Publikationer från Uppsala Universitet
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Predicting Physical Properties Using Neural Networks: A Case Study from Ludvika Mines-Central Sweden : Machine-learning applications for predicting unmeasured rock physical properties
No full textThis MSc project aims to leverage the power of machine learning solutions to predict subsurface wave velocities for other measured properties, a crucial parameter in seismic exploration and characterization of mineral deposits. Specifically, the project will develop a neural network model that utilizes rock properties, lithology, and depth information extracted from borehole data from the Blötberget mine in the Ludvika region in central Sweden. By training the model on these parameters, it seeks to generate reliable sonic velocity predictions for other boreholes within the same area.There are six boreholes where these properties are measured and the goal is to predict the velocities fo rborehole where only limited other information is available.The significance of sonic velocity lies in its direct correlation with the subsurface geological structure,which is accountable in identifying potential mineralized zones but also in their use in for seismic imaging applications such as for migration and time-to-depth conversion. Traditional methods of obtaining these velocities, such as direct measurement or empirical correlations, are often time-consuming, costly, and subject to significant uncertainties. By adopting a machine-learning approach, this MSc thesis endeavors to bypass these limitations, offering a cost-effective, accurate, and efficient alternative in the exploration phase
Machine Learning Predicts Accuracy in Eyewitnesses' Voices
No full textAn important task in criminal justice is to evaluate the accuracy of eyewitness testimony. In this study, we examined if machine learning could be used to detect accuracy. Specifically, we examined if support vector machines (SVMs) could accurately classify testimony statements as correct or incorrect based purely on the nonverbal aspects of the voice. We analyzed 3,337 statements (76.61% accurate) from 51 eyewitness testimonies along 94 acoustic variables. We also examined the relative importance of each of the acoustic variables, using Lasso regression. Results showed that the machine learning algorithms were able to predict accuracy between 20 and 40% above chance level (AUC = 0.50). The most important predictors included acoustic variables related to the amplitude (loudness) of speech and the duration of pauses, with higher amplitude predicting correct recall and longer pauses predicting incorrect recall. Taken together, we find that machine learning methods are capable of predicting whether eyewitness testimonies are correct or incorrect with above-chance accuracy and comparable to human performance, but without detrimental human biases. This offers a proof-of-concept for machine learning in evaluations of eyewitness accuracy, and opens up new avenues of research that we hope might improve social justice
A Mixed Methods Approach to Analyzing Embodied Interaction : The Potentials of Integrated Mixed Methods Analysis of Video Interaction Data
No full textVideo has become a widespread tool for capturing naturalistic behavioral data. While mixed methods show great potential in understanding the active nature of children’s interaction, only a few studies have developed mixed methods for video-based interaction research. This paper presents a mixed methods embodied interaction model appropriate for studying complex embodied interaction and draws on methodological insights from a mixed methods project to capture changes in children’s interaction with touchscreen technologies. The paper details how integrated mixed methods analysis was needed to fully explain the results and how mono-method studies would provide misleading results. The theoretical advancements generated during the project illustrate how mixed methods for video-based studies have valuable properties for understanding complex interactional phenomena, such as learning
Drug utilization among young adults with atopic dermatitis : Influence of sex, socio-economic status and disease severity
No full textBackground Atopic dermatitis (AD) affects individuals of all ages, and the first-line treatment are emollients and topical corticosteroids. There is insufficient knowledge about factors possibly affecting the drug utilization of young adults with AD. Objectives To describe the drug utilization of young adults with AD in relation to sex, socio-economic status and disease severity. Methods A cross-sectional study based on the 24-year follow-up from the population-based BAMSE (Children, Allergy, Milieu, Stockholm, Epidemiology Survey) birth cohort linked with dispensing data from the National Drug Register (n = 2912). Self-reported AD and socio-economic status were defined from questionnaire data and disease severity was determined through the clinical examination and Patient-Oriented Eczema Measure questionnaire. Results The prevalence of AD in young adults was 17.7% (n = 516) and 45.5% of them were dispensed at least one drug for the treatment of AD during the study period (January 2016 to June 2019). Topical corticosteroids (TCS) were the most common drugs (32.9%) followed by emollients (21.7%). A larger proportion of men were dispensed TCS than women (39.0% vs. 29.1%: p-value = 0.020). A larger proportion of young adults with moderate-to-severe AD were dispensed TCS than those with mild AD (52.6% vs. 35.3%: p-value = 0.026). No one was dispensed the recommended amount of emollients and less than five individuals were dispensed the recommended amount of TCS for mild disease. Male sex (adj.OR 1.54, 95% CI 1.06–2.34) and moderate-to-severe AD (adj.OR 2.62, 95% CI 1.59–4.31) were associated with dispensation of TCS. Conclusions A large proportion of young adults with AD was undertreated or untreated. Sex and disease severity did affect the dispensing patterns of investigated drugs
Towards a new generation of solid total-energy detectors for neutron-capture time-of-flight experiments with intense neutron beams
No full textChallenging neutron-capture cross-section measurements of small cross sections and samples with a very limited number of atoms require high-flux time-of-flight facilities. In turn, such facilities need innovative detection setups that are fast, have low sensitivity to neutrons, can quickly recover from the so-called. gamma-flash, and offer the highest possible detection sensitivity. In this paper, we present several steps towards such advanced systems. Specifically, we describe the performance of a high-sensitivity experimental setupat CERN n_TOF EAR2. It consists of nine sTED detector modules in a compact cylindrical configuration, two conventional used large-volume C6D6 detectors, and one LaCl3(Ce) detector. The performance of these detection systems is compared using Nb-93(n, gamma) data. We also developed a detailed GEANT4 Monte Carlo model of the experimental EAR2 setup, which allows for a better understanding of the detector features, including their efficiency determination. This Monte Carlo model has been used for further optimization, thus leading to a new conceptual design of a gamma detector array, STAR, based on a deuterated-stilbene crystal array. Finally, the suitability of deuterated-stilbene crystals for the future STAR array is investigated experimentally utilizing a small stilbene-d12 prototype. The results suggest a similar or superior performance of STAR with respect to other setups based on liquid-scintillators, and allow for additional features such as neutron-gamma discrimination and a higher level of customization capability
Tripping in the Happiest Country of the World : Use Values of Psychedelics According to Finnish Users
No full textBackground The use of psychedelics is on the rise worldwide as more people are experimenting, self-medicating or seeking benefits from these substances. Aims This study explores the use values ascribed to classic psychedelics by 40 users in Finland – a country that scores high in welfare and happiness but has faced an increase in mental health problems and has adapted austerity policies in the public service sector. Methods The data consists of thematical interviews with individuals who use or have used psychedelics. We analysed the data focusing on the sense-making regarding use practices and use values. Results The analysis identified three main functions and benefits: (a) psychedelics as a catalyst for change, (b) psychedelics as a self-medication practice and (c) psychedelics as a device for self-improvement. Positive experiences included feelings of beauty, calmness, awe, connecting with others and mystical experiences. Psychedelics had helped the participants with depression, anxiety, difficult experiences and traumas. Conclusions Psychedelics appear to offer users experiences that are unattainable in their everyday lives. Their use can be seen as part of a contemporary biopolitical project of self-care and individualistic solutions for contemporary need for better mental health, living a carefree and meaningful life. When certain harm and risk reduction practices are considered, psychedelic use still seems likely to provide more benefits than harm for some individuals
"A Double Decline in Character" : A Grounded Theory Analysis of Female Drug User Experiences in Iran
No full textUsing a constructivist grounded theory design, this study explores the perception and experience of Iranian women living with drug use, identifying everyday conflicts and coping strategies that enable them to manage their situation. We conducted unstructured, in-depth interviews with abstinent drug users (11) and healthcare professionals (2) at three rehab centers in Tehran, Iran. In line with our grounded theory aspirations to explore the social meanings of women's drug use and addiction, we supplemented the interviews with a surrounding material consisting of articles published in the main national newspaper from 2015 to 2018 and a film documentary (10 parts, 3 h) entitled “Iranian Women of Addiction,” (Shab boohay-e-sokhteh) (2010–2011). Our analysis resulted in two main bundles of meaning-making that we claim are permeating the everyday lives of Iranian women with drug use: the double decline in character, and self-shielding. The study reveals the simultaneous presence of two stigmatized identities: drug use and sex work (fahsha). It shows that the stigma of sex work is closely connected to a drug-related identity, irrespective of whether women are actively involved in sex work or not. The findings illustrate how societal views are biased against drug user women in the domain of drug use, diminishing their presence and voice. The interviewees tried to manage by developing a peer network, adopting a protective role, and becoming intrinsically motivated to quit drug use. The study furthers our understanding of women's alarming and complex realities in traditional Islamic and familistic patriarchal structures
AI som verktyg i bedömningsprocessen av elevtexter : En svenskämnesdidaktisk studie
No full textDenna uppsats undersöker AI:s roll i bedömningen av elevtexter och jämför dess förmåga med mänsklig bedömning. Fokuset ligger på att identifiera styrkor, begränsningar och möjligheter hos AI i bedömningsprocessen. Metoddiskussionen visar att AI har svårt att ge både samstämmiga betyg och detaljerade kommentarer samtidigt. Detta begränsar dess användbarhet för slutgiltig bedömning. AI har svårt för att bedöma innehållsliga aspekter i elevtexter men är däremot närmare de mänskliga bedömningarna när det kommer till bedömning av språkliga och strukturella aspekter. Analysen pekar på att AI har begränsningar när det gäller att ge detaljerad kontextuell och metaspråklig bedömning. Samtidigt visar analysen att AI har en förmåga att ge generella kommentarer och analyser, vilket är något som kan bidra till lärares bedömningsarbete. Uppsatsen tar även upp utmaningar och förutsättningar för att implementera AI i undervisningen. Läraren behöver en viss teknisk kompetens och tillgång till resurser för att använda verktyget. Slutligen föreslås fortsatt forskning kring hur AI kan hantera bedömningskriterier och interagera med lärare för att förbättra bedömningsprocessen. Studien visar på att AI har potential som ett stödverktyg i bedömning men att det inte kan fullständigt ersätta en lärares expertis
Evaluating Modernization Through Hydropower: Social and Environmental Impacts of Nam Theun 2 and Nam Ou River Cascade in Laos
No full textThis thesis evaluates the environmental and social impacts of two landmark hydropower projects in Laos: the World Bank-funded Nam Theun 2 and the Chinese-funded Nam Ou River Cascade. Framed within the critiques of modernization theory, the study investigates how development projects, driven by differing conditionalities - normative for the West and economic for China - affect sustainability and equity. Employing a comparative case study approach, the research examines land use, biodiversity, water management, stakeholder engagement, resettlement, livelihoods, and access to services. The findings reveal that both projects exhibit significant shortcomings in mitigating environmental and social trade-offs, albeit in different dimensions reflective of their funding models. Nam Theun 2 demonstrates ambitious but poorly implemented governance frameworks, while Nam Ou River Cascade highlights efficiency-driven approaches with limited safeguards. This analysis underscores the limitations of traditional and economic conditionalities in addressing the multidimensional impacts of large-scale infrastructure projects, contributing to broader discussions on sustainable development and the applicability of modernization theory in the Global South
Micro-RNA Signature in CSF Before and After Autologous Hematopoietic Stem Cell Transplantation for Multiple Sclerosis
No full textBackground and Objectives: MicroRNAs (miRNAs) are regulators of gene expression and have been reported to be dysregulated in people with multiple sclerosis (pwMS). Autologous hematopoietic stem cell transplantation (aHSCT) is an immune-ablative treatment intervention for pwMS. Currently, it is unknown if aHSCT affects expression levels of miRNAs in CSF. We explored the ability of circulating miRNA to discriminate between pwMS and healthy controls (HCs) and investigated whether these miRNAs were affected by treatment with aHSCT. Methods: Using quantitative reverse transcription PCR, 87 miRNAs were analyzed in CSF samples of a discovery cohort (baseline: 4 & HC: 4). The top 22 miRNAs discriminating between pwMS and HCs were then analyzed in 187 CSF samples of a validation cohort (pwMS: 50, HC: 32). Samples, failing quality control or being follow-ups to baseline samples with quality control issues, were excluded from further analyses. The remaining 133 samples (HC: 29, MS: baseline: 33, 1 year: 30, 2 years: 26, 3-5 years: 15) were analyzed for expression of the top 22 miRNAs. Results: Twelve miRNAs were dysregulated in pwMS compared with HC (q < 0.05). Associations with clinical and analytical parameters were observed in relation to all 12 miRNAs; however, a cluster of 4 miRNAs (miR-16-5p, miR-21-5p, miR-150-5p, and miR-146a-5p) with strong correlations (r > 0.60, p < 0.001) with multiple parameters was identified. Of the 12 miRNAs, 8 were differentially expressed in pwMS with gadolinium-enhancing lesions at baseline and 4 by prior disease-modifying treatment class (p < 0.05). These 4 miRNAs correlated strongly with each other, decreased after aHSCT, and remained low throughout the follow-up period (p < 0.05). Target and pathway analysis of these revealed association with biological processes affecting cytokine production, inflammatory response, and regulation of myelin maintenance. Discussion: miRNAs are dysregulated in CSF from pwMS and particularly in patients with less effective treatments and/or higher inflammatory disease activity. A 4-miRNA signature with elevated expression of miR-16-5p, miR-21-5p, miR-150-5p, and miR-146a-5p was recurring in multiple analyses. After intervention with aHSCT, the expression levels approached the levels of the HCs, suggesting a potent treatment effect