβ knockout mice displayed an increased response to colitis.

In paper IV, we aimed to see whether estrogen signaling and sex affect the circadian rhythmicity in the colon. In here, we saw that intestinal inflammation disrupted the expression of core circadian genes in mice and in cell lines. This disruption was further affected by sex and, mildly, by loss of ERβ in mice. Additionally, we have validated the findings in the human IBD dataset, indicating that males had heightened responses to inflammation and a lack of ERβ. Notably, we were also able to demonstrate that ERβ participates in the regulation of circadian rhythmicity through modulation of BMAL1, a key circadian component.

Overall, this thesis demonstrates that sex and estrogen signaling, particularly through ERβ, are important modulators of intestinal inflammation, shaping the response at multiple biological levels. Taken together, these findings highlight the importance of considering sex as a variable in studies and point to ERβ as a potential target for modulation of intestinal inflammatory response, spanning microbiome composition, immune cell dynamics, and circadian regulation.

Krav på obligatorisk hållbarhetsrapportering enligt EU:s direktiv CSRD (Corporate Sustainability Reporting Directive) har införlivats i svensk lagstiftning från och med år 2024. Införandet beräknades få stora konsekvenser i många kommunalt ägda bolag och koncerner som skulle komma att omfattas av rapporteringskravet. Situationen har dock förändrats efter att EU i början av 2025 presenterade ”Omnibus-paketet”, en akut åtgärd i syfte att minska företagens administrativa börda, som innebär att svensk lagstiftning återigen måste ändras. Införandet av CSRD, liksom uppskjutandet och förändringarna under den pågående processen, har medfört en osäkerhetssituation för de kommunalt ägda bolagen. I forskningsprojektet har analyser genomförts för att kartlägga vilka kommunalt ägda bolag och koncerner som omfattas av CSRD, både utifrån det ursprungliga direktivet och med hänsyn till de lättnader som har föreslagits i Omnibus paketet. I projektet identifieras även vad de kommunalt ägda bolagen behöver rapportera, där genomlysningen av verksamheterna utifrån den så kallade dubbla väsentlighetsanalysen till stor del styr vad som anses vara väsentligt att rapportera. Inom ramen för projektet belyses även vilka strategiska val kommunalt ägda bolag gör i förhållande till CSRD-rapporteringen, som exempelvis rationalisering av innehållet i rapporterna med avseende på relevans och hanterbarhet, att rapporteringen koncentreras till kommunkoncernernas moderbolag, samt att styrningen av processen kan ske centraliserat eller mer decentraliserat. Även om många kommunkoncerner har lagt ner ett omfattande arbete på förberedelserna inför CSRD-rapporteringen, så skjuter så gott som samtliga nu upp rapporteringen i den mån det är möjligt.

Accurate biomolecular structure prediction enables the prediction of mutational effects, the speculation of function based on predicted structural homology, the analysis of ligand binding modes, experimental model building, and many other applications. Such algorithms to predict essential functional and structural features remain out of reach for biomolecular complexes containing nucleic acids. Here, we report a quantitative and qualitative evaluation of nucleic acid structures for the CASP16 blind prediction challenge by 12 of the experimental groups who provided nucleic acid targets. Blind predictions accurately model secondary structure and some aspects of tertiary structure, including reasonable global folds for some complex RNAs; however, predictions often lack accuracy in the regions of highest functional importance. All models have inaccuracies in non-canonical regions where, for example, the nucleic-acid backbone bends, deviating from an A-form helix geometry, or a base forms a non-standard hydrogen bond (not a Watson-Crick base pair). These bends and non-canonical interactions are integral to forming functionally important regions such as RNA enzymatic active sites. Additionally, the modeling of conserved and functional interfaces between nucleic acids and ligands, proteins, or other nucleic acids remains poor. For some targets, the experimental structures may not represent the only structure the biomolecular complex occupies in solution or in its functional life cycle, posing a future challenge for the community.

We analyse high signal-to-noise ESPaDOnS/CFHT spectra of 20 very metal-poor (VMP) stars ([Fe/H] < -2.0) in the solar neighbourhood (within similar to 2 kpc), selected to be on planar orbits with maximum heights less than or similar to 4 kpc. The sample comprises 11 stars on prograde and 9 on retrograde orbits, all with relatively high eccentricities (0.5-0.9). Their chemical abundance patterns indicate enrichment from high-energy supernovae and hypernovae up to the Fe-peak, and contributions from fast-rotating massive stars and neutron star mergers for the neutron-capture elements. No significant chemical differences are found between prograde and retrograde stars. The [Sr, Ba, Eu/Fe] ratios resemble those of stars in classical dwarfs galaxies. Chemical dispersion and distance analyses further highlight the internal similarity of the sample and its separation from the bulk of the observed, non-planar halo population. Applying the same kinematical selection to another homogeneous dataset yields consistent results, confirming that this group of planar VMP stars exhibit peculiar chemical properties distinct from those of the observed halo and other known Galactic structures. These findings suggest that the stars formed in an environment that experienced a homogeneous chemical evolution akin to that of dwarf galaxies. A plausible scenario, supported by cosmological zoom-in simulations, is the early accretion of a single system whose subsequent dynamical evolution naturally produced stars on both prograde and retrograde planar orbits. If this interpretation is correct, we tentatively refer to this putative progenitor as Loki. However, comparisons with other planar VMP stars spanning a wider range of chemo-dynamical properties indicate that multiple accretion events likely contributed to this diverse population orbiting close to the Galactic plane.

Aims

Patients with device-detected atrial fibrillation (DDAF) have a lower stroke risk than those with ECG-diagnosed AF, requiring careful evaluation of oral anticoagulation benefits vs. its inherent bleeding risk.

Methods and results

An unmatched win ratio analysis was performed of the NOAH-AFNET 6 trial dataset, using components of the primary efficacy and safety outcomes of the trial. The primary analysis used this hierarchical order: (1) all-cause death, (2) stroke, (3) systemic or pulmonary embolism/myocardial infarction, and (4) major bleeding. Two additional analyses replaced all-cause death with cardiovascular death or included patient-reported outcomes. Win odds were calculated to account for undecided comparisons. Among 2534 patients 77 ± 7 years old, 947 (37%) women, median CHA2DS2-VA score 3 [interquartile range (IQR), 3–4], median follow-up 21 months (IQR, 10–38) 1 605 280 win ratio pairs were analyzed. The win ratio comparing edoxaban to no anticoagulation was 0.87 (95% CI: 0.68–1.10; P = 0.23). Most comparisons resulted in no clear winner (undecided pairs 84.9%). In the remaining comparisons, edoxaban won in 46% of the cases, placebo in 54%. Death and major bleeding were the most common events. The win odds was 0.98 (95% CI: 0.94–1.01; P = 0.23).

Conclusions

This hypothesis-generating win ratio analysis, integrating death, thrombotic events, and major bleeds with and without quality of life, did not find an advantage of anticoagulation with edoxaban over no anticoagulation in patients with DDAF. The most common events were death and major bleeding.

Over recent decades, the integration of digital technologies has reshaped operations and business models across industries such as banking, telecommunications, and manufacturing. Within construction, a range of digital technologies such as BIM, AI, and IoT likewise have altered project-level and operational practices. Large contractors test digital technologies through testbeds, pilot projects, and proofs of concept (POCs). Yet, because construction is organised through temporary projects, decentralised decision-making, and loosely coupled structures, these initiatives often remain isolated within individual projects or business units. As a result, lessons learned and demonstrated benefits are not easily transferred, embedded, or scaled across the firm. This recurring pattern, in which one pilot is followed by another rather than being translated into broader organisational change, is framed in this thesis as the Yet Another Pilot (YAP) syndrome. The prevalence of YAP confines benefits to individual projects and inhibits scaling that would enable firms to innovate business models, enter new markets, change core firm logics, and improve operational efficiency at firm level. Consequently, many firms have digitised data and information and partly digitalised operations, while digital transformation remains nascent. Existing literature has tended to focus on technology, projects, or SMEs, leaving the digital transformation of large construction contractors relatively underexplored. Hence, it remains unclear how digital transformation evolves within large contractors and how the barriers to scaling can be overcome in this context.

The purpose of this thesis is thus to investigate digital transformation in large construction contractors, with a particular focus on how digital pilot projects and POC initiatives can be scaled beyond the project level to support firm-level transformation. The phenomenon of digital transformation is examined through three interrelated dimensions: technological innovation, business development, and ecosystem evolution. The firm constitutes the unit of analysis, while the unit of observation is at the corporate level to capture firm-level transformation associated with digitalisation. To investigate this, two research questions have been formulated:

1. What strategic approaches do large construction contractors adopt in relation to digital transformation, and what factors hinder or enable the scaling of digital initiatives beyond the project level?

2. How can digital transformation in large construction contractors be conceptualised and analytically understood in relation to the scaling of digital initiatives?

To answer these questions and fulfil the purpose, the work combines a scoping literature review, an interview study, case study research, and conceptual development, resulting in a 72-marker model. The model captures the interactions between the three dimensions and five domains: creating value, managing change, scaling pilots, innovating business models, and corporate-level engagement.

In response to the first research question, firms adopt either defensive or offensive strategic approaches to digital transformation. Defensive firms use digital technology primarily to improve existing operations and strengthen current business structures. As a result, scaling beyond the project level remains limited, leaving these firms more constrained by the underlying barriers to innovation in construction. Offensive firms, by contrast, use digital technology not only to improve existing business, but also to extend current offerings and create new business opportunities. This allows digital initiatives to support new business creation, business model innovation, and ecosystem development. As a result, these firms are better positioned to address the barriers to innovation in construction and to scale digital initiatives beyond the project level.

In response to the second research question, digital transformation within large contractors is conceptualised as evolving through three sequential steps: alignment, reconfiguration, and adaptation. At an analytical level, firms’ strategic approaches can be compared using the 72-marker model, which reveals three distinct profiles: the operationally oriented digitalisation profile, the internally orchestrated transformation profile, and the advanced transformation profile. The operationally oriented digitalisation profile describes firms that recognise the value of becoming more data-driven, but where most efforts remain focused on internal efficiency, specific tools, and local business-unit initiatives. This profile is therefore associated with firms adopting a predominantly defensive approach. The internally orchestrated transformation profile describes firms with well-defined structures for innovation and change, prioritised innovation funding, and stronger capability-building efforts, where scaling is prioritised mainly within the firm rather than through business model innovation or ecosystem repositioning. This profile is associated with firms that remain mainly defensive but are beginning to develop a more offensive approach. In the advanced transformation profile, digitalisation extends beyond isolated technologies and is strongly linked to customer value, organisational change, scaling mechanisms, business model innovation, and corporate-level management. This profile is associated with firms that adopt a clearly offensive strategic approach.

The main theoretical contribution is the 72-marker model for studying digital transformation through the interactions between the three dimensions and the five domains. From a practical perspective, the contribution is an assessment model that enables managers to classify their firm’s approach to digitalisation, identify its strategic position, and prioritise actions towards specific business, technical, and ecosystem goals. The thesis is limited by its reliance on mainly qualitative interview data and corporate-level focus, with limited depth at the project and business-unit levels. In addition, the focus on large construction contractors constrains the generalisability of the findings to other firm types, such as SMEs. On this basis, future research could further test the model using a survey-based approach, as well as through more in-depth and longitudinal studies of construction firms of different sizes and in different geographical contexts. It could also extend the empirical scope to include more organisational levels.

Inte långt efter Stockholms högskolas tillkomst bildades ett institut för experimentell fysik. I Del 1 beskrivs detta liksom den tid under nittonhundratalet, till 1959, under vilken verksamheten förändrades endast måttligt. Del 2 ägnas åt den påverkan på institutionen som ”utbildningsexplosionen” medförde och den expansion och diversifiering av forskningen som skedde under sextio- och sjuttiotalen. Det påbörjades en samverkan med Institutionen för teoretisk fysik som senare ledde till en sammanslagning, till Fysikum. I Del 3 beskrivs hur förskjutningen från centralt till lokalt ansvar under nittonhundratalets sista del påverkade utbildningens utformning. Ett antal av de då aktuella forskningsprojekten omnämns i korthet och det redovisas hur antalet studenter och lärare/forskare ökade under århundradet. En sammanfattning av den presenterade översikten ges i Del 4, som är tänkt att vara tillfyllest för den som önskar en kortare, och mindre teknisk, redogörelse.

This prospective cradle-to-gate life cycle assessment evaluates lithium-ion battery pouch cells utilising novel bio-silica electrolytes and bio-silicon anodes and aims to integrate environmental sustainability and circularity considerations early in process development. Although the bio-silica and bio-silicon are sourced from barley husk bio-waste with minimal upstream burden, current processing routes are energy- and chemically intensive and generate substantial acid waste. Reliance on high-temperature treatments makes renewable electricity essential. Climate-change impact of cells utilising the novel materials falls from 13,200 kg CO₂-eq/kWh at lab-scale to 62 kg CO₂-eq/kWh when certain key parameters were optimised in an industrial scenario. Key levers for impact reduction include increasing active-material capacity, applying pre-lithiation, and optimising anode processing. However, even the best-case manufacturing energy demand (207 kWh/kWh cell) is around double that of conventional giga-factory production, underscoring the need for process innovation. From a circularity perspective, low material yields and high chemical intensity limit net environmental benefits, demonstrating that circular feedstocks do not inherently deliver sustainable outcomes. For developers, the results highlight the importance of more resource-efficient, higher-yield, and less energy-intensive routes to bio-silica and bio-silicon production, including feedstocks with higher silica content. For LCA practitioners, they emphasise challenges of scaling lab data and the scarcity of industrial benchmarks. Overall, bio-waste represents a potentially valuable feedstock for circular battery materials, although realising sustainable circularity depends on advances in processing efficiency and system-level optimisation.

Magnetotail current sheet (CS) flapping is a universal plasma phenomenon observed at multiple planets, yet its triggering mechanisms remain poorly understood outside of Earth. At Mars, single-spacecraft observations have also reported tail flapping, but the processes responsible for its onset have never been identified. In this study, we investigate the potential correlation between magnetic reconnection and magnetotail flapping using multipoint measurements from Mars Atmosphere and Volatile EvolutioN (MAVEN) and Tianwen-1 (TW-1) missions. We analyze an example event in which MAVEN observed a reconnection-associated CS crossing in the near tail while TW-1 simultaneously detected CS flapping further downtail. A statistical survey of joint observations from November 2021 to February 2024 identifies that about two-thirds of TW-1 flapping events coincide with reconnection signatures observed by MAVEN. Multiple magnetic flux ropes were also detected before or during flapping intervals, similar to previous observations at Earth, suggesting that reconnection-generated magnetic flux ropes may propagate tailward and drive plasma instabilities that trigger the tail flapping at Mars. These results provide the first multipoint evidence of a potential statistical correlation between magnetic reconnection and magnetotail flapping at Mars, enabling us to explore the potential triggering mechanism of magnetotail flapping. Our findings also offer new insights into Martian magnetotail dynamics and broaden the comparative understanding of this fundamental plasma process across planetary environments.

Populations of aquatic vertebrates, mainly fish, have dramatically decreased since the last century. Collapsed fish populations often show slow recovery or remain at the same level, due to associated changes in food web interactions and population characteristics. Most depleted fish populations are commercially exploited and play an important ecological role, and their recovery is a priority for conservation biology and the fishing industry. Restocking programs aim to restore populations and often habitats and ecosystems by releasing captive-bred individuals into their natural habitat. Releasing fish at early life stages, such as larvae, avoids the negative effects of captive breeding and reduces costs. The Eastern Baltic cod (EBC) is ecologically and genetically divergent from the Atlantic cod (Gadus morhua). In a few decades, the population size has dramatically decreased, and EBC now attains sexual maturity at half the size it used to. In parallel, the Baltic Sea is becoming warmer, more anoxic and fluctuating in salinity. Project ReCod aims to strengthen the EBC population through releases of yolk-sac larvae. This has further allowed close study of early life stages and their performance, as well as to better understand the situation of EBC. In this thesis, I increase our knowledge of EBC for restocking purposes and investigate its present and future situation. In Paper I, I found that neutral buoyancy plays a crucial role in determining salinity preference in first-feeding larvae. Paper II showed that yolk-sac larvae are able to adjust to a low salinity environment when released. In Paper III, I found that the elusive large and healthy cod from the Åland Sea (northern Baltic Proper) is not different from southern EBC and locally adapted to the low environmental salinity of the region; however, EBC eggs appear to be able to develop on sediment. Paper IV showed that, contrary to expectations, the smallest fish produced the largest and most buoyant eggs, and the eggs from small-sized fish were buoyant enough to avoid the anoxic bottom in the Baltic Sea. In Paper V, I found that climate change-induced increased water temperature and decreased salinity can be detrimental for the early stages of EBC.

Machine learning is widely used to identify complex patterns in data and translate them into useful predictions. The choice of modelling approach depends on both the available data and the question being addressed, while modelling priorities may vary depending on the intended end user. This thesis investigates predictive modelling in two distinct biomedical scenarios: prediction of the biological function of chemicals using network topology-derived data (Paper I), and prediction of disease course in multiple sclerosis (MS) using electronic health records from hospital visits (Papers II, III, and IV).

In Paper I, a deep learning model was developed to predict protein network topology clusters directly from chemical structure representations, enabling functional characterization and identification of biological similarity for compounds not present in existing databases.

The second part of this thesis addresses a clinical prediction problem in MS. Identifying the transition from relapsing-remitting MS (RRMS) to secondary progressive MS (SPMS) remains challenging in clinical practice, despite its importance for clinical trials, treatment decisions, and patient management. In Paper II, we developed a machine learning model combined with conformal prediction to classify RRMS and SPMS using data from the Swedish Multiple Sclerosis Registry (SMSReg). The study demonstrated that uncertainty-aware predictions can improve trustworthiness by identifying cases that are difficult to classify reliably. In Paper III, we prospectively validated this framework using newly collected SMSReg data and showed that the model remained well-calibrated and outperformed the current state-of-the-art method. In Paper IV, we extended this work to an international registry setting using data from SMSReg and from 37 countries in the MSBase registry, based in Australia. We showed that calibrating models to specific countries can improve disease course classification across heterogeneous real-world cohorts, while also highlighting challenges arising from variation in clinical practice and data availability. Across these studies, the explainable AI framework SHAP was used to identify influential variables and improve model interpretability.

Collectively, the findings show that machine learning can extract meaningful biological and clinical patterns from complex data, and that uncertainty quantification and interpretability are essential for clinically useful decision-support tools.

This thesis examines the modal auxiliaries in Elfdalian from a semantic perspective. Modal auxiliaries in smaller, traditionally non-standardised languages have received little attention, and the thesis aims to partially fill this gap by providing an in-depth study of such a language. As there is no established set of the Elfdalian modal auxiliaries, a first step is to identify verbs that can qualify as such. Discussions are conducted regarding the criteria that should be used to define the category. The commonly held view that morphosyntax is central to determining category membership is argued to have several shortcomings, and a semantic definition is adopted instead. According to this definition, auxiliaries with modal meaning are considered to be modal. Modal meaning, in turn, is defined as pertaining to the semantic category of modality and its subcategories: dynamic, deontic, and epistemic modality.

Drawing on information in grammar books and dictionaries, 16 verbs are identified as modal auxiliaries. These are examined in a self-compiled text corpus consisting of literary prose, periodical texts and transcriptions of dialect recordings. A key informant study is conducted as a complement. The following verbs are examined: bella, byöva, dugå, edd ulað, fą̊, fą̊ luv, fą̊ luv um, kunna, lär, mą̊, mą̊tte, munde, slippa, ula, wårå tundjin and werda. 

On a general level, the modal auxiliaries behave similarly to those in other Germanic languages. The same polysemic pattern by which the auxiliaries are used to express several modal meanings is also present in Elfdalian. At a more detailed level, however, the investigated forms exhibit certain distinctive features. These regard the semantic behaviour of individual verbs (notably, some verbs have a different semantic makeup than related ones in other languages) and the expression of some of the modal meanings. For instance, Elfdalian lexicalises meanings that other Germanic languages generally do not. Other findings include empirical support for the view that inferential meaning, often conveyed by modal auxiliaries, cannot be analysed as expressing a secondary modal meaning. The thesis also discusses the extent to which the modal auxiliaries form a coherent category. As these auxiliaries also convey other, non-modal meanings, the category is found to be rather loose. 

Enigma

This paper examines the role of private information in conflict. While acting on information can provide an advantage, using it can expose its source and diminish its value in the long run. I study this trade-off empirically, focusing on the Battle of the Atlantic during World War II. There, Allied merchant ships faced Nazi U-boats, which regularly communicated their positions with German central command using Enigma encryption. The Allies secretly broke these codes. I combine novel data on decrypted messages with records of U-boat and merchant ship losses. Using an event-study design, I show that U-boat sinkings of Allied ships fell by 80 percent in the days following position reports, likely due to the rerouting of merchant ships. In contrast, U-boats’ own survival declined only marginally. Allied strikes were selective, prioritizing high-capacity commanders and increasing over time—consistent with the Allies strategically forgoing benefits to protect their information access. Counterfactual simulations suggest that military intelligence prevented 40 percent of potential shipping losses.

Coffeehouses and the Rise of Science

Coffeehouses emerged as a key social institution in early modern England. In 1962, Jürgen Habermas famously argued that they transformed the public sphere by fostering rational debate, enabling Enlightenment ideas to flourish. This paper tests that claim in the context of Enlightenment science in seventeenth-century London. Exploiting the staggered spread of coffeehouses, we find a substantial increase in the number of applied scientists and scientific instrument shops coinciding with the establishment of the first coffeehouse in a jurisdiction. We argue that coffeehouses fostered this growth by lowering the cost of accessing scientific knowledge and making experimental science more interactive and public. Consistent with this mechanism, coffeehouses especially benefited individuals with weaker ties to elite intellectual circles, strengthened links between theory-oriented scientists and practical instrument makers, and increased the number of experimental instrument shops.

Leveling the Playing Field: Knowledge Production in the Digital Age

80% of all journals are not freely available—even though access to existing knowledge is crucial for pushing the research frontier. In this paper, we examine the impact of Sci-Hub, an online platform providing free access to scientific articles, on knowledge creation. Using data on 300 million geo-coded download requests, and the near-universe of scientific articles we employ an instrumented difference-in-differences design. We find that Sci-Hub has significantly changed consumption patterns of scientific works, with a substitution of references from open- to closed-access publications. In turn, greater access to frontier knowledge resulted in higher-quality research output as measured by citations, but not more publications.

Social Policy and Autocracy: Evidence from East German Administrative Data

This paper studies the role of social policy in shaping citizen-state relations under autocratic rule. I argue that social policies can increase political support especially when they signal recognition—of citizens’ needs, burdens and social identities. To examine this argument, I focus on the introduction of extended maternity leave in former East Germany, a policy that extended material benefits but also signaled attentiveness to women’s dual roles as workers and caregivers. Using administrative data on civilian bureaucrats, I show that women giving birth after the policy reform saw a surge in membership of the ruling party compared to women giving birth shortly before. I also find suggestive evidence of gendered spillovers: first, affected grandmothers were more likely to become members, but not grandfathers. Second, in present-day surveys, likely affected daughters lean more towards left-wing ideology.