| 1. |
- Aad, G, et al.
(författare)
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- 2015
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swepub:Mat__t
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| 2. |
- Duarte-Cabral, A., et al.
(författare)
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The SEDIGISM survey: Molecular clouds in the inner Galaxy
- 2021
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Ingår i: Monthly Notices of the Royal Astronomical Society. - : Oxford University Press (OUP). - 0035-8711 .- 1365-2966. ; 500:3, s. 3027-3049
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Forskningsöversikt (refereegranskat)abstract
- We use the 13CO(2-1) emission from the SEDIGISM (Structure, Excitation, and Dynamics of the Inner Galactic InterStellar Medium) high-resolution spectral-line survey of the inner Galaxy, to extract the molecular cloud population with a large dynamic range in spatial scales, using the Spectral Clustering for Interstellar Molecular Emission Segmentation (SCIMES) algorithm. This work compiles a cloud catalogue with a total of 10 663 molecular clouds, 10 300 of which we were able to assign distances and compute physical properties. We study some of the global properties of clouds using a science sample, consisting of 6664 well-resolved sources and for which the distance estimates are reliable. In particular, we compare the scaling relations retrieved from SEDIGISM to those of other surveys, and we explore the properties of clouds with and without high-mass star formation. Our results suggest that there is no single global property of a cloud that determines its ability to form massive stars, although we find combined trends of increasing mass, size, surface density, and velocity dispersion for the sub-sample of clouds with ongoing high-mass star formation. We then isolate the most extreme clouds in the SEDIGISM sample (i.e. clouds in the tails of the distributions) to look at their overall Galactic distribution, in search for hints of environmental effects. We find that, for most properties, the Galactic distribution of the most extreme clouds is only marginally different to that of the global cloud population. The Galactic distribution of the largest clouds, the turbulent clouds and the high-mass star-forming clouds are those that deviate most significantly from the global cloud population. We also find that the least dynamically active clouds (with low velocity dispersion or low virial parameter) are situated further afield, mostly in the least populated areas. However, we suspect that part of these trends may be affected by some observational biases (such as completeness and survey limitations), and thus require further follow up work in order to be confirmed.
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| 3. |
- Urquhart, J. S., et al.
(författare)
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SEDIGISM-ATLASGAL: Dense gas fraction and star formation efficiency across the Galactic disc
- 2021
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Ingår i: Monthly Notices of the Royal Astronomical Society. - : Oxford University Press (OUP). - 0035-8711 .- 1365-2966. ; 500:3, s. 3050-3063
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Tidskriftsartikel (refereegranskat)abstract
- By combining two surveys covering a large fraction of the molecular material in the Galactic disc, we investigate the role spiral arms play in the star formation process. We have matched clumps identified by APEX Telescope Large Area Survey of the Galaxy (ATLASGAL) with their parental giant molecular clouds (GMCs) as identified by SEDIGISM, and use these GMC masses, the bolometric luminosities, and integrated clump masses obtained in a concurrent paper to estimate the dense gas fractions (DGFgmc = ΣMclump/Mgmc) and the instantaneous star formation efficiencies (i.e. SFEgmc = ΣLclump/Mgmc). We find that the molecular material associated with ATLASGAL clumps is concentrated in the spiral arms (∼60 per cent found within ±10 km s-1 of an arm).We have searched for variations in the values of these physical parameters with respect to their proximity to the spiral arms, but find no evidence for any enhancement that might be attributable to the spiral arms. The combined results from a number of similar studies based on different surveys indicate that, while spiral-arm location plays a role in cloud formation and HI to H2 conversion, the subsequent star formation processes appear to depend more on local environment effects. This leads us to conclude that the enhanced star formation activity seen towards the spiral arms is the result of source crowding rather than the consequence of any physical process.
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| 4. |
- Paris, Bas, et al.
(författare)
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A Review of the Current Practices of Bioeconomy Education and Training in the EU
- 2023
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Ingår i: Sustainability. - : MDPI. - 2071-1050. ; 15:2
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Forskningsöversikt (refereegranskat)abstract
- This study conducts a review of the current practices of bioeconomy education and training in the EU; as well as the associated methodologies; techniques and approaches. In recent years; considerable efforts have been made towards developing appropriate bioeconomy education and training programs in order to support a transition towards a circular bioeconomy. This review separates bioeconomy education approaches along: higher education and academic approaches, vocational education and training (VET) and practical approaches, short-term training and education approaches, and other approaches. A range of training methodologies and techniques and pedagogical approaches are identified. The main commonalities found amongst these approaches are that they are generally problem based and interdisciplinary, and combine academic and experiential. Higher education approaches are generally based on traditional lecture/campus-based formats with some experiential approaches integrated. In contrast, VET approaches often combine academic and practical learning methods while focusing on developing practical skills. A range of short-term courses and other approaches to bioeconomy education are also reviewed.
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| 5. |
- Ramos, Lucas P., et al.
(författare)
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A wavelength-resolution sar change detection method based on image stack through robust principal component analysis
- 2021
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Ingår i: Remote Sensing. - : MDPI AG. - 2072-4292. ; 13:5, s. 1-16
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Tidskriftsartikel (refereegranskat)abstract
- Recently, it was demonstrated that low-frequency wavelength-resolution synthetic aperture radar (SAR) images could be considered to follow an additive mixing model due to their backscatter characteristics. This simplification allows for the use of source separation methods, such as robust principal component analysis (RPCA) via principal component pursuit (PCP), for detecting changes in those images. In this manuscript, a change detection method for wavelength-resolution SAR images based on image stack through RPCA is proposed. The method aims to explore both the temporal and flight heading diversity of a set of wavelength-resolution multitemporal SAR images in order to detect concealed targets in forestry areas. A heuristic based on three rules for better exploring the RPCA results is introduced, and a new configurable parameter for false alarm reduction based on the analysis of image windows is proposed. The method is evaluated using real data obtained from measurements of the ultrawideband (UWB) very high-frequency (VHF) SAR system CARABAS-II. Experiments for stacks of four and seven reference images are conducted, and the use of reference images acquired with different flight headings is explored. The results indicate that a gain in performance can be achieved by using large image stacks containing, at least, one image of each possible flight heading of the data set, which can result in a probability of detection (PD) above 99% for a false alarm rate (FAR) as low as one false alarm per three square kilometers. Furthermore, it is demonstrated that high PD and low FAR can be achieved, also considering images from similar flight headings as reference images. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
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| 6. |
- Ramos, Lucas P., et al.
(författare)
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Change Detection in Wavelength-Resolution SAR Image Stack Based on Tensor Robust PCA
- 2024
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Ingår i: IEEE Geoscience and Remote Sensing Letters. - : Institute of Electrical and Electronics Engineers (IEEE). - 1545-598X .- 1558-0571.
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Tidskriftsartikel (refereegranskat)abstract
- Wavelength-resolution (WR) synthetic aperture radar (SAR) change detection (CD) has been used to detect concealed targets in forestry areas. However, most proposed methods are generally based on matrix or vector analyses and, therefore, do not exploit information embedded in multidimensional data. In this letter, a CD method for WR SAR image stacks based on tensor robust principal component analysis (TRPCA) is proposed. The proposed CD method used the new tensor nuclear norm induced by the definition of the tensor-tensor product to exploit temporal and spatial information contained in the image stack. To assess the performance of the proposed method, we considered SAR images obtained by the very high frequency (VHF) WR CARABAS-II SAR system. Experiments for three different stack sizes show that a significant performance gain can be achieved when large image stacks are considered. The proposed CD method performs better in terms of probability of detection (PD) and false alarm rate (FAR) than the other five CD methods in VHF WR SAR images, including one based on matrix robust principal component analysis (RPCA). In a particular setting, it achieves a PD of 99% and a FAR of 0.028 false alarms per km2. Authors
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| 7. |
- Ramos, Lucas P., et al.
(författare)
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Robust Principal Component Analysis Techniques for Ground Scene Estimation in SAR Imagery
- 2023
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Ingår i: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. - : Institute of Electrical and Electronics Engineers (IEEE). - 1939-1404 .- 2151-1535. ; 16, s. 9697-9710
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Tidskriftsartikel (refereegranskat)abstract
- Robust principal component analysis (RPCA) has been widely used for processing and interpreting high-dimensional data in different applications such as data classification, face recognition, video analytics, and recommendation system design. However, the advancement of multisensor-based technologies and the emergence of large data sets have highlighted the limitations of traditional matrix-based models, which have paved the way for higher-order extensions such as tensor RPCA (TRPCA) techniques. These signal separation techniques can be useful for ground scene estimation (GSE) in synthetic aperture radar (SAR) imagery. GSE estimates the clutter-plus-noise content in the scene, and therefore, change detection (CD) methods can benefit, reducing the number of false alarms (FA). This paper presents two new GSE methods for SAR imagery based on robust PCA techniques. The first proposed method uses the RPCA via Principal Component Pursuit (PCP) to obtain the GSE-RPCA. The second method uses TRPCA via New Tensor Nuclear Norm (TNN) to obtain the GSE-TRPCA. The methodology allows the GSE to be obtained through a generalized regularization parameter. The alternating direction method of multipliers (ADMM) algorithm is utilized to solve both optimization problems. Experimental results are evaluated considering real SAR imagery from two data sets acquired with the CARABAS II and ALOS PALSAR systems, respectively. Additionally, the proposed techniques were evaluated under several input characteristics, e.g., eight-image stacks and image pairs. Both GSE techniques are more robust to outliers and missing data when compared to existing solutions found in the literature. Finally, GSE-TRPCA achieved a minimum-square error performance of 0.0018 for some of the evaluated scenarios.
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