https://www.mdu.se/

Classical Ewald methods for Coulomb and Stokes interactions rely on “kernel-splitting,” using decompositions based on Gaussians to divide the resulting potential into a near field and a far field component. Here, we show that a more efficient splitting for the scalar biharmonic Green’s function can be derived using zeroth-order prolate spheroidal wave functions (PSWFs), which in turn yields new efficient splittings for the Stokeslet, stresslet, and elastic kernels, since these Green’s tensors can all be derived from the biharmonic kernel. This benefits all fast summation methods based on kernel splitting, including FFT-based Ewald summation methods, that are suitable for uniform point distributions, and DMK-based methods that allow for nonuniform point distributions. The DMK (dual-space multilevel kernel-splitting) algorithm we develop here is fast, adaptive, and linear-scaling, both in free space and in a periodic cube. We demonstrate its performance with numerical examples in two and three dimensions.

Enligt kursplanen ska undervisningen i svenska för invandrare (sfi) individanpassas och planeras utifrån elevens intressen samt tidigare erfarenheter och kunskaper (Skolverket, 2022a), vilket även innefattar tidigare erfarenheter av litteracitet samt av användning av digitala verktyg (Skolverket, 2022b). Digital kompetens har visat sig hjälpa de vuxnas integrering på arbetsmarknaden och en kartläggning är viktig ur ett likvärdighetsperspektiv då vuxenutbildningen har ett kompensatoriskt uppdrag (Basaran, 2020). Skolinspektionen (2023) har dock i upprepade granskningar påtalat brister i sfi-undervisningens individanpassning vilket motiverar föreliggande studie om hur lärare ser på kartläggning av digital litteracitet, samt vilka digitala litteracitetspraktiker i olika domäner som framkommer vid några kartläggningar. Insamlade data består av enkätsvar från 52 sfi lärare samt tre sammanfattningar av kartläggningar gjorda av sfi-lärare. En tematisk analys av enkäterna visar att lärarna har olika uppfattningar om betydelsen av denna bakgrundsinformation om eleven för planering av deras undervisning där såväl en bredare ideologisk syn på litteracitet, som en snävare autonom syn på digital litteracitet som en i huvudsak teknisk färdighet (Street, 1984) representeras. I dokumentanalysen av sammanfattningar av kartläggningar framkommer erfarenheter av digitala litteracitetspraktiker i olika domäner och genom olika digitala verktyg från datorskrivande i yrkes- och utbildningssammanhang till sms:ande och användning av appar i vardagssammanhang.

It has been recognized that schools play a key role in promoting well-being and preventing mental health problems among children and adolescents. The local context is crucial for realizing the school’s health-promotive potential. This study aimed to explore how the role of schools is approached in Swedish municipal policy documents governing mental health efforts. A qualitative document analysis using the READ approach was conducted. Seventy-three municipalities were selected and asked to provide policy documents on mental health; twelve policy documents met the inclusion criteria and were analyzed using conventional content analysis. The analysis identified the school as a central actor across the documents. Four categories were constructed: (i) the school as a context influencing mental health, (ii) the school as a platform for reaching all children and adolescents with mental health interventions, (iii) the school as responsible for detecting mental health problems, and (iv) the school as a collaborating partner in mental health efforts. The analysis highlighted a primarily individualized and often medicalized understanding of mental health problems, positioning health professionals as key actors. Although the school’s role as a context influencing mental health was clearly acknowledged, teachers, pedagogical support and social relationships were overlooked in relation to this role. The school’s role in mental health efforts was thus largely detached from its educational mission. Finally, there was substantial variation in the activities expected of schools across municipalities. Hence, despite schools’ recognized importance, their role in mental health efforts was subject to local interpretation of national policy within a decentralized school system.

Growing crops under agrivoltaic (AV) systems often exposes them to a modified microclimate, which can affect yield and quality. A field experiment was carried out in 2025 on oat ( Avena sativa L.) grown within a vertical AV system near Fellingsbro, Sweden. The aim of this study was to assess the growth and yield performance of oat relative to open-field reference conditions. The dataset allows analysis of oat growth by exploiting photosynthetic rate and leaf area index measurements, as well as yield performance at harvest, estimated as total biomass yield (kernel and straw combined). It also aims to explain the impact of vertical AV systems on oat photosynthetic rate, considering different positions within the system with varying shading patterns and sun exposure, and their impact on overall oat yield. These data provide insights into oat growth and yield under vertical AV systems and facilitate further analyses or comparisons across locations or AV system designs. Additionally, the dataset can support the development and validation of crop models under similar conditions and encourage collaborations to promote experimental studies on AV systems.

Background: Low-value care (LVC) remains a persistent problem in primary healthcare. While various implementation strategies have been proposed and tested for deimplementation, there is limited knowledge about whether there are strategies uniquely suited to deimplementation. Furthermore, there is limited knowledge about system-level responsibilities for deimplementation. Given that implementation strategies are recommended to be tailored to the specific contextual factors surrounding LVC practices, involving primary care physicians in identifying contextually appropriate strategies holds promise. This study aimed to explore the strategies that primary care physicians suggest could facilitate the deimplementation of LVC and map them to the system levels responsible for initiating and deploying these strategies. Methods: This qualitative study was based on responses to an open-ended survey question asking physicians to suggest strategies that could facilitate the deimplementation of LVC practices within primary healthcare in Sweden. A national sample of 441 primary care physicians responded. Responses were analyzed via deductive content analysis categorized by the Expert Recommendations for Implementing Change (ERIC) compilation. Responses that could not be categorized via ERIC were analyzed inductively. The identified strategies were then mapped to the system levels (individual, group, leader, organization and overarching system) responsible for deploying these strategies. Results: Strategies were identified across all nine original ERIC domains, representing 39 (53%) of the original ERIC strategies, and later additions for deimplementation. Additionally, a set of strategies categorized under a new domain, develop better evidence, was identified. Most strategies were suitable for deployment at the organizational (31 strategies) and overarching (31 strategies) levels. Sixteen strategies were best suited for the group level, thirteen for the leadership level, and two for the individual level. Conclusion: Primary care physicians proposed strategies across all nine ERIC domains, with additional strategies beyond those previously described, including develop better evidence. From the physicians’ perspective, deimplementation cannot rely solely on individuals but requires coordinated action across the organizational and system levels. Broader structural, policy, and cultural changes would support physicians and ensure that responsibility for deimplementation is shared across the healthcare system.

In the early 2020s, the Swedish child welfare services (CWS) were accused in social media of kidnapping and placing migrant children in foster or family care, without their families’ knowledge or permission. This debate became referred to as a large-scale disinformation campaign, which can be understood as a discursive struggle between different versions of truth. This study explores social media content about the Swedish CWS in Arabic between 2021 and 2023. The material consisted of Facebook and YouTube posts and comments in Arabic. The analysis departed from the narrative genre of shared stories, and focused on claims about the CWS and how such claims are made credible. The findings show three types of claims within the shared story of ‘the CWS kidnapping migrant children’: families are victims of CWS’ malpractice; affected children suffer; and migrant families fear the CWS. These claims are made legitimate and credible by constructing the teller as an expert using time, place, and details while constructing the testimonies to invoke an emotional response. In conclusion, this study highlights how social reality is constructed and negotiated on social media, where migrant families’ testimonies of wrongdoings and fear become intertwined with larger stories of good and bad, truth or falsehood. It is therefore essential that claims made online is treated as signals of perceived vulnerability and institutional distance, rather than as “falsehoods” to be corrected, while CWS’ procedures and legal thresholds are clearly conveyed.

Artificial Intelligence (AI) is widely used in Industry 4.0 and Industry 5.0 applications for anomaly detection and predictive analytics. However, the opaque decision-making of most Machine Learning (ML) models limits interpretability and hinders effective decision-making and root cause analysis. Explainable AI (XAI) seeks to address these challenges; however, the combined processes of anomaly detection and explanation generation often require substantial domain expertise, limiting their accessibility to a broader audience. To address this gap, this paper presents EXACT (EXplainable Anomaly Classification Tool), a novel, modular software framework that enables practitioners and researchers to rapidly and easily perform explainable anomaly detection on time-series data, regardless of domain expertise. EXACT integrates time-series anomaly detection with XAI techniques into a single end-to-end workflow, including data handling, anomaly injection, parameter tuning, model training, anomaly detection, explanation generation, and visualization, making these features broadly accessible and user-friendly to the wider community. The effectiveness of EXACT is demonstrated through rigorous evaluations conducted on three public time-series datasets from distinct domains, using three anomaly detection models and three widely adopted XAI methods. Among these, XGBoost exhibits the most balanced predictive performance, achieving 99.96% accuracy, 82.61% F1-score, and 98.59% ROC-AUC on the Credit Card Fraud dataset, while Decision Trees demonstrate significantly lower training times. In terms of explainability, SHAP consistently delivers high-quality feature rankings, reaching an NDCG score of 0.98 on the Credit Card Fraud dataset, whereas LIME provides substantially faster explanation generation. These results demonstrate that EXACT effectively facilitates explainable anomaly detection in an efficient, user-friendly manner, while also providing a systematic analysis of trade-offs among predictive performance, interpretability, and computational efficiency. EXACT is publicly available at GitHub (https://github.com/TedBoman/EXACT), and the community is invited to contribute to its continued development and extension.

District heating (DH) systems in Sweden are facing growing challenges due to rising biomass prices and uncertainty surrounding future supply availability. Integrating solar thermal collectors with pit thermal energy storage (PTES) offers a promising pathway for reducing dependence on biomass and improving system sustainability. However, the optimal integration and techno-economic performance of such systems under real-world limitations (such as spatial and hydraulic constraints) remain largely underexplored. This study develops a two-stage modeling framework to evaluate solar + PTES integration while accounting for practical constraints such as sitting feasibility and discharge power limitations. A Python-based simplified model first generates a sensitivity matrix mapping heat delivery performance across a wide range of collector areas and storage volumes, which guides the selection of PTES sizes for subsequent detailed modelling in TRNSYS. Three system configurations are analysed: a real-world case with waste heat and pipe limitations, a generalized case without waste heat but with pipe constraints, and an ideal case without any integration barriers. Monte Carlo simulations and sensitivity analyses are performed to quantify economic uncertainties and identify key influencing factors. Results show that discharge power limitations and pipe constraints significantly penalise the system performance, leading to higher levelized costs of heat (LCOH) compared with the ideal benchmark. The findings highlight the necessity of simultaneous consideration of spatial and techno-economic constraints to achieve cost-effective solar fractions and optimal storage design in real-world DH systems. 

Syfte: Att beskriva kvinnors erfarenheter av medicinsk abort i första trimestern. Metod: Kvalitativ intervjuundersökning med semi-strukturerade intervjuer, där tio kvinnor intervjuades. Data analyserades med kvalitativ innehållsanalys enligt Graneheim och Lundman. Resultat: Beslutsprocessen var en utmanande process även om det var rätt beslut baserat på kvinnornas enskilda faktorer. Graviditeten kom ibland opassande i relation till livet vilket var en framträdande faktor till att genomgå abort. Stöd från närstående var viktigt, där även barnmorskans bemötande framkom som betydelsefull. Processen kändes negativ när det inte förelåg stöd från närstående eller vårdpersonal. Information inför abortprocessen varierade, där de flesta erfarenheter talade för en önskan om tydligare och mer information kring processen samt mer personcentrerad preventivmedelsrådgivning. Variation i de fysiska erfarenheterna framkom också, där stark smärta var framträdande. De fysiska och psykiska begränsningarna i vardagen varierade, där de psykiska kändes som det största hindret. Slutsats: Stöd från närstående och vårdpersonal under abort är en viktig aspekt för att underlätta abortprocessen. I kombination med tydlig information kring fysiska och psykiska upplevelser finns det förbättringspotential för att möjliggöra en trygg och positiv abortupplevelse för kvinnorna. Samt möjlighet att göra vården mer individanpassad vilket kan bidra till att bättre möta kvinnors individuella behov.

Purpose: This study aims to understand the potential and challenges of incorporating low-cost automation (LCA) in the adoption of the Internet of Things (IoT) within the context of Industry 4.0 implementation and how it influences factory employee empowerment.

Design/methodology/approach: Multiple case studies were conducted with industrial companies located in Sweden. Relevant empirical evidence was collected from the workshops where factory employees explored and prototyped simple IoT solutions to improve their work environments.

Findings: The study revealed multiple benefits of LCA incorporation, including enhancing factory employees' knowledge, skills, and motivation for improvement. The compatibility of LCA with Lean production was also found to be positive for the employees. However, the study also identified several challenges, mainly concerning preparing organisational preconditions that enable or facilitate the incorporation, such as its strategic alignment and securing managers' understanding and support. The study found a tension between simple IoT solutions and large integrated solutions in terms of empowerment. Managing the tension was found particularly challenging.

Originality/value: This paper provides a more comprehensive understanding of the potential and limitations of incorporating LCA into IoT adoption than previous studies. It highlights the potential of a bottom-up approach to IoT adoption which is currently predominated by top-down, engineering-driven approaches.