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1.
  • 2019
  • Journal article (peer-reviewed)
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2.
  • Feigin, Valery L., et al. (author)
  • Global, regional, and national burden of stroke and its risk factors, 1990-2019 : a systematic analysis for the Global Burden of Disease Study 2019
  • 2021
  • In: Lancet Neurology. - : Elsevier. - 1474-4422 .- 1474-4465. ; 20:10, s. 795-820
  • Journal article (peer-reviewed)abstract
    • Background Regularly updated data on stroke and its pathological types, including data on their incidence, prevalence, mortality, disability, risk factors, and epidemiological trends, are important for evidence-based stroke care planning and resource allocation. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) aims to provide a standardised and comprehensive measurement of these metrics at global, regional, and national levels. Methods We applied GBD 2019 analytical tools to calculate stroke incidence, prevalence, mortality, disability-adjusted life-years (DALYs), and the population attributable fraction (PAF) of DALYs (with corresponding 95% uncertainty intervals [UIs]) associated with 19 risk factors, for 204 countries and territories from 1990 to 2019. These estimates were provided for ischaemic stroke, intracerebral haemorrhage, subarachnoid haemorrhage, and all strokes combined, and stratified by sex, age group, and World Bank country income level. Findings In 2019, there were 12.2 million (95% UI 11.0-13.6) incident cases of stroke, 101 million (93.2-111) prevalent cases of stroke, 143 million (133-153) DALYs due to stroke, and 6.55 million (6.00-7.02) deaths from stroke. Globally, stroke remained the second-leading cause of death (11.6% [10.8-12.2] of total deaths) and the third-leading cause of death and disability combined (5.7% [5.1-6.2] of total DALYs) in 2019. From 1990 to 2019, the absolute number of incident strokes increased by 70.0% (67.0-73.0), prevalent strokes increased by 85.0% (83.0-88.0), deaths from stroke increased by 43.0% (31.0-55.0), and DALYs due to stroke increased by 32.0% (22.0-42.0). During the same period, age-standardised rates of stroke incidence decreased by 17.0% (15.0-18.0), mortality decreased by 36.0% (31.0-42.0), prevalence decreased by 6.0% (5.0-7.0), and DALYs decreased by 36.0% (31.0-42.0). However, among people younger than 70 years, prevalence rates increased by 22.0% (21.0-24.0) and incidence rates increased by 15.0% (12.0-18.0). In 2019, the age-standardised stroke-related mortality rate was 3.6 (3.5-3.8) times higher in the World Bank low-income group than in the World Bank high-income group, and the age-standardised stroke-related DALY rate was 3.7 (3.5-3.9) times higher in the low-income group than the high-income group. Ischaemic stroke constituted 62.4% of all incident strokes in 2019 (7.63 million [6.57-8.96]), while intracerebral haemorrhage constituted 27.9% (3.41 million [2.97-3.91]) and subarachnoid haemorrhage constituted 9.7% (1.18 million [1.01-1.39]). In 2019, the five leading risk factors for stroke were high systolic blood pressure (contributing to 79.6 million [67.7-90.8] DALYs or 55.5% [48.2-62.0] of total stroke DALYs), high body-mass index (34.9 million [22.3-48.6] DALYs or 24.3% [15.7-33.2]), high fasting plasma glucose (28.9 million [19.8-41.5] DALYs or 20.2% [13.8-29.1]), ambient particulate matter pollution (28.7 million [23.4-33.4] DALYs or 20.1% [16.6-23.0]), and smoking (25.3 million [22.6-28.2] DALYs or 17.6% [16.4-19.0]). Interpretation The annual number of strokes and deaths due to stroke increased substantially from 1990 to 2019, despite substantial reductions in age-standardised rates, particularly among people older than 70 years. The highest age-standardised stroke-related mortality and DALY rates were in the World Bank low-income group. The fastest-growing risk factor for stroke between 1990 and 2019 was high body-mass index. Without urgent implementation of effective primary prevention strategies, the stroke burden will probably continue to grow across the world, particularly in low-income countries.
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3.
  • Santangelo, James S., et al. (author)
  • Global urban environmental change drives adaptation in white clover
  • 2022
  • In: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 375
  • Journal article (peer-reviewed)abstract
    • Urbanization transforms environments in ways that alter biological evolution. We examined whether urban environmental change drives parallel evolution by sampling 110,019 white clover plants from 6169 populations in 160 cities globally. Plants were assayed for a Mendelian antiherbivore defense that also affects tolerance to abiotic stressors. Urban-rural gradients were associated with the evolution of clines in defense in 47% of cities throughout the world. Variation in the strength of clines was explained by environmental changes in drought stress and vegetation cover that varied among cities. Sequencing 2074 genomes from 26 cities revealed that the evolution of urban-rural dines was best explained by adaptive evolution, but the degree of parallel adaptation varied among cities. Our results demonstrate that urbanization leads to adaptation at a global scale.
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4.
  • Schael, S, et al. (author)
  • Precision electroweak measurements on the Z resonance
  • 2006
  • In: Physics Reports. - : Elsevier BV. - 0370-1573 .- 1873-6270. ; 427:5-6, s. 257-454
  • Research review (peer-reviewed)abstract
    • We report on the final electroweak measurements performed with data taken at the Z resonance by the experiments operating at the electron-positron colliders SLC and LEP. The data consist of 17 million Z decays accumulated by the ALEPH, DELPHI, L3 and OPAL experiments at LEP, and 600 thousand Z decays by the SLID experiment using a polarised beam at SLC. The measurements include cross-sections, forward-backward asymmetries and polarised asymmetries. The mass and width of the Z boson, m(Z) and Gamma(Z), and its couplings to fermions, for example the p parameter and the effective electroweak mixing angle for leptons, are precisely measured: m(Z) = 91.1875 +/- 0.0021 GeV, Gamma(Z) = 2.4952 +/- 0.0023 GeV, rho(l) = 1.0050 +/- 0.0010, sin(2)theta(eff)(lept) = 0.23153 +/- 0.00016. The number of light neutrino species is determined to be 2.9840 +/- 0.0082, in agreement with the three observed generations of fundamental fermions. The results are compared to the predictions of the Standard Model (SM). At the Z-pole, electroweak radiative corrections beyond the running of the QED and QCD coupling constants are observed with a significance of five standard deviations, and in agreement with the Standard Model. Of the many Z-pole measurements, the forward-backward asymmetry in b-quark production shows the largest difference with respect to its SM expectation, at the level of 2.8 standard deviations. Through radiative corrections evaluated in the framework of the Standard Model, the Z-pole data are also used to predict the mass of the top quark, m(t) = 173(+10)(+13) GeV, and the mass of the W boson, m(W) = 80.363 +/- 0.032 GeV. These indirect constraints are compared to the direct measurements, providing a stringent test of the SM. Using in addition the direct measurements of m(t) and m(W), the mass of the as yet unobserved SM Higgs boson is predicted with a relative uncertainty of about 50% and found to be less than 285 GeV at 95% confidence level. (c) 2006 Elsevier B.V. All rights reserved.
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5.
  • Flood, Gabrielle, et al. (author)
  • Efficient Merging of Maps and Detection of Changes
  • 2019
  • In: Image Analysis - 21st Scandinavian Conference, SCIA 2019, Proceedings. - Cham : Springer International Publishing. - 0302-9743 .- 1611-3349. - 9783030202040 ; 11482 LNCS, s. 348-360
  • Conference paper (peer-reviewed)abstract
    • With the advent of cheap sensors and computing capabilities as well as better algorithms it is now possible to do structure from motion using crowd sourced data. Individual estimates of a map can be obtained using structure from motion (SfM) or simultaneous localization and mapping (SLAM) using e.g. images, sound or radio. However the problem of map merging as used for collaborative SLAM needs further attention. In this paper we study the basic principles behind map merging and collaborative SLAM. We develop a method for merging maps – based on a small memory footprint representation of individual maps – in a way that is computationally efficient. We also demonstrate how the same framework can be used to detect changes in the map. This makes it possible to remove inconsistent parts before merging the maps. The methods are tested on both simulated and real data, using both sensor data from radio sensors and from cameras.
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6.
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7.
  • Flood, Gabrielle, et al. (author)
  • Minimal Solvers for Point Cloud Matching with Statistical Deformations
  • 2022
  • In: 2022 26th International Conference on Pattern Recognition (ICPR). - 9781665490634
  • Conference paper (peer-reviewed)abstract
    • An important issue in simultaneous localisation and mapping is how to match and merge individual local maps into one global map. This is addressed within the field of robotics and is crucial for multi-robot SLAM. There are a number of different ways to solve this task depending on the representation of the map. To take advantage of matching and merging methods that allow for deformations of the local maps it is important to find feature matches that capture such deformations. In this paper we present minimal solvers for point cloud matching using statistical deformations. The solvers use either three or four point matches. These solve for either rigid or similarity transformation as well as shape deformation in the direction of the most important modes of variation. Given an initial set of tentative matches based on, for example, feature descriptors or machine learning we use these solvers in a RANSAC loop to remove outliers among the tentative matches. We evaluate the methods on both synthetic and real data and compare them to RANSAC methods based on Procrustes and demonstrate that the proposed methods improve on the current state-of-the-art.
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8.
  • Flood, Victoria A., et al. (author)
  • Evaluating modelled tropospheric columns of CH4, CO, and O3 in the Arctic using ground-based Fourier transform infrared (FTIR) measurements
  • 2024
  • In: Atmospheric Chemistry and Physics. - 1680-7316 .- 1680-7324. ; 24:2, s. 1079-1118
  • Journal article (peer-reviewed)abstract
    • This study evaluates tropospheric columns of methane, carbon monoxide, and ozone in the Arctic simulated by 11 models. The Arctic is warming at nearly 4 times the global average rate, and with changing emissions in and near the region, it is important to understand Arctic atmospheric composition and how it is changing. Both measurements and modelling of air pollution in the Arctic are difficult, making model validation with local measurements valuable. Evaluations are performed using data from five high-latitude ground-based Fourier transform infrared (FTIR) spectrometers in the Network for the Detection of Atmospheric Composition Change (NDACC). The models were selected as part of the 2021 Arctic Monitoring and Assessment Programme (AMAP) report on short-lived climate forcers. This work augments the model-measurement comparisons presented in that report by including a new data source: column-integrated FTIR measurements, whose spatial and temporal footprint is more representative of the free troposphere than in situ and satellite measurements. Mixing ratios of trace gases are modelled at 3-hourly intervals by CESM, CMAM, DEHM, EMEP MSC-W, GEM-MACH, GEOS-Chem, MATCH, MATCH-SALSA, MRI-ESM2, UKESM1, and WRF-Chem for the years 2008, 2009, 2014, and 2015. The comparisons focus on the troposphere (0-7km partial columns) at Eureka, Canada; Thule, Greenland; Ny Ålesund, Norway; Kiruna, Sweden; and Harestua, Norway. Overall, the models are biased low in the tropospheric column, on average by -9.7% for CH4, -21% for CO, and -18% for O3. Results for CH4 are relatively consistent across the 4 years, whereas CO has a maximum negative bias in the spring and minimum in the summer and O3 has a maximum difference centered around the summer. The average differences for the models are within the FTIR uncertainties for approximately 15% of the model-location comparisons.
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9.
  • Gillsjö, David, et al. (author)
  • Polygon Detection for Room Layout Estimation using Heterogeneous Graphs and Wireframes
  • 2023
  • In: Proceedings - 2023 IEEE/CVF International Conference on Computer Vision Workshops, ICCVW 2023. - 9798350307443 ; , s. 1-10
  • Conference paper (peer-reviewed)abstract
    • This paper presents a neural network based semantic plane detection method utilizing polygon representations. The method can for example be used to solve room layout estimations tasks and is built on, combines and further develops several different modules from previous research. The network takes an RGB image and estimates a wireframe as well as a feature space using an hourglass backbone. From these, line and junction features are sampled. The lines and junctions are then represented as an undirected graph, from which polygon representations of the sought planes are obtained. Two different methods for this last step are investigated, where the most promising method is built on a heterogeneous graph transformer. The final output is in all cases a projection of the semantic planes in 2D. The methods are evaluated on the Structured3D dataset and we investigate the performance both using sampled and estimated wireframes. The experiments show the potential of the graph-based method by outperforming state of the art methods in Room Layout estimation in the 2D metrics using synthetic wireframe detections.
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10.
  • Gillsjö, David, et al. (author)
  • Semantic Room Wireframe Detection from a Single View
  • 2022
  • In: 26th International Conference on Pattern Recognition, 2022. - 9781665490634 - 9781665490627 ; , s. 1886-1893
  • Conference paper (peer-reviewed)abstract
    • Reconstruction of indoor surfaces with limited texture information or with repeated textures, a situation common in walls and ceilings, may be difficult with a monocular Structure from Motion system. We propose a Semantic Room Wireframe Detection task to predict a Semantic Wireframe from a single perspective image. Such predictions may be used with shape priors to estimate the Room Layout and aid reconstruction. To train and test the proposed algorithm we create a new set of annotations from the simulated Structured3D dataset. We show qualitatively that the SRW-Net handles complex room geometries better than previous Room Layout Estimation algorithms while quantitatively out-performing the baseline in non-semantic Wireframe Detection.
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