The global accumulation of per- and polyfluoroalkyl substances (PFAS) in soils raises concerns about soil quality. While PFAS sorption may depend on the quality of soil organic matter (SOM), their unique properties may also affect SOM dynamics in complex and poorly understood ways, impacting long-term soil quality. Literature provides vague conclusions about how SOM, particularly its quality, influences PFAS–soil interactions and whether PFAS can modify SOM characteristics. The present study aims to enhance both the qualitative and quantitative understanding of the reciprocal impact that PFAS and SOM have on each other’s environmental fate. Sorption of three PFAS molecules and simultaneous mobilization of dissolved organic matter (DOM) in three distinct soils were studied. PFOS had the highest sorption by ranging 61–98% followed by PFOA and PFBA. 13C NMR analysis indicated that PFAS sorption is driven by hydrophobic components of SOM. The highest PFAS sorption was observed in soils containing polycyclic aromatic hydrocarbons (PAHs), while the lowest was recorded in soils with less hydrophobic SOM. Conversely, the presence of PFAS increased the release of DOM in soils with less hydrophobic SOM. The changes in DOM release induced by PFAS were directly influenced by the chemical properties of the soil components. Additionally, 1H NMR revealed notable structural changes in the chemical composition of DOM caused by PFAS, characterized by an increase in hydrophobic constituents and a decrease in hydrophilic components. The results indicated that PFAS can affect both the quantity and quality of SOM, potentially compromising long-term SOM stability and carbon sequestration in contaminated soils.

When designing wood materials for fire resistance, the charring rate is a critical parameter. However, the values defined in the relevant standards are not always determined in favour of safety. Determining the actual charring rate for a specific material using standard approved methods (e.g., cone calorimeter, large-scale tests) is costly, so we sought an alternative using small-scale testing. The Lindner method may be suitable for determining the charring rate, but it needs to be compared with standardized testing (e.g., cone calorimeter) to establish correlations between the results of the two methods. We examined the relationship between the charring tests performed with the cone calorimeter and the Lindner method on solid wood samples and plywood. Based on our investigations, the results of these tests show a strong correlation. In earlier research, we established that computed tomography (CT) imaging is suitable for spatial analysis of burned solid wood samples. In this study, we analysed the applicability of CT imaging for burned plywood samples using scans of burned plywood specimens. We found that the segmentation algorithm used for solid wood is not suitable for examining plywood without additional shape filters due to the intersection of gaps formed in the internal layers during production with the burned volume. 

This article explores inequality in European geoscience organizations through the

perspective of geoscience women professionals and their perception of gendered

positions in academia and industry. Male dominance in geoscience organizations has

previously been demonstrated within US and Canadian organizations, often in relation to

gender inequality in STEM subjects and rarely in relation to the specific ideals and practices

that shape geoscience. The current study contributes a European context, as well as a

comparative approach to gendered positions in the organizational contexts of academia

and industry. Using participatory research methods and visualization techniques, the

study collected 42 organizational maps of academic and industry organizations in

16 European countries. The results reveal perceptions of gender inequality in academic

and industrial geoscience organizations through women’s limited access to positions

of power, i.e. women geoscience professionals perceived underrepresentation in senior

management positions in industry and in senior positions in academic organizations.

Within the growing demand for geoscience expertise in the green transition, the results

raise questions about what the perceived structures of gender inequality mean in relation

to sustainable employment and good working conditions in European geoscience.

Electrical power systems operate at 50 Hz. However, generation loss, a sudden increase in loads, or faults in the system cause disturbances and deviations that destabilize the frequency of electrical power systems. Therefore, there is a need to study and improve the frequency stability of electrical power systems during disturbances. The present study examines improving the frequency stability of electrical power system, using a solar photovoltaic (PV) system, a battery energy storage system (BESS), and underfrequency load-shedding (UFLS) to estimate and control the frequency.The proposed method was tested on a standard Institute of Electrical and Electronics Engineers' (IEEE) 9-bus system that was simulated in MATLAB Simulink. The simulation results indicate that the used method significantly stabilizes the frequency of electrical power system.

Understanding a person’s life story can transform dementia care by promoting a person-centered approach. Documented life stories help staff to personalize care, but further research is needed to understand their construction and usage in care practice. The aim of this study was to explore assistant nurses’ experiences of life story documentation and their practical applications in dementia care practice. Five semi-structured focus groups were conducted, and data were analyzed using qualitative content analysis. The findings consisted of five themes: “Ensuring timing and accessibility when constructing a documented life story,” “Recognizing template limitations in capturing a comprehensive view of the person,” “Refining life story quality and understanding through ongoing dialogues,” “Building connection and support through insights from documented life stories,” and “Harmonizing life histories with evolving care needs in practice.” Our findings highlight the importance of a dynamic and inclusive approach to life story documentation that goes beyond rigid templates. Accessible and well-documented life stories can empower nursing staff to provide responsive and personalized care, enhancing the dignity and quality of life of people living with dementia.

Mining at deep-seated deposits is associated with high stresses, which upon redistribution during mining, may cause induced seismic events. This mining-induced seismicity can lead to rockbursts that pose a threat to mining activities. Rockburst failures are classified based on the location of their occurrences, sources, and severity. Rockbursts have been recorded in deep and hard rock mines in various countries around the world. In Sweden, rockburst failures have been prominent since the year 2000, attracting researchers to study Swedish deep mines experiencing these failures. An investigation and mapping of failures during seismic events at the Kiirunavaara mine in Sweden from 2014 to 2017 evaluated seismicity parameters but did not focus on the failures and performance of rock supports. This paper analyzes failures mapped and investigated during seismic events in four blocks at the Kirunavaara mine, focusing on the failure mechanisms of the rock and rock supports. It considers geological factors, rock support, and provides remedial suggestions. It was found that most damages were either directly or indirectly influenced by stress changes due to seismic events. This analysis can provide insights for designing rock supports to mitigate rockburst occurrences.

The present study focuses on the selective extraction of potassium from a hydrochloric acid-based feldspar leachate using solvent extraction with crown ethers, CE (dibenzo-18-crown-6 and 12-crown-4). The effects of hydrochloric acid concentration, extractant type, diluent, extractant concentration, and organic-to-aqueous phase ratio on potassium extraction efficiency have been examined. Dibenzo-18-crown-6 diluted in m-cresol was shown to preferentially extract potassium (≈85 %) from highly acidic hydrochloric acid solutions (2 to 6 M), with minimal co-extraction of impurities, such as aluminum and sodium, in a single extraction step. Aluminum, however, was shown to be extracted efficiently (≈99 %) at lower acidities (<0.1 M). The extraction mechanisms were explored using various analyses, such as slope analysis, nuclear magnetic resonance, and scanning electron microscopy showing that dibenzo-18-crown-6 forms a highly stable complex with potassium at 1:1 M ratio, (KCl)(CE), driven by the size compatibility between potassium ions and the crown ether cavity. For aluminum, the extraction mechanism likely involves the formation of a cooperative complex where aluminum ions are associated with the potassium-crown ether complex (AlKCl4)(CE). Increasing the concentration of hydrochloric acid increased potassium ion activity, chloride ion activity, and ionic strength in the solution. These changes would enhance selective potassium extraction over the formation and extraction of the aluminum‑potassium cooperative complex.

Despite overall improvements in general health, the prevalence of mental illness continues to rise, underscoring the need for innovative approaches to health promotion. This study examines how purpose-driven small and medium-sized enterprises (SMEs) design and develop nature-based interventions (NBIs) as social innovations to promote mental health. Using a case study approach, the research draws on data from workshops, semi-structured interviews, and expert stakeholder discussions involving 28 SME practitioners, eight public actors from social and healthcare sectors, nine entrepreneurs, and four experienced stakeholders. The analysis reveals that the successful development of NBIs depends on five core dimensions: accessibility, acceptance, affordability, meaningfulness, and knowledge. In addition, the study identifies a range of strengths, weaknesses, opportunities, and threats that SMEs encounter when navigating the complex landscape of NBI implementation. The findings highlight the potential of NBIs to complement traditional healthcare by fostering empowerment and supporting tailored recovery, while also offering strategic insights into the collaboration required for sustainable social innovation.

This study experimentally investigated laser micro-wire cladding (LMWC), an additive manufacturing process that covers a substrate with cladding tracks having small cross-section area and low dilution. Laterally fed 200 μm thin steel wire and a continuous laser beam were used to deposit single tracks with widths and heights between 220 to 370 μm and 115 to 180 μm, respectively. By carefully selecting setup and process parameters, tracks with 0 to 35 % dilution and deposition speeds up to 20 mm/s were realised. An advanced high-resolution high-speed imaging technique was used to study the melt transfer and evaluate process stability. Specifics of LMWC compared to regular sized laser wire cladding are proposed along with explanations based on size effects. Cross-section analysis of the single tracks gave quantitative data that was used together with process parameters to relate between track geometry, dilution, deposition speed, and laser power. A novel wire-bending technique was developed that improved process stability and overall track quality. Finally, two 120 μm thin demonstration clads were manufactured, using two different wire materials by overlapping tracks. The results show the potential of LMWC for thin coatings especially on thin substrates, micro scale repair of components, or further development towards layer-by-layer laser metal wire deposition (LMWD) with high geometric resolution.

Downstream migration of salmonid smolts through regulated rivers remains a major ecological and engineering challenge, with high mortality and delay rates despite mitigation measures like bypasses and guidance systems. This study integrates Computational Fluid Dynamics (CFD) with fish telemetry to analyze how salmon smolts respond to local hydraulic conditions in a real riverine environment. By coupling detailed CFD flow models with two-dimensional smolt track data from a hydropower facility in northern Sweden, we identified behavioral tendencies linked to specific flow velocities. The analysis of fish movement patterns indicates a general tendency to follow the main current during migration, with occasional variations influenced by initial velocity and local flow conditions. This behaviorally informed CFD–telemetry approach provides a method for identifying behavioral patterns based on velocities and demonstrates its potential to improve fish passage models, supporting more ecologically effective hydropower design. This study highlights the need for broader datasets to fully capture smolt behavior and to develop standardized, transferable modeling frameworks for fish–flow interactions.

The rapid evolution of labor market demands, driven by technological and societal transformations, has intensified the need for higher education to foster future-oriented competencies. Frameworks such as Education 4.0 emphasize the development of abilities, skills, attitudes, and values; such as problem-solving, critical thinking, adaptability, and curiosity; alongside disciplinary knowledge. However, translating these competencies into course-level practice remains a challenge for educators, especially with regard to course materials and assessment methods. This study addresses this gap by proposing and evaluating a structured, instructor-led method for course redesign aligned with the Education 4.0 framework (E4CAM). Through an iterative research process involving literature reviews, expert workshops, and in-depth interviews, E4CAM integrates self-assessment checklists and targeted action guidelines to support competency integration. E4CAM was evaluated through two workshops and experimental applications involving university instructors. Results indicate E4CAM's practical relevance and adaptability across course levels and disciplines. By enabling instructors to systematically align course content and assessments with Education 4.0 competencies, the proposed approach offers a scalable tool for enhancing pedagogical practices and advancing competency-based education in higher education.

Since 1972, the Swedish preschool has undergone several policy reforms that state guidelines for the work in preschool where preschool teachers and caregivers work close together in work teams. Since 2010, preschool teachers have been given increased responsibility for preschool education and its pedagogical content, including lead teaching, which has been identified as a challenging and complex issue in preschool practice. This study analyzes how preschool policies have positioned preschool teachers over time and how this plays a role in making it possible for preschool teachers to take increased responsibility for preschool education. Building on positioning theory and using a qualitative research design with content analysis of seven policy documents over time, the results show that policy documents have positioned preschool teachers as invisible between 1972 and 2010 by downgrading their position and as visible from 2010 to the present by upgrading their position. The results indicate that policies either marginalize or empower preschool teachers, with insights into the broader implications of policy decisions. Policy plays a crucial role as a mechanism with the power to reshape responsibilities and redistribute power within preschools. It is essential to overcome policy ambiguities when responsibilities overlap between preschool teachers and the work team, which enables opportunities for contested positions in which preschool teachers and caregivers can reinterpret their roles and responsibilities. 

This paper presents the development and field testing of "Save the World," a gamified healthcare application aimed at promoting healthcare innovation among children aged 8–10 years. Developed within the SynAir-G project, the app combines gamification with healthcare to educate and monitor health, raising awareness about environmental health and sustainability challenges. Utilizing an iterative Living Lab (LL) methodology, the app was co-created with stakeholders including children, parents, teachers, healthcare professionals, and developers. Field-testing events in Sweden and Denmark evaluated the app’s usability, technical performance, inclusivity, and engagement, revealing significant improvements in user experience. The project emphasized ethical engagement, inclusive design, and robust data protection. The study highlights the effectiveness of LL methodologies in fostering user-centric healthcare innovation, demonstrating the potential of gamified approaches to create impact fuldigital tools for healthcare and education.

With the growing demand for raw materials, there is also an increased need in faster and more efficient processes of mineral exploration, especially locating possible materials to mine. Machine learning (ML) for supporting the labor-intensive and interpretive process of drill core logging becomes increasingly relevant to address these needs, since drill cores are the most direct and physically preserved record of subsurface geology available during mineral exploration. This paper reviews the current state of the art in ML-based drill core analysis, including its capabilities, limitations, and specific challenges related to generalization and practical deployment within geological workflows. The review focuses specifically on photographic images of drill core, which have been routinely used in mineral exploration for decades. This paper presents several major contributions: It offers a structured overview of current methods, organized around three key geological tasks, which are lithology prediction, geotechnical analysis, and mineralogical prediction. Additionally, it identifies potential research gaps and proposes directions for future work, concluding with an emphasis on advancing context-aware machine learning in drill core analysis through a human-in-the-loop approach.

Ore-distal hydrothermal alteration zones are commonly suggested as a source of metals to ore-forming fluids. The Bergslagen ore district, Sweden exhibits extensive ore-proximal and ore-distal alterations and has been used as a typical locality for establishing the hydrothermal leaching model for volcanogenic massive sulphide (VMS) deposits. The ore-distal alteration in the region has been reported as depleted in ore-forming metals but robust mass change evaluations are lacking. Defining least-altered reference compositions is a major hurdle in Bergslagen due to compositional variation in the stratigraphy, extensive alteration, and high-grade metamorphic overprint. This study presents mass balance calculations for Na- and Mg-altered rocks in the Hällefors area using a set of systematically defined least-altered samples. Results show systematic mobility of light rare earth elements (LREE, here La-Eu; e.g., 80% of the Ce is mobilised during alteration which equates to 60 µg/g Ce), but no mobility of base metals. Precursor rock compositions have conspicuously low base metal concentrations (median: Zn 10 µg/g, Pb 2.5 µg/g; n = 13) compared to other volcanic centres in Bergslagen. Major base metal deposits occur in areas where least-altered volcanic rocks have higher base metal concentrations (e.g., Garpenberg; median: Zn 31.50 µg/g; Pb 11.75 µg/g; n = 10). The REE contents in least-altered rocks are relatively elevated in areas that host REE mineralisation such as the Riddarhyttan area. The results indicate that regional differences in metal fertility of the volcanic host succession may be a primary control on the metal enrichments, including REEs, occurring in the ore deposits throughout Bergslagen.

Introduction: Psychological distress is of concern among university students worldwide, more so than in a comparable working population. The impostor phenomenon (IP) describes feelings of inadequacy often experienced by individuals struggling to internalize success despite evidence to the contrary. IP is prevalent among university students and has been identified as a significant factor in understanding psychological distress within this population. This study aimed to investigate the prevalence of IP and its association with perceived stress and anxiety in dental, law, medical, nursing and psychology university students.

Methods: A web-survey consisting of the Clance Impostor Phenomenon Scale (CIPS), the Perceived Stress Scale-4 (PSS-4), the Generalized Anxiety Disorder-2 (GAD-2), and sociodemographic questions were completed by 968 university students registered at a Swedish university during 2022 and 2023. The prevalence of IP, perceived stress, and anxiety was calculated. Pearson’s correlation coefficient and multiple linear regression were used to examine the relationship between the variables.

Results: 64.0% of the participants scored above the cut off value for experiencing IP (CIPS score ≥62). According to cut-off levels developed to categorize the intensity of IP experiences 8.4% of participants had low experiences of IP, 26.0% moderate, 42.6% frequent, and 23.0% intense experiences of IP. Of all participants, 91.6% had at least moderate experiences of IP and 65.6% had frequent to intense experiences of IP. Women scored significantly higher on CIPS than men. In contrast, neither attending semester nor age group significantly impacted CIPS scores. Finally, there was a moderate correlation between the levels of perceived stress and anxiety, respectively, and the IP scores.

Conclusion: This study suggests that the majority of dental, medical, nursing, psychology and law students experience severe IP. Moreover, this study provides valuable insights into the association of IP with perceived stress and anxiety. The results underscore the significance of exploring IP and its link to psychological distress, suggesting that interventions aimed at diminishing IP may play a crucial role in enhancing the well-being of university students.

Labyrinth seals are commonly used in space mechanisms to reduce evaporative losses of lubricant molecules and limit the transport of contaminants. Analytical models and numerical simulations for predicting mass flow through these seals typically assume smooth, idealized surfaces, neglecting the effects of realistic surface roughness. This study systematically investigates the impact of surface roughness on the transmission probability (TP) of oil molecules using Monte Carlo simulations under free molecular flow conditions. Key geometric and surface parameters including average roughness (Ra), corridor length, and seal width are varied to evaluate their influence on molecular transport. The results demonstrate that surface roughness significantly reduces TP and molecular flux, especially in narrow and elongated geometries. Furthermore, increasing surface roughness by an order of magnitude enables a reduction in channel length or an increase in gap width by approximately 35–40 % while maintaining equivalent transmission probability. Based on these findings, a correction model is proposed to improve prediction accuracy and is validated against experimentally measured oil evaporative losses. This work highlights the potential of controlled surface texturing as a design strategy to both enhance sealing effectiveness and enable geometric reductions for improved compactness and manufacturability.

Stope instability remains a persistent and hazardous challenge in underground mining, impacting safety, efficiency, and sustainability. Traditional stability assessment methods, while valuable, are often limited by site-specific calibration, simplifications, and adaptability issues in dynamic underground conditions. While machine learning shows potential for improved accuracy, a critical gap persists in understanding how geotechnical factors interact in practice. This study introduces a novel, practical machine learning framework (Scikit-Learn) to predict stope instability, and crucially, to quantify the nuanced, non-linear influence and interaction of critical geotechnical factors in a shallow gold mine. Comprehensive geotechnical investigation (observations, lab tests, rock mass classifications, blast damage assessments) and advanced data analysis (Random Forest feature importance, RFE, decision boundary analysis) identified water ingress, blast-induced damage, and rock mass quality (RMR) as the most significant instability factors. Water ingress profoundly impacted stability, with moderate blast damage exacerbating instability under high water ingress. Rock strength showed comparatively lower significance. The developed model achieved robust predictive performance (accuracy: 0.83, precision: 0.88, recall: 0.83, F1-score: 0.83). Based on these insights, tailored support patterns (e.g. 22mm/16mm cone bolts, timber props) are proposed to mitigate specific risks. This research significantly advances targeted rock mechanics solutions by providing a deeper, quantifiable understanding of complex instability mechanisms, enhancing mine safety and operational efficiency in shallow gold mining. 

The growing demand for coal in Zimbabwe’s industrial sector has necessitated the shift to underground mining as surface reserves become increasingly depleted. However, underground mining introduces substantial risks due to the formation of unstable voids, which, if not adequately supported by pillars, can result in catastrophic failures, such as the historic Coalbrook Colliery disaster. To mitigate these challenges, effective pillar design is critical for ensuring both ground stability and economic feasibility. This study adopts a multifaceted approach to balance operational safety with economic sustainability. Empirical design methods, including the Tributary Area Theorem and the Van der Merwe formula, were initially applied to determine appropriate pillar dimensions. These were further evaluated and refined through numerical modelling techniques using Phase2 software to enhance stability predictions. Key performance indicators, such as the safety factor and the economic extraction ratio, were analyzed to assess the design’s structural integrity and profitability. The results underscore the significance of optimized pillar configurations in reducing stress concentrations and preventing structural collapses. By integrating empirical and numerical techniques, this study presents a robust framework for the design of safe and cost-effective pillar systems in Zimbabwe’s underground coal mines. These findings contribute to safer mining practices while supporting the nation's increasing energy requirements.

Study develops and field-validates a SCADA-based real-time monitoring system to reduce unplanned dilution and hanging-wall over-break in underground long-hole stoping at a Zimbabwean gold mine. The objectives were to detect and constrain drilling deviation in real time, quantify the impact on stope stability and dilution, and evaluate operational and economic effects. The system integrates IMU inclinometers (hole angle), rotary encoders (depth), and LiDAR (collar spacing) with a Siemens S7 PLC (RS Americas, Fort Worth, TX, USA) and AVEVA™ InTouch HMI 2023 R2. Field trials across three production stopes (12L, 14L, 15L) compared baseline manual monitoring to SCADA control. Mean angular deviation fell from 0.8–1.6° to 0.2–0.3°, length deviation from 0.8–1.1 m to 0.05–0.08 m, and positional error from 0.25–0.32 m to 0.04–0.06 m; major collapses were eliminated, and ELOS dropped (e.g., 0.20 m to 0.05 m). Dilution decreased from 25% (typical 21–26%) to 16–18%, with mill feed grade rising from 1.90 to 2.25 g/t; production rates were maintained, with brief auto-stops in 5% of holes and rapid operator correction. Real-time drilling control materially reduces unplanned dilution and improves wall stability without productivity penalties, yielding compelling economics.

A search for a heavy pseudoscalar Higgs boson, A, decaying to a 125 GeV Higgs boson h and a Z boson is presented. The h boson is identified via its decay to a pair of tau leptons, while the Z boson is identified via its decay to a pair of electrons or muons. These arch targets the production of the A boson via the gluon-gluon fusion process, gg → A, and in association with bottom quarks, bb¯A. The analysis uses a data sample corresponding to an integrated luminosity of 138 fb−1 collected with the CMS detector at the CERN LHC in proton-proton collisions at a centre-of-mass energy of √s = 13 TeV. Constraints are set on the product of the cross sections of the A production mechanisms and the A → Zh decay branching fraction. The observed (expected) upper limit at 95% confidence level ranges from 0.049 (0.060) pb to 1.02 (0.79) pb for the gg → A process and from 0.053 (0.059) pb to 0.79 (0.61) pb for the bb¯A process in the probed range of the A boson mass, mA, from 225 GeV to 1 TeV. The results of the search are used to constrain parameters within the M125h,EFT benchmark scenario of the minimal supersymmetric extension of the standard model. Values of tan β below 2.2 are excluded in this scenario at 95% confidence level for all mA values in the range from 225 to 350 GeV.

A search for the rare decay 𝐷0→𝜇+⁢𝜇− is reported using proton-proton collision events at √𝑠 =13.6  TeV collected by the CMS detector in 2022–2023, corresponding to an integrated luminosity of 64.5  fb−1. This is the first analysis to use a newly developed inclusive dimuon trigger, expanding the scope of the CMS flavor physics program. The search uses 𝐷0 mesons obtained from 𝐷*+→𝐷0⁢𝜋+ decays. No significant excess is observed. A limit on the branching fraction of ℬ⁡(𝐷0→𝜇+⁢𝜇−)<2.4×10−9 at 95% confidence level is set. This is the most stringent upper limit set on any flavor changing neutral current decay in the charm sector.

Inclusive and differential cross sections for Higgs boson production in proton-proton collisions at a centre-of-mass energy of 13.6 TeV are measured using data collected with the CMS detector at the LHC in 2022, corresponding to an integrated luminosity of 34.7 fb−1. Events with the diphoton final state are selected, and the measured inclusive fiducial cross section is σfid = 74±11 (stat)+5−4(syst) fb, in agreement with the standard model prediction of 67.8 ± 3.8 fb. Differential cross sections are measured as functions of several observables: the Higgs boson transverse momentum and rapidity, the number of associated jets, and the transverse momentum of the leading jet in the event. Within the uncertainties, the differential cross sections agree with the standard model predictions.

A search for the production of a single top quark in association with invisible particles is performed using proton-proton collision data collected with the CMS detector at the LHC at  TeV, corresponding to an integrated luminosity of 138 fb−1. In this search, a flavor-changing neutral current produces a single top quark or antiquark and an invisible state nonresonantly. The invisible state consists of a hypothetical spin-1 particle acting as a new mediator and decaying to two spin-1/2 dark matter candidates. The analysis searches for events in which the top quark or antiquark decays hadronically. No significant excess of events compatible with that signature is observed. Exclusion limits at 95% confidence level are placed on the masses of the spin-1 mediator and the dark matter candidates, and are compared to constraints from the dark matter relic density measurements. In a vector (axial-vector) coupling scenario, masses of the spin-1 mediator are excluded up to 1.85 (1.85) TeV with an expectation of 2.0 (2.0) TeV, whereas masses of the dark matter candidates are excluded up to 0.75 (0.55) TeV with an expectation of 0.85 (0.65) TeV.

Hydropower plants in Sweden has a long history dating back to the early 20th century. In the design of these, now old facilities, expected probable flows were based on recorded precipitation data. As a safety valve of the dam various types of spillway can be installed, to either spill water when no power is produced. Or to regulate water levels above and below the dam to prevent or mitigate flooding, and to be able to prevent overtopping of a dam. As the climate is ever changing, and now average temperatures climb, this leads to an increase in both average annual precipitation and likelihood of expected flood events in Sweden. This leads to a case of old infrastructure designed for old conditions, which now may exceed flow discharge capabilities for safe operations. A need for reevaluation of the existing dam fleet is needed to explore if it can face the new conditions brought by increased precipitation. Previous work has been done by Computational Fluid Dynamics (CFD) to compare scale model data of existing dams, recorded when they were designed. Such comparisons show mostly low differences between the CFD simulations and scale model results, in the range of 1-2%. Some show as much as 10%. With CFD now being a standard tool in many industries involving fluid mechanics, there are several guidelines on how to perform CFD with respect to quality. However CFD is an approximate science and the physics needs to be simplified by a number of models with inherent limitations. Hence to gain trust in CFD simulations for dam operators there needs to be validation cases. Validation cases for single outlet spillway setup exist, but dams often do not have geometries as simple as the existing validation cases. Hence, a need for well defined experiments for CFD validation of hydraulic designs.

This thesis aims to provide experimental data suitable for use in evaluating CFD methods for assessing spillway capacity. To this endeavour a purpose built experimental setup was designed to produce experimental data of a quality and complexity not found elsewhere today. The main feature of the experiment is three outlets with the capability of recording the discharge passing through each outlet individually. Other tools used for evaluating flow conditions in the channel include Acoustic Doppler Velocimetry.

The results consists of experimental data gathered for three different variations of the experimental geometry. First a Deep channel flowing past a sharp corner, which produced low velocities in the channel leading up to the outlets. A second variation where the channel floor was raised to induce larger velocities in the flow leading up to the outlets, for increased differences in the flow distribution between the different outlets. As a final variation, the channel width was reduced leading to even higher velocities, and larger differences in both waterlevels at different points in the experimental channel, and in the discharge recorded in the different outlets. The distribution of the flow discharge across the outlets varies with the different geometries, and with the different inflows tested. At low flows differences in distribution between the outlets were negligible, especially with the first channel layout. At higher flows the differences grow, and show clear differences that should be replicable in simulations. Thus showing results that could be used for validation of CFD methods in regards to flow distribution across a spillway with multiple outlets. Additional data to use for validation include ADV data gathered in the channel leading up to the outlets, which documents recirculation zones introduced due to the geometries. As potentially simulations could produce flow distribution results that are correct while not simulating flow behaviour correctly.

A first search is presented for vector-like leptons (VLLs) exclusively decaying into a light long-lived pseudoscalar boson and a standard model τ lepton. The pseudoscalar boson is assumed to have a mass below the τ+τ− threshold, so that it decays exclusively into two photons. It is identified using the CMS muon system. The analysis is carried out using a data set of proton-proton collisions at a center-of-mass energy of 13 TeV collected by the CMS experiment in 2016–2018, corresponding to an integrated luminosity of 138 fb−1. Selected events contain at least one pseudoscalar boson decaying electromagnetically in the muon system and at least one hadronically decaying τ lepton. No significant excess of data events is observed compared to the background expectation. Upper limits are set at 95% confidence level on the vector-like lepton production cross section as a function of the VLL mass and the pseudoscalar boson mean proper decay length. The observed and expected exclusion ranges of the VLL mass extend up to 700 and 670 GeV, respectively, depending on the pseudoscalar boson lifetime.

The polarization of the Λ and ¯Λ hyperons along the beam direction has been measured in proton-lead (𝑝-Pb) collisions at a center-of-mass energy per nucleon pair of 8.16 TeV. The data were obtained with the CMS detector at the LHC and correspond to an integrated luminosity of 186.0±6.5  nb−1. A significant azimuthal dependence of the hyperon polarization, characterized by the second-order Fourier sine coefficient 𝑃𝑧,s⁢2, is observed. The 𝑃𝑧,s⁢2 values decrease as a function of charged particle multiplicity, but increase with transverse momentum. A hydrodynamic model that describes the observed 𝑃𝑧,s⁢2 values in nucleus-nucleus collisions by introducing vorticity effects does not reproduce either the sign or the magnitude of the 𝑝-Pb results. These observations pose a challenge to the current theoretical implementation of spin polarization in heavy ion collisions and offer new insights into the origin of spin polarization in hadronic collisions at LHC energies.

Design Neurocognition, a field bridging Design Research and Cognitive Neuroscience, offers new insights into the cognitive processes underlying creative ideation. This study adopts a micro-perspective on design ideation by examining convergent and divergent thinking as its core components. Using 32-channel EEG recordings, it investigates how educational background (Industrial Design Engineering vs. Engineering Design) influences designers’neural activity (alpha, beta, and gamma frequency bands), behavioral responses, and perceived stress during ideation tasks. Data from forty participants reveal a consistent and meaningful interaction between brain activity, behavior, and self-reported stress, highlighting that educational background significantly modulates cognitive and neural patterns during ideation. Importantly, perceived stress shows strong negative correlations with neural power across all frequency bands, suggesting a close alignment between subjective experience and physiological measures. By integrating neural, behavioral, and psychological data, this study advances the understanding of the neurocognitive mechanisms driving design ideation and establishes a methodological foundation for bridging Design and Cognitive Neuroscience. These findings contribute to building a unified evidence base for future human-centred and neuro-informed design research.

The Q-system is one of the broad techniques used in tunnel design and aids in the determination of tunnel support – a crucial aspect for safety and stability in tunnel engineering. It is complex, costly, and time-consuming to acquire all the necessary Q-system characteristics. This study predicts the Q value using parameters that have the largest coefficient of relevance in the value of Q and determines the most important Q-system parameters. The predictions of the models are correlated with the actual Q values using the marginal histograms for training, testing and validation of the datasets. The histogram of the ANN and GB models is closer to that of the measured Q for training, while the RF model is a bit different from the actual Q. The imposed normal distribution curves of the ANN and GB are also closer to that of the actual Q, while RF shows a much more curved cone. These observations account for the high R2 values of 0.9992 and 0.9998 obtained for the ANN and GB models for training, while an R2 of 0.9716 is observed for the RF model. The histograms of the ANN models are the closest resemblance to the actual histogram of Q, followed by those of the GB and then RF for testing and validation. The ANN models have the highest R2 values for the testing and validation of the dataset, which can be attributed to the closeness of their histograms to the actual Q. The ANN model performs better than the other ensemble models, demonstrating its superiority in predicting rockmass quality. The Taylor diagram displays the prediction efficacy of the three proposed models by using the testing and validation datasets, and confirms that the ANN predictive models are the closest to the actual Q values.

Polymer-composites are indispensable tribo-materials in a wide range of engineering applications, including gears, bearings, joint implants, and automotive components. In many of these applications the presence of liquid lubricant is unavoidable, requiring a thorough understanding of composite behaviour under lubricated conditions. However, with growing emphasis on environmental safety, the use of petroleum oil-based lubricants, especially near aqueous environments, such as ships, pumps and turbines, has become increasingly dubious. Estimates suggest that of the 30–40 million tonnes of lubricant used annually, around 55% may eventually re-enter the environment, with approximately 95% of these being petroleum-based. These systems contribute to emissions and resource depletion, driving interest in the development of lubricant technologies free from petroleum-derived products. Some potential replacements to them are acceptable alternate lubricants like esters and glycerol, or mere water, which is abundantly available and emission free. The tribological performance of polymer composites often differs between dry and lubricated conditions, as contribution from polymer and fillers are observed to vary across environments. While numerous studies have explored the role of various fillers in water lubricated conditions, limited knowledge is available on other alternate lubricants. More recently, the focus on polymer-composite side has shifted towards multi-filler systems, which, when working synergistically, can provide superior performance compared to having a single filler. However, the existing literature lacks clarity on several key aspects: including the individual roles of filler material and scale; the nature and effect of filler–filler and filler–lubricant interactions to overall performance. This thesis investigates these gaps and provides deeper insights into the mechanisms governing the lubricated tribological behaviour of multi-filler polymer composites.

Incoherent 𝐽/𝜓 photoproduction in heavy ion ultraperipheral collisions (UPCs) provides a sensitive probe of localized, fluctuating gluonic structures within heavy nuclei. This Letter reports the first measurement of the photon-nucleon center-of-mass energy (𝑊𝛾⁢N) dependence of this process in PbPb UPCs at a nucleon-nucleon center-of-mass energy of 5.02 TeV, using 1.52  nb−1 of data recorded by the CMS experiment. The measurement covers a wide 𝑊𝛾⁢N range of ≈40–400  GeV, probing gluons carrying a fraction 𝑥 of nucleon momentum down to an unexplored regime of 6.5 ×10−5. Compared to baseline predictions neglecting nuclear effects, the measured cross sections exhibit significantly greater suppression at lower 𝑥. Additionally, the ratio of incoherent to coherent photoproduction is found to be constant across the probed 𝑊𝛾⁢N and 𝑥 range, disfavoring the establishment of the black disk limit. This Letter provides critical insights into the 𝑥-dependent evolution of fluctuating gluonic structures within nuclei and calls for further advancements in theoretical models incorporating nuclear shadowing and gluon saturation.

In cold climate regions, seasonal snow accumulation in road ditches plays a critical role in governing the thermal behavior of road embankments. Snow exerts a spatially uneven thermal influence on heat transfer within the embankment due to its strong insulating properties, which can lead to differential frost heave and the formation of cracks on the road surface. However, accurately quantifying this insulation effect requires detailed knowledge of the thermal regime of the snow cover accumulated in the ditches, including its temporal evolution throughout the winter season.

Snow is a porous medium characterized by a high volume fraction of air, which significantly reduces the thermal conductivity of snow and provides a strong insulating capacity. This insulation creates a natural temperature gradient between the snow surface and its base, governing the rate of heat transfer through the snow. Once snow is deposited, a temperature gradient develops, initiating metamorphic processes that alter the morphology and bonding of the snow grains. These microstructural changes lead to temporal variations in the thermal conductivity of snow, making its accurate determination over time particularly challenging. Furthermore, freezing-melting cycles modify the content of unfrozen liquid water within the snow structure, which not only complicates the quantification of latent heat exchanges but also exerts a significant influence on the effective thermal conductivity.

To address these challenges and gain a deeper understanding of the thermal dynamics in snow-covered road embankments, two experimental field sites were established in Luleå, Sweden. The first site, located on the premises of the Luleå University of Technology, was designed to investigate the thermal regime of a natural undisturbed snow cover and its impact on temperatures at the soil–snow interface, as well as within the shallow subsurface soil layer. The second site was located in a road ditch near Luleå Airport, where the snow cover consisted of a mixture of naturally accumulated snow and plowed snow from the adjacent road. The purpose of this site was to investigate the thermal regime of the snow cover in the ditch and its influence on the thermal conditions of the road embankment. The objective was to investigate the thermal regime of both the snow cover in the ditch and the road embankment influenced by snow accumulation during the winter season.

At both sites, the thermal regime of the accumulated snow was continuously monitored by measuring the snow temperature at different heights throughout the winter season. Meteorological conditions were also recorded using a weather station installed at each site. At the site with natural snow accumulation, the thermal influence of snow cover on subsurface soil was measured down to a depth of 40 cm. In contrast, at the experimental site in the road ditch, the thermal regime of the entire road embankment was investigated. To provide a comprehensive overview, the temperature distribution was measured from the road surface to a depth of 2 m, as well as from the surface of the ditch to the same depth.

Analysis of the thermal regimes of snow cover at each experimental site reveals that the natural undisturbed snow cover possesses a greater insulating capacity compared to snow cover accumulated in ditches, due to differences in metamorphic processes. The metamorphism of each type of snow cover is influenced by factors such as history of deposition and environmental conditions.

To assess the insulating behavior of the snow in the ditch, the thermal conductivity of the snow cover at different heights was evaluated over time. Since manual measurements are restricted to discrete points, estimation of the thermal conductivity of snow over a period enables the consideration of continuous changes in the properties of snow driven by metamorphism. To achieve a realistic estimate, a mathematical approach was applied to analyze heat transfer processes within the snow cover based on field measurements. For depths where melting occurred, a novel method was developed to estimate the unfrozen water content of the snow, a parameter that is otherwise very difficult to measure or determine. Based on the analysis, an empirical relation was proposed to estimate the thermal conductivity of snow in the ditch, which is practically useful under similar climatic conditions. However, it was not possible to derive an empirical formula for the unfrozen water content, since the snow undergoes different metamorphic processes at different depths, resulting in highly variable behavior.

Furthermore, the thermal regime of the road embankment during the winter season was assessed using a one-dimensional finite-difference model validated against field measurements. In this model, a new approach was introduced to account for cloud cover in calculating incoming long-wave radiation, which plays a key role in the energy balance of the road surface and strongly affects the surface temperature. The influence of traffic was also incorporated by deriving a representative daily traffic load based on measurements collected over a two-week period. In general, the model improved the estimation of the road surface temperature and provided a more accurate assessment of the thermal regime of the road embankment.

The findings of this study improve the understanding of the thermal regime of road embankments in typical cold-climate regions with significant snow precipitation. Incorporating the thermal behavior of snow in design and maintenance strategies offers critical guidance for implementing measures that mitigate freezing-induced damage and improve the long-term durability of embankments. Furthermore, understanding the thermal influence of snow cover in road ditches can support the development of targeted snow management strategies to optimize its insulating effect. Such strategies may include the complete or partial removal of snow from the ditch or densification of the snowpack to modify its thermal impact on the road embankment. These measures can help improve the long-term performance of the embankment.

Ground thermal regime in cold regions is influenced by seasonal snow cover, which acts as an insulating layer influencing the heat transfer between the atmosphere and the underlying soil. The thermal properties of the snow change with different environmental conditions, playing a crucial role to determine the thermal state of the sub-surface soil. Previous research in this field have faced challenges to accurately characterize thermal properties of seasonal snowpacks under varying spatial and meteorological conditions. To address this issue, two experimental field setups were constructed in Luleå, Sweden, to observe the temperature distribution of the snowpack and the ground sub-surface soil. The first experiment studied a naturally accumulated, undisturbed snowpack. The second experiment was conducted on a roadside ditch where the snowpack consists of a combination of natural accumulated snow and plowed snow from the adjacent road. In this research, heat transfer processes at both field sites were monitored over a winter season each to better understand the complex relationship between snow cover properties and sub-surface thermal regime. Furthermore, thermal conductivity of a basal layer in each snowpack was calculated over a time period, based on the field measurements. The results showed that the history of snow deposition, meteorological conditions, and changes in soil moisture impact the metamorphism process within the snowpack, thereby altering the structure of the layers of snowpack and its influence on the thermal regime of the sub-surface soil. The findings of this research have important applications in various sectors, from mining to road maintenance and agriculture.

Amine-based deep eutectic solvents (DESs) are promising alternatives to conventional amines for CO2 capture; however, the molecular design principle to achieve practical performance remains unclear. In response to this challenge, this licentiate thesis aims to develop DES-based solvents that achieve balanced performance in 30 wt% aqueous solutions, including high absorption capacity, efficient desorption, good thermal stability, and manageable viscosity, with ethanolamine (MEA) used as the reference. 

In the first part of this work, ethylenediamine (EDA) and diethylenetriamine (DETA) were selected as hydrogen-bond donors (HBD), while a series of hydrogen-bond acceptors (HBAs) were varied to evaluate their effects on CO2 absorption and desorption behaviors. The solvents were evaluated for absorption capacity and absorption rate at 22 °C and 1 bar, for desorption and cyclic loading at 110 °C, and for thermal stability using thermogravimetric (TG) and derivative thermogravimetric (DTG). From this side-by-side comparison, 30 wt% aqueous [TrizCl][DETA] was identified as the most practical candidate. It achieves a CO2 absorption capacity of 0.164 g-CO2/g-solvent and an absorption rate of 0.183 g-CO2/(g-solvent·min), provides the largest cyclic loading of 0.091 g-CO2/g-solvent, and exhibits an onset decomposition temperature (Tonset) of approximately 178.7 °C. Although EDA-based DESs demonstrate the highest capacity and rapid absorption, for example, a 30 wt% aqueous [N-1,2,4-TrizCl][EDA] solution reaches 0.203 g-CO2/g-solvent, they exhibit limited thermal stability.

Building on these findings, the second part of the study focused on structure-property relationships by fixing [TrizCl] as the HBA and varying the amine-based HBDs, including diamines, triamines, and alkanolamines. The comparison revealed that the balanced performance of [TrizCl][DETA] arises from the optimal combination of the triazolium-based HBA and the triamine HBD, which provides sufficient basicity and hydrogen-bonding capacity for CO2 activation. 

Additionally, [TrizCl][DETA] maintains workable viscosity after CO2 absorption at about 7.5 mPa·s, and exhibits stable absorption-desorption behaviors. Corrosion, oxidative degradation, and mechanistic analyses confirm its stability and explain the rise of moderate viscosity via carbamate and bicarbonate formation, indicating strong potential for CO2 capture and solvent recycling.