Publikationer från Linköpings universitet
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Fluid-structure interaction topology optimization using density jumps for implicit boundary representation
No full textWe propose a new density-based topology optimization method for applications where fluid-structure interaction (FSI) plays a significant role. The method utilizes the jump in density between neighboring finite elements to implicitly track the FSI boundary and the FSI load. A pressure penalty term is introduced into the Navier-Stokes equations to mitigate the formation of internal pressurized holes, providing a more accurate representation of the physics and enhancing manufacturability. The method is implemented using a parallelized computational framework that enables efficient optimization of large-scale 3D problems. High-resolution discretization, combined with filtering techniques, minimizes intermediate densities and achieves detailed, binary structures that accurately model the FSI load. This is then exemplified using a classic FSI benchmark (the wall problem) with different objective functions and constraints. A relevant engineering example is then shown, maximizing fluid performance with a mechanical constraint. The approach demonstrates good convergence and provides conceptually robust designs with potential for further refinement.Funding Agencies|Linkoping University; Swedish Research Council [2019-0461, 2022-06725]</p
Reproducibility of published model-based cancer drug cost-effectiveness analyses: a study protocol for a cross-sectional analysis
No full textIntroduction Model-based cost-effectiveness analysis (CEA) of pharmaceuticals informs reimbursement and pricing in many healthcare systems, and it is essential that CEA evidence is valid and reliable. Several studies have reported lacking transparency in CEA studies. In this study protocol, we describe a study that will investigate whether model-based CEA studies of cancer drugs are transparent and informative enough to enable the reproduction of study findings. Methods and analysis This study protocol outlines a study where we will identify CEA studies indexed in MEDLINE from 2015 to 2023 based on predefined search terms. We will include English-language CEA studies evaluating pharmaceutical treatments based on decision-analytical modelling methods that report cost-effectiveness results using life-years, quality-adjusted life-years and/or disability-adjusted life-years as health outcome metric(s). Two authors will screen abstracts and full text for inclusion. We anticipate that a maximum of 150 studies will be included after a full-text review. A data extraction template is designed to capture information used to determine reproducibility together with other information that will be analysed as potential determinants of reproducibility in logistic and linear regression analyses. Ethics and dissemination This study design has been deemed exempt from ethical approval. All collected data will be made available in an online repository that will host the study protocol and other supplementary data. Results from this proposed study will be published in peer-reviewed journals and at scientific conferences and workshops.Funding Agencies|Swedish Research Council for Health, Working Life and Welfare (Forte) [2023-00275]; Vinnova [2023-00275] Funding Source: Vinnova; Swedish Research Council [2023-00275] Funding Source: Swedish Research Council; Forte [2023-00275] Funding Source: Forte</p
Experiences of Eldercare Staff Working With Older People With Severe Mental Illness
No full textIn Sweden, older persons living with severe mental illnesses (SMI) increasingly live independently in the community with support from informal and formal carers and welfare services. A proportion of this group is older people with SMI who, due to age or disability, receive municipal eldercare services such as home care in their ordinary housing, or in residential care. The situation and needs of this group demand that eldercare staff have an understanding for the older person’s situation and the tools to provide appropriate care. The aim of this present study is to explore the experiences of eldercare staff working with older people with SMI. Focus group interviews were conducted with staff from three residential care facilities and two home care teams in one mid-sized Swedish municipality. To analyse the interviews, qualitative content analysis was used. The overarching theme from the analysis was “Doing the best they can,” which was unpacked in two categories: “Working with fragmentary knowledge” and “Finding the right approach.” We could also see differences between the experiences of staff in residential care and in home care. The eldercare staff in our interviews faced lack of formal training, insufficient information and skills concerning mental illness and its treatment. Nevertheless, they tried to make the situation of the older people with SMI as good as possible using experiential and tacit knowledge. Our results also point to system level barriers that hinder effective care for older people with SMI
Koppla samman mesoskaliga molnmönster och meteorologi med hjälp av maskininlärningstekniker
No full textClimate model projections of future climate scenarios play a critical role in informing decision making and policy contexts. This study focuses primarily on marine low-level mesoscale clouds, which are poorly represented in Earth System Models (ESMs). Using machine learning tools, couplings between cloud properties and the prevailing meteorological conditions could be found. Several artificial neural networks were implemented and analyzed to solve this problem. The results show that the predictive performance of machine learning models is affected by many things, such as the data used, configuration, and computational resources. In addition, comparative and factor analysis provides the foundation to build further models that can be used to help ESMs better represent mesorscale cloudsProjektioner av klimatmodeller av framtida klimat scenarier spelar en avgörande roll för att informera beslutsfattande och policy sammanhang. Denna studie fokuserar främst på marina låg-nivå mesoskaliga moln, vilka är dåligt representerade i Earth System Models (ESM:er). Genom att använda maskininlärning kunde kopplingar mellan molnegenskaper och rådande meteorologiska förhållanden identifieras. Flera artificiella neurala nätverk implementerades och analyserades för att lösa detta problem. Resultaten visar att prestandan hos maskininlärningsmodeller påverkas av många faktorer, såsom vilken typ av data som används, konfigurationen och tillgängliga resurser. Dessutom utgör jämförande och faktoranalys grunden för att bygga vidare modeller som kan användas för att hjälpa ESM:er att bättre representera mesoskaliga moln
Joint waking activity in early childhood education as a collaborative configuration of care
No full textAlthough sleeping and waking are everyday activities and inherent parts of being human, they are rarely considered social, collaborative, or educational. In this study, we explore practices of waking young children up in institutional interaction. Taking a cultural-historical approach and using a video-observation method, we investigated how young children (1-5 years old) and adults participate in joint waking activity after nap time in early childhood education. We asked how joint waking activity creates learning opportunities for children to collaborate as valuable members of the early childhood education community. Our results show that waking activity creates opportunities for children to learn to care for each other and to become sensitive to other children's needs. Waking moments that involve encountering sleeping and just-awakened members of the community invite caring responses from co-participant children and create collaborative configurations of care. We discuss how our concept, collaborative configuration of care, offers cultural-historical theory new insights into everyday guiding and learning
Prediction of Sulfur Dioxide Emissions in China Using Novel CSLDDBO-Optimized PGM(1, N) Model
No full textSulfur dioxide not only affects the ecological environment and endangers health but also restricts economic development. The reasonable prediction of sulfur dioxide emissions is beneficial for formulating more comprehensive energy use strategies and guiding social policies. To this end, this article uses a multiparameter combination optimization gray prediction model (PGM(1, N)), which not only defines the difference between the sequences represented by variables but also optimizes the order of all variables. To this end, this article proposes an improved algorithm for the Dung Beetle Optimization (DBO) algorithm, namely, CSLDDBO, to optimize two important parameters in the model, namely, the smoothing generation coefficient and the order of the gray generation operators. In order to overcome the shortcomings of DBO, four improvement strategies have been introduced. Firstly, the use of a chain foraging strategy is introduced to guide the ball-rolling beetle to update its position. Secondly, the rolling foraging strategy is adopted to fully conduct adaptive searches in the search space. Then, learning strategies are adopted to improve the global search capabilities. Finally, based on the idea of differential evolution, the convergence speed of the algorithm was improved, and the ability to escape from local optima was enhanced. The superiority of CSLDDBO was verified on the CEC2022 test set. Finally, the optimized PGM(1, N) model was used to predict China's sulfur dioxide emissions. From the results, it can be seen that the error of the PGM(1, N) model is the smallest at 0.1117%, and the prediction accuracy is significantly higher than that of other prediction models.Funding Agencies|National Natural Science Foundation of China; [52375264]</p
No major changes in injury incidence in European club football during the 2022/23 FIFA World Cup season: a subanalysis of the UEFA Elite Club Injury Study
No full textObjectives To compare injury incidences between the 2022/23 season and the preceding five seasons, and between World Cup players and non-World Cup players during the 2022/23 season.Methods During the 2022/23 season, 29 teams participated in the Union of European Football Associations Elite Club Injury Study and reported football exposures and injuries prospectively. Injury incidence was compared with that of the five preceding seasons for the full season and for periods before and after the F & eacute;d & eacute;ration Internationale de Football Association World Cup 2022. In addition, World Cup players were compared with non-World Cup players. Incidences were compared using rate ratio (RR) with 95% CI.Results Injury incidences during the 2022/23 season were similar to previous seasons except for training incidence which, due to a significantly lower incidence in the 2017/18 season compared with all other seasons, was higher during the full season (RR 1.10, 95% CI 1.00 to 1.21) and in the period before the World Cup (RR 1.17, 95% CI 1.02 to 1.35). World Cup players had similar injury incidences before and after the tournament (training incidence; RR 0.95, 95% CI 0.65 to 1.38, match incidence; RR 1.15, 95% CI 0.87 to 1.52) but a significantly lower match incidence than non-World Cup players before the tournament (RR 0.84, 95% CI 0.71 to 1.00).Conclusions No major changes in injury incidences were observed during the 2022/23 season compared with previous seasons. World Cup players experienced similar injury incidences before and after the tournament, and had a lower match injury incidence before the tournament compared with non-World Cup players.Funding Agencies|Union of European Football Associations (UEFA)</p
Electrochemical Deoxygenation Electrolyzers Using an Organic Catalyst
No full textAn efficient oxygen reduction reaction (ORR) is crucial for deoxygenation electrolyzers. However, the use of metal catalysts in electrolyzer designs is challenging due to their high cost, catalyst dissolution, and susceptibility to poisoning. Conductive polymers have emerged as a promising new class of metal-free catalysts for ORR, combining electron conductivity and a lack of an insulating oxidation layer. In this study, a new n-type polymer is explored, poly(benzimidazobenzophenanthroline) (BBL), as an ORR catalyst to enhance deoxygenation efficiency in carbon-based electrolyzers. Electrocatalytic studies show that BBL film improves ORR kinetics via a four-electron pathway with a mass activity of the order of 100 A g-1. A low-voltage electrolyzer is constructed and tested using BBL-coated carbon fiber paper (CFP) as the cathode for ORR and CFP as the anode to drive the oxidation of catechol as a compensating faradaic reaction to facilitate ORR. The deoxygenation electrolyzer with a drop-cast BBL cathode achieves fast deoxygenation kinetics, reaching below 0.1 mg L-1 DO in salty solution with 0.001 m catechol. The findings introduce a new approach to deoxygenating thermal fluids by employing an ORR polymer catalyst and a compensating redox additive (RA) in water.Funding Agencies|Knut och Alice Wallenbergs Stiftelse</p
Self-limiting deposition of copper from copper beta-diketonates and plasma electrons
No full textWe studied deposition of copper films by a pulsed electron chemical vapor deposition process using free electrons from a plasma discharge as reducing agents, with copper beta-diketonates, Cu(hfac)(2), and Cu(acac)(2) as the copper source. The mass gain per deposition cycle, as monitored by a quartz crystal microbalance sensor, suggests that pulsing allows us to access a process window with a self-limiting deposition process. X-ray photoelectron spectroscopy shows that the films are not metallic copper and that they are contaminated by carbon, oxygen, and when Cu(hfac)(2) was used, also fluorine. We speculate that the surface chemistry involves electron stimulated desorption reactions. Optical emission spectroscopy suggests redeposition of precursor fragments from plasma volume decomposition of precursor molecules desorbing during the plasma step. This redeposition limits the control of the surface chemistry during the plasma step of the deposition cycle.aFunding Agencies|Wallenberg Initiative Materials Science for Sustainability (WISE) - Knut and Alice Wallenberg Foundation [2019-05055]; Swedish Government Strategic Research Area in Materials Science [2009-00971]</p
Föräldraskap och ekonomisk ojämlikhet : – vardagslivets villkor för familjer i socialtjänsten
No full text Families in social services and child protection agencies often live under strained economic conditions. However, this is not always the truth. This article addresses the economic and social differences of families in contact with the Swedish social services. Empirically the article relies on life-course interviews with mothers in four families. Using Bourdieu’s concepts of economic, social and cultural capital the analysis highlights how inequal conditions of everyday life interplay with the lives of families from different economical positions and their relationships with the social services. The analysis describes that the better-off families are quite content with the help they get from the social services. The families with smaller economic resources however, are not only less satisfied, but also feel a lack of recognition from the services regarding their needs