Publikationer från Uppsala Universitet
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The United States of Americas renewable energy situation through the lens of the planner’s triangle : a case study using GIS
No full textThe purpose of this thesis was to calculate the levelized cost of energy and energy generation of both the current use of fossil fuels and the potential of renewables in the United States of America. The case study was based on Scott Campbells theory of the “Planner’s triangle”. This was done with the use of data from governmental agencies in ArcGIS Pro. To fully encompass all aspects of the theoretical framework, a minor literature review was also conducted. The results showed significant potential for renewable sources, with the cost of renewable energy being lower than that of fossil fuel in most cases. The potential generation of energy was also high for many parts of the United States. The literature review revealed indications of social inequity related to energy cost and provision. However, for real world applications, laws and policies, along with regional social factors would need to be considered for the analysis to be as correct as possible for any given case
Development and optimization of Gyrolab immunoassay targeting biomarker neurofilament light chain : Implementation of BOLD signal amplification on the Gyrolab platform
No full textImmunoassays (IAs) are a collection of analytical tools used to detect and measure the concentration of different macromolecules such as proteins or nucleic acids in solutions. Referred to as biomarkers, these macromolecules tell us about different conditions in our bodies which makes them useful in a vast majority of different medical fields involving diagnostics, prognostics and drug development. Neurofilament light chain (NfL) is one example of a general biomarker indicating neuronal degradation, which is a typical hallmark for neurodegenerative diseases such as Alzheimer’s, Parkinson disorder and Multiple sclerosis. The aim of this project was to develop and optimize a sensitive immunoassay for detection and quantification of neurofilament light protein in human serum. The work was conducted at Gyros Protein Technologies using their highly flexible and automated immunoassay platform Gyrolab. With Gyrolab, immunoassays are performed at nanoliter-scale on microfluidic discs that generates fast results while covering a broad dynamic range. In this project, a NfL-assay was designed by initially testing different anti-NfL antibodies-pairs in a sandwich assay-setup. To increase the sensitivity of the assay, the Binding Oligo Ladder Detection (BOLD) signal amplification technique was applied on promising assay-candidates. The BOLD technique is a set of add-on reagents that expands the binding site for detection antibodies, generating more signal per antibody-antigen interaction. It works by conjugating primers to the original detection antibody to which enzymes, RNA-template and DNA-monomers are added. A DNA/RNA hybrid strand is synthesized which act as a binding spot for tertiary detection antibodies. The implementation of BOLD increased the signal significantly. Lowering the template-concentration further increased the sensitivity of the assay. The optimized assay was tested in human serum were LOD- and LLOQ-values were estimated to 2.28 pg/mL and 20pg/mL respectively. Although this study successfully applied a signal amplification strategy to a NfL-immunoassay previously untested on the Gyrolab platform, additional refinement is necessary to ensure and enhance assay sensitivity and reliability in serum matrices
Machine Learning-Based Wake Loss Estimation Using Operational Data And Terrain Features
No full textAccurate estimation of wake losses is substantial for wind resource assessment and financial feasibility of wind power projects. Despite their computational efficiency, analytical wake models often underperform in sites characterized as complex terrain. This study investigates the potential implementation of tree-based machine learning (ML) models on estimation wake losses by incorporating operational data augmented with terrain and inflow aspects. The study is based on a large-scale wind farm operating in northwest Sweden, from which 31 turbines were chosen to conduct pairwise analysis on wake losses. Over four years of time-series SCADA data were combined with terrain features derived via QGIS, such as ruggedness, roughness, and elevation variations. Turbulence intensity and Richardson number were obtained to represent flow conditions. Two ML models were trained, the Model A used freestream sector data to determine turbine performance under wake-free conditions as a baseline. The Model B trained on wake-affected sectors to predict wake losses. Wake loss was calculated by comparing actual SCADA output with prediction of Model A. Trained models were evaluated by R², MAE, and RMSE metrics. Feature importance rankings demonstrated that turbine spacing, Richardson number, and terrain characteristics, such as maximum slope and the elevation standard deviation, significantly affect the models’ estimations, together with wind speed and direction features. The findings demonstrate that pure machine learning models are inherently limited in capturing complexity of wake and wind flow dynamics compared to high-fidelity physical simulations. Still, the machine learning approach offers a simple and versatile computational setup for wind power developers, especially in the early phase of wind resource assessment, bridging the gap between model accuracy and insights gained from operational wind farms
Validated LC-MS/MS Method for Quantifying the Antiparasitic Nitroimidazole DNDI-0690 in Preclinical Target Site PK/PD Studies
No full textUnderstanding the target site pharmacokinetics (PK) of the nitroimidazole analog DNDI-0690, a potential drug for the neglected parasitic disease leishmaniasis, is important due to the diversity of infected tissue sites and potential drug penetration variability. An ultrahigh-performance liquid chromatography–tandem mass spectrometry (UHPLC-MS/MS) method was developed and validated for quantifying DNDI-0690 in murine biomatrices (plasma, liver, spleen, skin, and skin microdialysate). The method used three protein precipitation sample preparation procedures, tailored for different biomatrices, utilizing a surrogate biomatrix approach. Murine tissues were enzymatically homogenized with a Collagenase A mixture. Chromatographic detection was performed on a C18 column using gradient elution, coupled to a QTRAP6500 quadrupole MS, operating in positive ionization mode. The method demonstrated accurate and precise quantification of all murine biomatrices on the surrogate biomatrix calibration standards, with a high and reproducible total recovery ranging from 75.9% to 94.2% (CV% ≤ 2.5%). Matrix interferences were mitigated with a deuterated internal standard. Stability experiments demonstrated that DNDI-0690 remained stable in all biomatrices under various conditions. This validated UHPLC-MS/MS method was successfully used to quantify DNDI-0690 in a target site murine infection model, demonstrating its suitability for future target site PK studies involving DNDI-0690
Tracking mRNA in living cells : Analyzing the kinetics of mRNA dynamics using an MS2 based system
No full textTranslation is crucial to living cells and is itself highly dependent on the journey of mRNA.mRNA is responsible for delivering the embedded code of the DNA to the ribosome in order forthe correct proteins to be produced. The details of this system are complex and hard to graspby in vitro experiments. mRNA are translated to proteins in the cytosol and, in the case ofmembrane proteins, the protein can get inserted into the membrane as translation is going on.This single-molecule tracking project aims to further experiment with an existing MS2 system fortracking mRNA in vivo and analyze the kinetics of mRNA dynamics inside E. coli cells. Thesystem utilizes the affinity between the MS2 RNA stem loop and the MS2 bacteriophage coatprotein (MS2CP). The latter is fused to Halotag (creating MS2CPHalo) in order for tracking tobecome viable through fluorescence microscopy. We show that the system is capable oftracking membrane protein mRNA and displays key differences in mRNA behaviour underdifferent translation conditions, such as co-translational insertion and ribosome binding site(RBS) mutation
Predicting the long-term viscoelastic response by short-term tests in polymers
No full textAdditive manufacturing, specifically Material EXtrusion (MEX) based 3-D printing technique in thermoplastic polymers, enables intricate geometries by depositing molten material out of a nozzle and building layer-upon-layer. By using sustainable thermoplastics, such as PolyLactic Acid (PLA) that generates less emission during production regarding conventional plastics, it is possible to produce parts with a smaller carbon footprint. However, the resulting anisotropic properties from this layered structure and unknown viscoelastic characteristics may introduce uncertainties in predicting the long-term mechanical performance of printed components. PLA is modeled as a linear elastic material, yet we emphasize that polymers may have a long relaxation time, hence, we conduct benchmark on significance of viscoelastic behavior and then model the response by exploiting the Time-Temperature Superposition (TTS) in order to predict viscoelastic response over a longer duration than measured. To model the viscoelastic behaviour, we use fractional time derivative. Then by using the inverse analysis, we obtain the best parameters, minimizing the error between the experiments and the predictive model. The determined parameters in the fractional Maxwell model, with the data of 16 h at three different temperatures, is then validated by predicting the response with an accuracy of ± 1% after 100 h
Anticipating a Future with AI : An exploratory study on organisational and societal implications
No full textThis thesis explores how leaders of organisations in the Swedish IT sector anticipate theimpact that AI will have on organisations in the coming decade. A qualitative researchdesign, based on semi-structured interviews was used in order to gain empirical material forthe study. Thematic analysis was then used to organise and present the empirical data. Therespondents consisted of seven leaders and experts working in Swedish IT companies, in thespan of smaller startups to larger firms. The findings reveal both uncertainty and enthusiasmfor the future, and some themes that particularly emerged were transformation of roles andtasks, reliance on big tech, and efficiency. AI is seen by the respondents mainly as a tool forautomating repetitive tasks, however, the future impact of AI on organisations involvesquestions regarding job roles, trust, strategy and human interaction. This thesis contributes toresearch regarding the opportunities and challenges that AI developments might bring uponorganisations and the overall society. Hopefully, this thesis may also provide strategicinsights on how organisations can navigate an uncertain and complex future withtechnological disruptions related to AI
Interpersonal relationships in patients suffering from chronic musculoskeletal pain : a case-control study analyzing core conflictual relationship themes and interpersonal problems
No full textBackground Psychosocial factors are involved in all types of chronic pain but seem to play a more prominent role in non-specific pain, such as chronic musculoskeletal pain (CMP), compared to a specific pain condition, such as osteoarthritis (OA). We explored if diagnose and the pain experience in patients with CMP predicted more problematic interpersonal relationships compared to patients with OA. Methods Nineteen patients with CMP and 16 unmatched clinical controls with OA were measured with the Core Conflictual Relationship Theme coding of clinical interviews (CCRT) and the Inventory of Interpersonal Problems (IIP). Results Significant differences in age, work status, and pain experience were found between the groups. Controlling for these variables, components of CCRT were significantly more likely to be disharmonious in patients with CMP compared to patients with OA. Patients with CMP also reported more interpersonal distress in general and socially avoidant-nonassertive problems in particular as their pain experience increased. Conversely, scores of dominant-intrusive behaviours increased as their pain experience decreased. These interaction effects between pain experience and interpersonal problems were not seen in patients with OA. Conclusions The impact of interpersonal issues may differ depending on type of pain diagnosis. This study show that interpersonal distress seems to play a more prominent role in non-specific chronic pain compared to a specific pain condition. It is possible that patients whose pain-processing system is burdened by interpersonal problems are more prone to non-specific pain, such as CMP. It could also be that primary pain is a greater challenge to interpersonal relationships. Whether interpersonal distress is a precursor or an additional stressor, it may worsen the condition of primary pain with implications for treatments
Parents’ views of the acceptability and efficacy of the Safe Environment for Every Kid model in the Swedish child health services
No full textBackground: Safe Environment for Every Kid (SEEK) is one of few evidence-based approaches to identify psychosocial problems and facilitate support to families within pediatric primary care. The Swedish version of SEEK, called BarnSäkert (“Child Safe”), is being evaluated as a complex intervention in the Swedish child health services (CHS) for children aged 0–6 years. Objective: Assessment of parents’ views of the acceptability and efficacy of the BarnSäkert SEEK model within the CHS in Sweden. Participants and setting: Mothers and fathers (n = 353) whose children were enrolled in the CHS. Methods: An anonymous web-based survey posed questions regarding how parents perceived BarnSäkert/SEEK and whether services had been offered, accessed or planned as a result. Efficacy was measured as parents’ reports of an improved life situation or having been helped by the model. Results: Among parents who discussed their situation with the nurse, 80 % reported that it had helped, 24 % had received help that they otherwise would not have and 20 % that their situation had improved. Appropriateness of the model was scored at 91/100 by mothers and 86/100 by fathers. Logistic regression showed significantly higher odds ratios for efficacy measures and service uptake for parents who were younger, born outside of Sweden or had lower levels of education. Conclusions: Parents reported that the model was highly acceptable and efficacious in meeting their psychosocial needs. The findings lend support for application of the BarnSäkert/SEEK model in the Swedish CHS as an equitable approach to address psychosocial problems in families with young children
A U3 snoRNA is required for the regulation of chromatin dynamics and antiviral response in Drosophila melanogaster
No full textSmall nucleolar RNAs (snoRNAs) are prevailing components of the chromatin-associated transcriptome. Here we show that specific snoRNAs are required for the activation of immune response genes and for survival during viral infections in Drosophila melanogaster. We have studied snoRNA:U3:9B, a chromatin-associated snoRNA that binds to a large number of protein coding genes, including immune response genes. We have used CRISPR/Cas9 to delete snoRNA:U3:9B and study its function in vivo. SnoRNA:U3:9B-deficient larvae are viable but failed to develop into pupae when challenged by expression of a Sindbis virus replicon. SnoRNA:U3:9B is localized to immune genes in vivo and the chromatin decompaction and gene activation typically observed at immune genes following infection are abolished in snoRNA:U3:9B-deficient larvae, which suggests that this snoRNA acts locally to regulate chromatin accessibility. Mechanistically, snoRNA:U3:9B is required for the recruitment of the chromatin remodeler Brahma to a set of target immune genes. In summary, these results uncover an antiviral defense mechanism that relies on a snoRNA for the recruitment of a chromatin remodeling factor to immune genes to facilitate immune gene activation