Publikationer från Uppsala Universitet
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Investigation into the Existence of a Periodic Solution to Point and Patch Setting for the Incompressible 2D Euler Equations
No full textWe consider the incompressible Euler equations in two dimensions. These are a set of partial differential equations modeling certain ideal fluids. The equations may be formulated in terms of velocity flow or in terms of their curl, which in the context of fluid dynamics is aptly referred to as vorticity. We exhibit a certain simple solution to the equations consisting of a time-invariant circular patch of constant vorticity and remark that points outside rotate around said patch. Motivated by this we try to see whether a periodic point-and-patch solution also exists in the case when there is a localized non-zero vorticity in the point. The problem is reformulated into one of fixed point nature and thus suitable to attack by the Banach fixed point theorem. We seek solutions in two of the most simple scenarios. However the method we seek to employ in order for the fixed point argument to close fails due to non-invertibility
Variation in the number of radiocarbon (14C) dates does not equal change in Neolithic population size over time
No full textThis study investigates the relationship between radiocarbon (14C) dates and estimations of population size during the Neolithic period, approximately 5950-3650 cal BP, in the Malmo<spacing diaeresis> area of southwest Sweden. Utilising a dataset of 1025 radiocarbon samples, of which 732 were selected for detailed analysis, we applied the Lambda (lambda) model approach to identify significant periods of change in the number of radiocarbon dates. We also address the complexities introduced by the old wood effect (OWE), which impacts the reliability of radiocarbon dating. Our findings highlight four distinct periods of increase and decrease in the amount of radiocarbon dates during the time period under study. By comparing these results with other data from over 45 years of extensive contract archaeological excavations, we demonstrate that the assumption of a correlation between the number of radiocarbon dates and population size is overly simplistic. Our analysis reveals that a high number of dates does not necessarily guarantee credible population size inferences. These findings suggest that similar conditions could hypothetically apply to other spatiotemporal contexts, thereby calling into question the reliability of radiocarbon dates as sole indicators of population dynamics
Local Structure and Dynamics in Solvent-Free Molten Salt Ca2+-Electrolytes
No full textCalcium batteries (CaBs) fundamentally offer a promise of sustainable high energy density storage. However, the development of functional CaB electrolytes remains a key challenge. Here, molecular simulations are used to investigate structural and dynamic properties of solvent-free molten salt electrolytes (MSEs) containing Ca2+ and alkali cations (Li+, Na+, K+, paired with either FSI or TFSI anions. Two equimolar MSEs, [Li, Na, K, Ca]FSI and [Li, Na, K, Ca] TFSI, are examined across a range of temperatures to better understand cation-anion interactions, coordination and local structure, and ion mobility, in particular with respect to Ca2+. The interplay between cation charge density, anion structure, and thermal effects provides valuable insights into the MSEs' macroscopic behavior. These insights inform the design of advanced electrolytes that enhance Ca2+ mobility, supporting the development of next-generation CaBs
Enhanced glaucoma detection using U-Net and U-Net plus architectures using deep learning techniques
No full textThis study compares multiple image processing and deep learning methods to demonstrate an enhanced approach to glaucoma diagnosis. The approach focuses on noise reduction using median filtering and optic disc segmentation utilizing the U-Net and U-Net+ architectures. Capsule Networks were utilized for feature extraction and Extreme Learning Machines (ELM) for diagnostic classification. Three datasets were evaluated, including DRISHTI-GS, DRIONS-DB, and HRF, utilizing important parameters such as accuracy, sensitivity, and specificity. The findings revealed that median filtering reduced noise by 97.88%, with a peak signal-tonoise ratio of 44.99. U-Net beat U-Net+ in optic disc in the process of segmentation with a Dice coefficient of 0.8557, a Jaccard index of 0.7307, and higher segmentation accuracy. The suggested model has great diagnostic accuracy, scoring 99% for DRISHTI-GS, 99.5% for DRIONS-DB, and 98.5% for HRF. These findings show that using deep learning approaches can increase glaucoma diagnosis accuracy and reliability, with important implications for healthcare applications and patient outcomes.Wireless Brain-Connect inteRfAce TO machineS: B-CRA TOS, European Union’s Horizon 2020 Research and Innovation Program, Grant agreement ID: 965044“BOS: Software Principles & Techniques for a Body-centric OS”, the Swedish Foundation for Strategic Research (SSF) grant FUS21-006
Personal GP continuity improves healthcare outcomes in primary care populations : a systematic review
No full textBackground Personal continuity is a hallmark for GPs but there is insufficient evidence to support its benefits in ordinary primary care populations. Aim To investigate the effects of GP personal continuity on the healthcare outcomes of primary care populations. Design and setting Systematic review of quantitative studies investigating associations between personal continuity of care and outcomes such as mortality and healthcare utilisation. Method Embase, PubMed, Scopus, and Web of Science were searched for studies published between 1 January 2000 and 31 October 2023. Owing to study heterogeneity the synthesis was conducted narratively; study results were summarised and expressed as having higher (compared with lower) continuity of care. Certainty of each summarised result was assessed usingthe GRADE framework. Results Out of 5792 unique references, 18 studies were included in the final analyses. The outcomes were grouped into three categories of summarised outcomes. Higher (when compared with lower) personal continuity with a GP/ family physician probably prevents premature mortality (moderate certainty: four studies, 5 638 305 participants), probably reduces the risk of admission to hospital (moderate certainty: 11 studies, 13 642 684 participants), and probably lowers risk of emergency department visits (moderate certainty: seven studies, 3 855 487 participants). Conclusion Higher, compared with lower, continuity in the relationship between GP and patients in primary care populations is associated with reduced mortality, admissions to hospital, and emergency department visits. Relatively small improvements in personal continuity, which may be achieved in most practices, significantly reduce healthcare consumption, and thus may have an impact on access to care, which has implications for healthcare polic
'Chimes of resilience' : what makes forest trees genetically resilient?
No full textForest trees are foundation species of many ecosystems and are challenged by global environmental changes. We assemble genetic facts and arguments supporting or undermining resilient responses of forest trees to those changes. Genetic resilience is understood here as the capacity of a species to restore its adaptive potential following environmental changes and disturbances. Importantly, the data come primarily from European temperate tree species with large distributions and consider only marginally species with small distributions. We first examine historical trajectories of trees during repeated climatic changes. Species that survived the Pliocene-Pleistocene transition and underwent the oscillations of glacial and interglacial periods were equipped with life history traits enhancing persistence and resilience. Evidence of their resilience also comes from the maintenance of large effective population sizes across time and rapid microevolutionary responses to recent climatic events. We then review genetic mechanisms and attributes shaping resilient responses. Usually, invoked constraints to resilience, such as genetic load or generation time and overlap, have limited consequences or are offset by positive impacts. Conversely, genetic plasticity, gene flow, introgression, genetic architecture of fitness-related traits and demographic dynamics strengthen resilience by accelerating adaptive responses. Finally, we address the limitations of this review and highlight critical research gaps
Comparative Analysis of Spiking Neural Network Models
No full textThis study presents a comprehensive evaluation of state-of-the-art supervised learning algorithms based on spiking neural network (SNN) using an in-lab neuromorphic sensor dataset. The learning algorithms of the study include accumulated spiking flow backpropagation (ASF-BP), information maximization loss (IM-Loss), feedforward SNN with surrogate gradients, and spike timing-dependent plasticity (STDP), which are used to benchmark a novel laboratory-developed learning model, the brain-mimetic developmental neural network (BDNN). Using the neuromorphic tactile dataset of 4000 samples from 20 objects captured via 64-sensor electronic skin, we evaluated each method across three network architectures to establish comprehensive performance benchmarks. Compared to the BDNN which achieved 93\% classification accuracy with only 5.8 hours of training time, the IM-Loss achieved 91.68\% accuracy but requiring 31.75 hours of training, and the ASF-BP reached 76.57\% accuracy in 2.66 hours. The advantages of BDNN’s stem from its adaptive architecture determination and intrinsic knowledge transfer capabilities, eliminating the need for surrogate gradients and extensive hyperparameter tuning required by conventional approaches
Conditional sampling within generative diffusion models
No full textGenerative diffusions are a powerful class of Monte Carlo samplers that leverage bridging Markov processes to approximate complex, high-dimensional distributions, such as those found in image processing and language models. Despite their success in these domains, an important open challenge remains: extending these techniques to sample from conditional distributions, as required in, for example, Bayesian inverse problems. In this paper, we present a comprehensive review of existing computational approaches to conditional sampling within generative diffusion models. Specifically, we highlight key methodologies that either utilize the joint distribution, or rely on (pre-trained) marginal distributions with explicit likelihoods, to construct conditional generative samplers
Knowledge, attitudes, and practices toward zoonotic disease transmission among wildlife farmers in Vietnam
No full textBackground Wildlife farming and trade in Southeast Asia contribute to the growing threat of zoonotic diseases. Despite the diversity of species farmed and the varying levels of risk they may pose, biosecurity practices among wildlife farmers remain underexplored. This study aimed to assess the knowledge, attitudes, and practices (KAP) of wildlife farmers in Vietnam to inform targeted interventions for zoonotic risk reduction. Method A mixed-methods study was conducted among 210 wildlife farmers who raised bats, bamboo rats, civets, and wild boars in Lao Cai and Dong Nai provinces, Vietnam, between October 2023 and March 2024. Quantitative data were collected via structured questionnaires, and qualitative insights were obtained through 30 key informant interviews and two focus group discussions. Linear mixed-effects regression and thematic analysis were applied to explore KAP scores and associated factors. Results Wildlife farmers demonstrated relatively high knowledge (mean score: 10.1/13, 77.7%), positive attitudes (mean score: 41.3/50, 82.6%), and moderate preventive practices (mean score: 14.1/30, 47.0%). Farmers with college or above education had higher knowledge scores (Estimated marginal mean (EMM) = 11.8; 95% confidence interval (CI): 10.2–12.8) compared to those with no formal education (EMM = 7.8; 95% CI: 4.0–11.1). Farmers solely engaged in wildlife farming had lower attitude scores (EMM = 41.7; 95% CI: 37.8–45.0) than farmers who also worked as government employees (EMM = 46.1; 95% CI: 43.3–48.2). Farming bats (EMM = 8.5; 95% CI: 5.8–11.4) had lower practice scores compared to farming civets (EMM = 15.8; 95% CI: 13.0–18.6), and farmers consumed wild meat had lower practice score (EMM = 12.3; 95% CI: 9.5–15.2) than those did not (EMM = 14.5; 95% CI: 11.9–17.0). Qualitative findings revealed that many farmers normalised risky practices, prioritised convenience and personal experience over disease knowledge, and avoided reporting illnesses due to mistrust in veterinary authorities and fear of negative consequences. Conclusion This study highlights low risk perception and gaps between knowledge and practices among wildlife farmers, underscoring the urgent need for One Health interventions that promote low-cost preventive measures, build trust with authorities, and deliver targeted health education for reducing zoonotic risks
Tissue and cellular spatiotemporal dynamics in colon aging
No full textTissue structure and molecular circuitry in the colon can be profoundly impacted by systemic age-related effects but many of the underlying molecular cues remain unclear. Here, we build a cellular and spatial atlas of the colon across three anatomical regions and 11 age groups, encompassing ~1,500 mouse gut tissues profiled by spatial transcriptomics and ~400,000 single nucleus RNA-sequencing profiles. We develop a computational framework, cSplotch, which learns a hierarchical Bayesian model of spatially resolved cellular expression associated with age, tissue region and sex by leveraging histological features to share information across tissue samples and data modalities. Using this model, we identify cellular and molecular gradients along the adult colonic tract and across the main crypt axis and multicellular programs associated with aging in the large intestine. Our multimodal framework for the investigation of cell and tissue organization can aid in the understanding of cellular roles in tissue-level pathology