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Sökning: WFRF:(Lindgren J) > Chalmers tekniska högskola

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1.
  • Burstein, R., et al. (författare)
  • Mapping 123 million neonatal, infant and child deaths between 2000 and 2017
  • 2019
  • Ingår i: Nature. - : Nature Publishing Group. - 0028-0836 .- 1476-4687. ; 574:7778, s. 353-358
  • Tidskriftsartikel (refereegranskat)abstract
    • Since 2000, many countries have achieved considerable success in improving child survival, but localized progress remains unclear. To inform efforts towards United Nations Sustainable Development Goal 3.2—to end preventable child deaths by 2030—we need consistently estimated data at the subnational level regarding child mortality rates and trends. Here we quantified, for the period 2000–2017, the subnational variation in mortality rates and number of deaths of neonates, infants and children under 5 years of age within 99 low- and middle-income countries using a geostatistical survival model. We estimated that 32% of children under 5 in these countries lived in districts that had attained rates of 25 or fewer child deaths per 1,000 live births by 2017, and that 58% of child deaths between 2000 and 2017 in these countries could have been averted in the absence of geographical inequality. This study enables the identification of high-mortality clusters, patterns of progress and geographical inequalities to inform appropriate investments and implementations that will help to improve the health of all populations. © 2019, The Author(s).
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2.
  • Grahn, Maria, 1963, et al. (författare)
  • Description of the global energy systems model GET-RC 6.1
  • 2013
  • Rapport (övrigt vetenskapligt/konstnärligt)abstract
    • To provide a tool for decision makers to understand meeting global energy demand with global energy supply at a minimum cost and in a sustainable way, we have developed a global energy model (GET-RC 6.1) that includes a detailed description of passenger vehicle technology options. The model can be used to better understand the fuel and vehicle technology choices available for passenger vehicles and how these fit into the larger global energy system, where different energy sectors compete for the same limited primary energy sources. The original linear programming Global Energy Transition (GET) model is designed to meet exogenously given energy demand levels, subject to a CO2 constraint, at the lowest global energy system cost (all costs are in US$). The GET model is being developed and extended to address research questions related to the sustainable development of the global energy system. Several different versions of the GET model are available. The aim of this report is to describe the version used in collaboration between staff at Ford Motor Company and Chalmers University of Technology during the period 2008-2013. The model version used, GET-RC 6.1, was developed to address research questions related to light duty passenger vehicles, where R stands for regionalized and C for cars. The report contains a description of the settings that are defined in the model (i.e., the sets, parameters and variables), the equations used in the model, suggestion for how to implement the model step by step, and the mathematical description of the model.
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3.
  • Åkerlund, O., et al. (författare)
  • The similarity renormalization group for three-body interactions in one dimension
  • 2011
  • Ingår i: European Physical Journal A. - : Springer Science and Business Media LLC. - 1434-601X .- 1434-6001. ; 47:10
  • Tidskriftsartikel (refereegranskat)abstract
    • We report on recent progress of the implementation of the similarity renormalization group (SRG) for three-body interactions in a one-dimensional, bosonic model system using the plane-wave basis. We discuss our implementation of the flow equations and show results that confirm that results in the three-body sector remain unchanged by the transformation of the Hamiltonian. We also show how the SRG transformation decouples low- from high-momentum nodes in the three-body sector and therefore simplifies the numerical calculation of observables.
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4.
  • Anselmo, Ana Sofia, 1980-, et al. (författare)
  • Tuning the Vertical Phase Separation in Polyfluorene: Fullerene Blend Films by Polymer Functionalization
  • 2011
  • Ingår i: Chemistry of Materials. - Washington : American Chemical Society (ACS). - 1520-5002 .- 0897-4756. ; 23:9, s. 2295-2302
  • Tidskriftsartikel (refereegranskat)abstract
    • Achieving control over the nanomorphology of blend films of the fullerene derivative [6,6]-phenyl C61-butyric acid methyl ester, PCBM, with light-absorbing conjugated polymers is an important challenge in the development of efficient solution-processed photovoltaics. Here, three new polyfluorene copolymers are presented, tailored for enhanced miscibility with the fullerene through the introduction of polymer segments with modified side chains, which enhance the polymer's polar character. The composition of the spincoated polymer:PCBM films is analyzed with dynamic secondary ion mass spectrometry (dSIMS). The dSIMS depth profiles demonstrate compositional variations perpendicular to the surface plane, as a result of vertical phase separation, directed by the substrate. These variations propagate to a higher degree through the film for the polymers with a larger fraction of modified side chains. The surface composition of the films is studied by Near-edge X-ray absorption fine structure spectroscopy (NEXAFS). Quantitative analysis of the NEXAFS spectra through a linear combination fit with the spectra of the pure components yields the surface composition. The resulting blend ratios reveal polymer-enrichment of the film surface for all three blends, which also becomes stronger as the polar character of the polymer increases. Comparison of the NEXAFS spectra collected with two different sampling depths shows that the vertical composition gradient builds up already in the first nanometers underneath the surface of the films. The results obtained with this new series of polymers shed light on the onset of formation of lamellar structures in thin polymer:PCBM films prepared from highly volatile solvents.
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5.
  • Azar, Christian, 1969, et al. (författare)
  • The feasibility of low CO2 concentration targets and the role of bio-energy with carbon capture and storage (BECCS)
  • 2010
  • Ingår i: Climatic Change. - : Springer Science and Business Media LLC. - 1573-1480 .- 0165-0009. ; 100:1, s. 195-202
  • Tidskriftsartikel (refereegranskat)abstract
    • The United Nations Framework Convention on Climate Change (UNFCCC 1992) calls for stabilization of atmospheric greenhouse gas (GHG) concentrations at a level that would prevent dangerous anthropogenic interference with the climate system. We use three global energy system models to investigate the technological and economic attainability of meeting CO2 concentration targets below current levels. Our scenario studies reveal that while energy portfolios from a broad range of energy technologies are needed to attain low concentrations, negative emission technologies-e.g., biomass energy with carbon capture and storage (BECCS)-significantly enhances the possibility to meet low concentration targets (at around 350 ppm CO2).
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6.
  • Bolin, David, 1983, et al. (författare)
  • Fast estimation of spatially dependent temporal vegetation trends using Gaussian Markov random fields
  • 2009
  • Ingår i: Computational Statistics and Data Analysis. - : Elsevier BV. - 0167-9473. ; 53:8, s. 2885-2896
  • Tidskriftsartikel (refereegranskat)abstract
    • There is a need for efficient methods for estimating trends in spatio-temporal Earth Observation data. A suitable model for such data is a space-varying regression model, where the regression coefficients for the spatial locations are dependent. A second order intrinsic Gaussian Markov Random Field prior is used to specify the spatial covariance structure. Model parameters are estimated using the Expectation Maximisation (EM) algorithm, which allows for feasible computation times for relatively large data sets. Results are illustrated with simulated data sets and real vegetation data from the Sahel area in northern Africa. The results indicate a substantial gain in accuracy compared with methods based on independent ordinary least squares regressions for the individual pixels in the data set. Use of the EM algorithm also gives a substantial performance gain over Markov Chain Monte Carlo-based estimation approaches. © 2008 Elsevier B.V. All rights reserved.
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7.
  • Fan, Zheyong, et al. (författare)
  • GPUMD: A package for constructing accurate machine-learned potentials and performing highly efficient atomistic simulations
  • 2022
  • Ingår i: Journal of Chemical Physics. - : AIP Publishing. - 1089-7690 .- 0021-9606. ; 157:11
  • Tidskriftsartikel (refereegranskat)abstract
    • We present our latest advancements of machine-learned potentials (MLPs) based on the neuroevolution potential (NEP) framework introduced in Fan et al. [Phys. Rev. B 104, 104309 (2021)] and their implementation in the open-source package gpumd. We increase the accuracy of NEP models both by improving the radial functions in the atomic-environment descriptor using a linear combination of Chebyshev basis functions and by extending the angular descriptor with some four-body and five-body contributions as in the atomic cluster expansion approach. We also detail our efficient implementation of the NEP approach in graphics processing units as well as our workflow for the construction of NEP models and demonstrate their application in large-scale atomistic simulations. By comparing to state-of-the-art MLPs, we show that the NEP approach not only achieves above-average accuracy but also is far more computationally efficient. These results demonstrate that the gpumd package is a promising tool for solving challenging problems requiring highly accurate, large-scale atomistic simulations. To enable the construction of MLPs using a minimal training set, we propose an active-learning scheme based on the latent space of a pre-trained NEP model. Finally, we introduce three separate Python packages, viz., gpyumd, calorine, and pynep, that enable the integration of gpumd into Python workflows.
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8.
  • Gudmundsdottir, J. A., et al. (författare)
  • Normal neonatal TREC and KREC levels in early onset juvenile idiopathic arthritis
  • 2023
  • Ingår i: Clinical Immunology. - : Elsevier BV. - 1521-6616 .- 1521-7035. ; 249
  • Tidskriftsartikel (refereegranskat)abstract
    • Objective: Dysregulated central tolerance predisposes to autoimmune diseases. Reduced thymic output as well as compromised central B cell tolerance checkpoints have been proposed in the pathogenesis of juvenile idiopathic arthritis (JIA). The aim of this study was to investigate neonatal levels of T-cell receptor excision circles (TRECs) and kappa-deleting element excision circles (KRECs), as markers of T-and B-cell output at birth, in patients with early onset JIA.Methods: TRECs and KRECs were quantitated by multiplex qPCR from dried blood spots (DBS), collected 2-5 days after birth, in 156 children with early onset JIA and in 312 matched controls.Results: When analysed from neonatal dried blood spots, the median TREC level was 78 (IQR 55-113) in JIA cases and 88 (IQR 57-117) copies/well in controls. The median KREC level was 51 (IQR 35-69) and 53 (IQR 35-74) copies/well, in JIA cases and controls, respectively. Stratification by sex and age at disease onset did not reveal any difference in the levels of TRECs and KRECs.Conclusion: T-and B-cell output at birth, as measured by TREC and KREC levels in neonatal dried blood spots, does not differ in children with early onset JIA compared to controls.
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9.
  • Lindgren Belal, Sarah, et al. (författare)
  • 3D skeletal uptake of F-18 sodium fluoride in PET/CT images is associated with overall survival in patients with prostate cancer
  • 2017
  • Ingår i: EJNMMI Research. - : Springer Science and Business Media LLC. - 2191-219X. ; 7:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Sodium fluoride (NaF) positron emission tomography combined with computer tomography (PET/CT) has shown to be more sensitive than the whole-body bone scan in the detection of skeletal uptake due to metastases in prostate cancer. We aimed to calculate a 3D index for NaF PET/CT and investigate its correlation to the bone scan index (BSI) and overall survival (OS) in a group of patients with prostate cancer. Methods: NaF PET/CT and bone scans were studied in 48 patients with prostate cancer. Automated segmentation of the thoracic and lumbar spines, sacrum, pelvis, ribs, scapulae, clavicles, and sternum were made in the CT images. Hotspots in the PET images were selected using both a manual and an automated method. The volume of each hotspot localized in the skeleton in the corresponding CT image was calculated. Two PET/CT indices, based on manual (manual PET index) and automatic segmenting using a threshold of SUV 15 (automated PET15 index), were calculated by dividing the sum of all hotspot volumes with the volume of all segmented bones. BSI values were obtained using a software for automated calculations. Results: BSI, manual PET index, and automated PET15 index were all significantly associated with OS and concordance indices were 0.68, 0.69, and 0.70, respectively. The median BSI was 0.39 and patients with a BSI > 0.39 had a significantly shorter median survival time than patients with a BSI 0.53 had a significantly shorter median survival time than patients with a manual PET index 0.11 had a significantly shorter median survival time than patients with an automated PET15 index
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10.
  • Lindgren Belal, Sarah, et al. (författare)
  • Deep learning for segmentation of 49 selected bones in CT scans: First step in automated PET/CT-based 3D quantification of skeletal metastases
  • 2019
  • Ingår i: European Journal of Radiology. - : Elsevier BV. - 0720-048X .- 1872-7727. ; 113, s. 89-95
  • Tidskriftsartikel (refereegranskat)abstract
    • Purpose: The aim of this study was to develop a deep learning-based method for segmentation of bones in CT scans and test its accuracy compared to manual delineation, as a first step in the creation of an automated PET/CT-based method for quantifying skeletal tumour burden. Methods: Convolutional neural networks (CNNs) were trained to segment 49 bones using manual segmentations from 100 CT scans. After training, the CNN-based segmentation method was tested on 46 patients with prostate cancer, who had undergone 18 F-choline-PET/CT and 18 F-NaF PET/CT less than three weeks apart. Bone volumes were calculated from the segmentations. The network's performance was compared with manual segmentations of five bones made by an experienced physician. Accuracy of the spatial overlap between automated CNN-based and manual segmentations of these five bones was assessed using the Sørensen-Dice index (SDI). Reproducibility was evaluated applying the Bland-Altman method. Results: The median (SD) volumes of the five selected bones were by CNN and manual segmentation: Th7 41 (3.8) and 36 (5.1), L3 76 (13) and 75 (9.2), sacrum 284 (40) and 283 (26), 7th rib 33 (3.9) and 31 (4.8), sternum 80 (11) and 72 (9.2), respectively. Median SDIs were 0.86 (Th7), 0.85 (L3), 0.88 (sacrum), 0.84 (7th rib) and 0.83 (sternum). The intraobserver volume difference was less with CNN-based than manual approach: Th7 2% and 14%, L3 7% and 8%, sacrum 1% and 3%, 7th rib 1% and 6%, sternum 3% and 5%, respectively. The average volume difference measured as ratio volume difference/mean volume between the two CNN-based segmentations was 5–6% for the vertebral column and ribs and ≤3% for other bones. Conclusion: The new deep learning-based method for automated segmentation of bones in CT scans provided highly accurate bone volumes in a fast and automated way and, thus, appears to be a valuable first step in the development of a clinical useful processing procedure providing reliable skeletal segmentation as a key part of quantification of skeletal metastases.
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