Publikationer från Uppsala Universitet
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Mellan mall och verklighet : En kvalitativ studie om speciallärares praktik med pedagogiska utredningar av läs- och skrivsvårigheter i grundskolans tidiga år
No full textSammanfattning Syftet med denna studie var att undersöka hur speciallärare utreder läs- och skrivsvårigheter och hur deras utredningspraktik förhåller sig till det underlag för pedagogisk utredning som tillhandahålls av Skolverket och Specialpedagogiska skolmyndigheten (SPSM). Myndighetens material är ett stöd för att utreda läs- och skrivsvårigheter och öppnar även för möjligheten att ställa pedagogiska dyslexidiagnoser ute i skolorna. Studien har en kvalitativ ansats och baseras på en textanalys av SPSM:s material samt tematiska analyser av intervjuer med sex speciallärare. Resultatet visar att ingen av speciallärarna använder myndigheternas mall, men att det finns tydliga likheter mellan deras beskrivna arbetssätt och det som föreslås från myndighetshåll. Fokus såväl i SPSM:s material som i lärarnas egna utredningsmodeller är de tekniska aspekterna av läsning. Myndighetsmaterialet är icke-föreskrivande till sin karaktär. Speciallärarnas beskrivningar av sitt arbete visar att de i mångt och mycket arbetar i enlighet med SPSM:s material, men att det är variation mellan skolorna. Speciallärarna är inte intresserade av att ställa pedagogiska diagnoser ute på skolorna och betonar vikten av att utredningar ska ha ett tydligt syfte, samt ligga till grund för stödåtgärder oavsett om eleven har en diagnosticerad svårighet eller inte. Studien bidrar med kunskap om speciallärarnas utrednings- och bedömningspraktik under de tidiga skolåren. En fråga som väcks är om tydligare riktlinjer och nationellt fastställda arbetssätt vid utredningar skulle kunna bidra till att öka likvärdigheten i svensk skola. Nyckelord: speciallärares bedömningspraktik, läs- och skrivsvårigheter, utredningsmall, pedagogisk dyslexidiagnos, semistrukturerad intervju, textanalys, tematisk analys
Development and optimization of lyophilized dry emulsion tablet for improved oral delivery of Ivermectin
No full textIvermectin (IVM) is a widely used antiparasitic agent and has been repurposed for the treatment of COVID-19. However, its poor water solubility and low bioavailability present significant challenges, often requiring large doses for therapeutic effectiveness. This poses a burden on patients, as they need to take multiple tablets at once, which is both inconvenient and uncomfortable. This study aims to develop and optimize rapidly disintegrating lyophilized dry emulsion tablets (LDET) containing IVM using a quality by design (QbD) approach to enhance its solubility, dispersibility, wettability, and dissolution rate, thereby improving its absorption and bioavailability following oral administration. Oil-in-water (O/W) emulsions were prepared using sweet almond oil or Miglyol 840 as the oil phase, along with stabilizers. The optimal emulsion was subsequently lyophilized to produce IVMLDET. Tablets' characteristics were assessed in vitro for their properties including solubility, disintegration, and dissolution, and in vivo in rabbits for their pharmacokinetic (PK) profile. Results indicated a remarkable 600-fold increase in IVM solubility in the optimal emulsion formulation. IVM-LDET significantly enhanced the extent and rate of dissolution compared to raw IVM and the marketed tablet, Iverzine (R). Furthermore, the PK profile of IVM from LDET showed a 30 % increase in maximum plasma concentration (Cmax) and area under the curve (AUC), and reduced time to reach maximum concentration (tmax) by 4 h compared to Iverzine (R) tablets. In conclusion, the developed IVM-LDET formulation presents a promising therapeutic alternative to conventional oral IVM products for treating parasitic or viral infections, potentially leading to improved therapeutic outcomes and patient compliance
Game-based Quantification of Chess Player Types
No full textThe classification of chess players based on playing styles has traditionally relied on qualitative insights from chess experts. One way is to categorize players into four main types: activists, pragmatists, theorists, and reflectors. However, the classification relies on chess experts and is not quantitatively interrogated. In this thesis, we analyzed 100,000 chess games and 8.5 million positions from renowned players to extract features that can quantify their playing styles and trained a classifier. For the feature extraction, we reproduced the board complexity metrics from two prior studies, and proposed our own methods to identify sacrifices and board pressure. We also extracted other game-level and position-level features according to chess theory to build our dataset. These features were aggregated to the player level and used to classify players into the four types. With such a big dataset, we carried out data analysis to discover insights and patterns. We performed PCA visualizations at the game level and the player level. Although no distinct patterns were found at the game level, we discovered certain patterns at the player level. Finally, we designed a player-level machine learning pipeline to predict the playing styles, reaching an accuracy of 50%, compared to the 25% baseline of random guessing. This research contributes to the data-driven analysis of chess styles, providing a foundation for future studies on player behavior and strategic tendencies within the game
Evaluating a General-Purpose Tool in Project Management : A case study of Volvo CE’s NPD process
No full textThis research examines the impact of Microsoft Excel on project management processes within Volvo CE’s new product development procurement process. Through interviews, observations, and document analysis, four main themes were identified: Reliance on general-purpose tool; Multiple systems and standardisation; Communication and collaboration; and Organisational culture and change management. Although Excel’s widespread use in the organisation and flexibility allow for quick adaptations, it also introduces errors and inefficiencies. Datasilos across SAP, Windchill, and Excel lead to duplicated information and delays. The size of the organisation and ingrained habits slow down the adoption for integrated digital solutions. Recommendations for the short-, mid- and long-term are proposed: (1) short-term automation of time plan and template standardisation; (2) mid-term process integration and unified workflow; and (3) long-term system integration and implementation of specialised software or platforms. These measures aim to reduce administrative effort, strengthen cross-functional collaboration, and support a shift toward more agile, data-driven project management
Modelling the combined impacts of climate change and socio-economic development on waterborne pathogen transport
No full textProtection of our water resources is essential to provide future generations with safe drinking water, recreational opportunities, and reliable ecosystem services. Climate and land use changes exert pressure on the quality of our water resources. Additionally, societal development may generate both positive and negative impacts on future water quality. Thus, decisions made today will impact the water quality of tomorrow. In this paper, we address the issue of future microbial water quality by combining Representative Concentration Pathways and Shared Socio-economic Pathways with projections of societal development, either downscaled to a local level or assessed by local organisations. We use Lake Vomb in Sweden (providing approximately 330 000 persons with drinking water) to illustrate our novel approach of assessing the impact of climate change and societal development on future microbial water quality. The approach includes norovirus, Escherichia coli (as an indicator organism), and Cryptosporidium. Further, we combine hydrological and hydrodynamic fate and transport modelling to simulate future water quality in the tributaries and at the drinking water intake. Future simulations are compared to a baseline scenario representing the current situation. Results show that climate change will reduce future water quality. However, we can also see that societal development significantly impacts microbial water quality, potentially counteracting the increases in microbial concentrations induced by climate change. Therefore, drinking water supply management must adapt to both future climate and societal development
Är pennan mäktigare än tangentbordet? : En kvantitativ textanalys av analogt och digitalt skrivna elevtexter
No full textI takt med att datorer blivit vanligare i svensk skola har svenskämnets skrivundervisning och provgenomförande övergått till att alltmer genomföras på digitala enheter. Syftet med uppsatsen är att jämföra språkliga och textuella egenskaper i analogt respektive digitalt skrivna elevtexter. Studien utgår från teorin The Simple View of Writing och dess teoretiska antagande att om transkriptionen är kognitivt krävande återstår färre arbetsminnesresurser till skrivprocessens övriga delprocesser, vilket i sin tur kan leda till sämre textuell kvalitet. Antagandet testas med en kvantitativ textanalys av 30 analogt skrivna och 30 digitalt skrivna elevtexter från nationella prov i svenska 3 på gymnasiet. Skillnader uppvisas i produktivitet då de digitalt skrivna texterna är längre än de analogt skrivna texterna. Det stärker antagandet från tidigare forskning om att äldre elever är produktivare med tangentbord än med penna. Få eller inga skillnader uppvisas i språklig variation. Resultatet tyder således på att digital skrift är mindre krävande för gymnasieelevernas arbetsminne vilket påverkar produktiviteten men endast marginellt den språkliga variationen. Andra möjliga förklaringar diskuteras. Vidare indikerar resultatet tillsammans med tidigare forskning att elever bör erbjudas en varierad skrivundervisning i båda transkriptionsmedel. Förslag på vidare forskning ges
Rättsstat under inflytande : Hur avtalsparters regimtyp formar effekten av bilaterala investeringsavtal
No full text I takt med att allt fler länder ingår i bilaterala investeringsavtal har deras påverkan på rättsstatsprinciperna fått en allt större uppmärksamhet inom forskning. Samtidigt som fler studier undersöker sambandet mellan bilaterala investeringsavtal och rättsstatsnivån i länder har dessa resulterat i motstridiga uppfattningar om vad dess effekt egentligen är. Gemensamt för tidigare studier inom området är deras fokus på effekten av den totala kvantiteten bilaterala investeringsavtal på rättsstatsnivån. Denna studie bidrar med ett nytt perspektiv inom området genom att studera regimtyperna hos BIT-avtalsparter och deras effekt på rättsstatsnivån. Studien argumenterar för att de motstridiga resultaten från tidigare forskning beror på att de inte särskiljer på avtal med olika typer av regimer. Därav genomför denna studie en multivariat regressionsanalys för att undersöka hur staters nationella rättsstatsnivå påverkas av regimtypen hos stater de ingår bilaterala investeringsavtal med. Studien finner inga belägg för att det finns en effekt av avtal med stängda autokratier, elektorala autokratier och elektorala demokratier på rättsstatsprinciperna, men finner ett negativt samband mellan bilaterala investeringsavtal med liberala demokratier och rättsstatsnivån. Studien finner stöd för tidigare forskning som argumenterar för att bilaterala investeringsavtal, oavsett med vilka regimtyper, konsoliderar autokratiska regimer
Understanding Stakeholder Interactions, Relationship and Role Dynamics in the Electrification of Road Freight Transport in Sweden : A Qualitative Study of Perspectives from key stakeholders
No full text This thesis investigates stakeholder interactions and relationship dynamics in the transition to electrified road freight transport in Sweden. Heavy-duty vehicle (HDV) electrification is emerging as a key strategy for reducing transport-related greenhouse gas emissions. The key stakeholder ecosystem, which includes policymakers, freight companies, energy producers, grid operators, vehicle manufacturers, and charging infrastructure manufacturers, is complex, requiring a deeper understanding of how these stakeholders collaborate, exchange value, and perceive their roles. The study is guided by two research questions: (1) How do key stakeholders perceive their current relationships and interactions in the electrification of road freight transport? and (2) How can an analysis of stakeholder relationship and interaction dynamics enhance understanding of their roles in the transition? A mixed-method approach was adopted, combining thematic analysis of nine semi-structured interviews with Social Network Analysis (SNA) and the Value Exchange Model (VEM) to explore stakeholder centrality, collaboration structures, and value flows. Findings reveal that stakeholder relationships are multilayered and deeply interdependent, with freight companies occupying central coordinating roles. Institutional networks, technical forums, and policy platforms facilitate collaboration. However, gaps in cross-sector interaction continue. Stakeholder roles are shown to be dynamic and contingent on systemic support, regulatory clarity, and shared objectives. The study contributes theoretically to stakeholder and transition literature by integrating structural and value-based analyses. Practically, it highlights the importance of strategic coordination and mutual alignment. Recommendations include enhancing cross-sector engagement and long-term policy frameworks to support collaborative progress toward electrified freight systems
Brain-acting hepatokines : its impact on energy balance and metabolism
No full textThe liver is recognized for its central role in energy metabolism, yet emerging evidence highlights its function as an endocrine organ, secreting a variety of proteins-hepatokines-that influence distant tissues. Hepatokines not only regulate metabolic processes by acting on peripheral tissues but also exert direct effects on brain function. In this mini-review, we discuss the existing literature on the role of "brain-acting" hepatokines including IGF-1, FGF21, LEAP2, GDF15, and ANGPTLs, and their impact on energy balance and metabolism. We review the existing evidence regarding their roles in metabolism through their action in the brain, and their potential implications in metabolic disturbances. By integrating insights from recent studies, we aim to provide a comprehensive understanding of how liver-derived signals can modulate energy balance and metabolism
Predicting Commercial Real Estate Prices in Sweden Using Gradient Boosting and Random Forest Models : A Transaction-Based Study Guided by Industry and Academic Expertise
No full textThis study explored how machine learning models can be created to predict future sales prices of commercial real estate (CRE) in Sweden. With insights from both academic literature and interviews with industry experts, 94 relevant external parameters were identified for constructing Random Forest and Gradient Boosting models, additionally allowing analysis into what the model deemed important predictive variables. Of these, 71 were removed due to overlap or lacking data. Qualitative results were combined with a proprietary data set of 5798 Swedish CRE transactions conducted in the period 2014 to 2024, with 27 features. Resulting SHAP values indicated that variables linked to property information and location were the most important, whereas features highlighted by experts generally lacked predictive power. In general, Gradient Boosting models outperformed Random Forest models on both median errors (MDAPE of 31.7% vs. 33.4%) and proportion of variance explained by the respective models (R2 of 68% vs. 65.8%). Although performance improved through feature engineering and enhancing granularity, accuracy remained below previous machine learning applications analyzing private residential properties, where much larger transaction data sets were employed. Beyond differing data availability, smoothing effects and concept drift are potential reasons for the lower accuracy. These findings suggest that investors and appraisers could use gradient boosting models as a second-opinion tool in their current state, while firms should prioritize granular data to gain predictive accuracy in future settings. While data-driven price predictions can reduce transaction costs and enable sustainable development, it also risks increasing incumbents’ advantages, regional biases, and sector cyclicality, which necessitates transparent usage and human oversight. To create more accurate tree-based machine learning models, future studies should focus on exploring larger transaction data sets and including additional property-specific and external features. These findings contribute to the literature on algorithmic sales-price prediction as well as CRE literature through offering an analysis of what is currently possible provided the data availability within Swedish markets.