| 1. |
- Barausse, Enrico, et al.
(author)
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Prospects for fundamental physics with LISA
- 2020
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In: General Relativity and Gravitation. - : SPRINGER/PLENUM PUBLISHERS. - 0001-7701 .- 1572-9532. ; 52:8
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Journal article (other academic/artistic)abstract
- In this paper, which is of programmatic rather than quantitative nature, we aim to further delineate and sharpen the future potential of the LISA mission in the area of fundamental physics. Given the very broad range of topics that might be relevant to LISA,we present here a sample of what we view as particularly promising fundamental physics directions. We organize these directions through a "science-first" approach that allows us to classify how LISA data can inform theoretical physics in a variety of areas. For each of these theoretical physics classes, we identify the sources that are currently expected to provide the principal contribution to our knowledge, and the areas that need further development. The classification presented here should not be thought of as cast in stone, but rather as a fluid framework that is amenable to change with the flow of new insights in theoretical physics.
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| 2. |
- Holmes, Robin B., et al.
(author)
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Creation of an anthropomorphic CT head phantom for verification of image segmentation
- 2020
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In: Medical physics (Lancaster). - : Wiley-Blackwell. - 0094-2405 .- 2473-4209. ; 47:6, s. 2380-2391
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Journal article (peer-reviewed)abstract
- Purpose: Many methods are available to segment structural magnetic resonance (MR) images of the brain into different tissue types. These have generally been developed for research purposes but there is some clinical use in the diagnosis of neurodegenerative diseases such as dementia. The potential exists for computed tomography (CT) segmentation to be used in place of MRI segmentation, but this will require a method to verify the accuracy of CT processing, particularly if algorithms developed for MR are used, as MR has notably greater tissue contrast.Methods: To investigate these issues we have created a three-dimensional (3D) printed brain with realistic Hounsfield unit (HU) values based on tissue maps segmented directly from an individual T1 MRI scan of a normal subject. Several T1 MRI scans of normal subjects from the ADNI database were segmented using SPM12 and used to create stereolithography files of different tissues for 3D printing. The attenuation properties of several material blends were investigated, and three suitable formulations were used to print an object expected to have realistic geometry and attenuation properties. A skull was simulated by coating the object with plaster of Paris impregnated bandages. Using two CT scanners, the realism of the phantom was assessed by the measurement of HU values, SPM12 segmentation and comparison with the source data used to create the phantom.Results: Realistic relative HU values were measured although a subtraction of 60 was required to obtain equivalence with the expected values (gray matter 32.9-35.8 phantom, 29.9-34.2 literature). Segmentation of images acquired at different kVps/mAs showed excellent agreement with the source data (Dice Similarity Coefficient 0.79 for gray matter). The performance of two scanners with two segmentation methods was compared, with the scanners found to have similar performance and with one segmentation method clearly superior to the other.Conclusion: The ability to use 3D printing to create a realistic (in terms of geometry and attenuation properties) head phantom has been demonstrated and used in an initial assessment of CT segmentation accuracy using freely available software developed for MRI.
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| 3. |
- Kondo, Masayuki, et al.
(author)
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Are Land-Use Change Emissions in Southeast Asia Decreasing or Increasing?
- 2022
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In: Global Biogeochemical Cycles. - 0886-6236. ; 36:1
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Journal article (peer-reviewed)abstract
- Southeast Asia is a region known for active land-use changes (LUC) over the past 60 years; yet, how trends in net CO2 uptake and release resulting from LUC activities (net LUC flux) have changed through past decades remains uncertain. The level of uncertainty in net LUC flux from process-based models is so high that it cannot be concluded that newer estimates are necessarily more reliable than older ones. Here, we examined net LUC flux estimates of Southeast Asia for the 1980s−2010s from older and newer sets of Dynamic Global Vegetation Model simulations (TRENDY v2 and v7, respectively), and forcing data used for running those simulations, along with two book-keeping estimates (H&N and BLUE). These estimates yielded two contrasting historical LUC transitions, such that TRENDY v2 and H&N showed a transition from increased emissions from the 1980s to 1990s to declining emissions in the 2000s, while TRENDY v7 and BLUE showed the opposite transition. We found that these contrasting transitions originated in the update of LUC forcing data, which reduced the loss of forest area during the 1990s. Further evaluation of remote sensing studies, atmospheric inversions, and the history of forestry and environmental policies in Southeast Asia supported the occurrence of peak emissions in the 1990s and declining thereafter. However, whether LUC emissions continue to decline in Southeast Asia remains uncertain as key processes in recent years, such as conversion of peat forest to oil-palm plantation, are yet to be represented in the forcing data, suggesting a need for further revision.
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| 4. |
- Peano, Daniele, et al.
(author)
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Plant phenology evaluation of CRESCENDO land surface models-Part 1 : Start and end of the growing season
- 2021
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In: Biogeosciences. - : Copernicus GmbH. - 1726-4170 .- 1726-4189. ; 18:7, s. 2405-2428
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Journal article (peer-reviewed)abstract
- Plant phenology plays a fundamental role in land atmosphere interactions, and its variability and variations are an indicator of climate and environmental changes. For this reason, current land surface models include phenology parameterizations and related biophysical and biogeochemical processes. In this work, the climatology of the beginning and end of the growing season, simulated by the land component of seven state-of-The-Art European Earth system models participating in the CMIP6, is evaluated globally against satellite observations. The assessment is performed using the vegetation metric leaf area index and a recently developed approach, named four growing season types. On average, the land surface models show a 0.6-month delay in the growing season start, while they are about 0.5 months earlier in the growing season end. The difference with observation tends to be higher in the Southern Hemisphere compared to the Northern Hemisphere. High agreement between land surface models and observations is exhibited in areas dominated by broadleaf deciduous trees, while high variability is noted in regions dominated by broadleaf deciduous shrubs. Generally, the timing of the growing season end is accurately simulated in about 25% of global land grid points versus 16% in the timing of growing season start. The refinement of phenology parameterization can lead to better representation of vegetation-related energy, water, and carbon cycles in land surface models, but plant phenology is also affected by plant physiology and soil hydrology processes. Consequently, phenology representation and, in general, vegetation modelling is a complex task, which still needs further improvement, evaluation, and multi-model comparison.
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