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- Glasbey, JC, et al.
(author)
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- 2021
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swepub:Mat__t
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- Pöntinen, M., et al.
(author)
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Euclid: Identification of asteroid streaks in simulated images using deep learning
- 2023
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In: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 679
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Journal article (peer-reviewed)abstract
- The material composition of asteroids is an essential piece of knowledge in the quest to understand the formation and evolution of the Solar System. Visual to near-infrared spectra or multiband photometry is required to constrain the material composition of asteroids, but we currently have such data, especially in the near-infrared wavelengths, for only a limited number of asteroids. This is a significant limitation considering the complex orbital structures of the asteroid populations. Up to 150 000 asteroids will be visible in the images of the upcoming ESA Euclid space telescope, and the instruments of Euclid will offer multiband visual to near-infrared photometry and slitless near-infrared spectra of these objects. Most of the asteroids will appear as streaks in the images. Due to the large number of images and asteroids, automated detection methods are needed. A non-machine-learning approach based on the Streak Det software was previously tested, but the results were not optimal for short and/or faint streaks. We set out to improve the capability to detect asteroid streaks in Euclid images by using deep learning. We built, trained, and tested a three-step machine-learning pipeline with simulated Euclid images. First, a convolutional neural network (CNN) detected streaks and their coordinates in full images, aiming to maximize the completeness (recall) of detections. Then, a recurrent neural network (RNN) merged snippets of long streaks detected in several parts by the CNN. Lastly, gradient-boosted trees (XGBoost) linked detected streaks between different Euclid exposures to reduce the number of false positives and improve the purity (precision) of the sample. The deep-learning pipeline surpasses the completeness and reaches a similar level of purity of a non-machine-learning pipeline based on the StreakDet software. Additionally, the deep-learning pipeline can detect asteroids 0.25–0.5 magnitudes fainter than StreakDet. The deep-learning pipeline could result in a 50% increase in the number of detected asteroids compared to the StreakDet software. There is still scope for further refinement, particularly in improving the accuracy of streak coordinates and enhancing the completeness of the final stage of the pipeline, which involves linking detections across multiple exposures.
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| 7. |
- Adams, D., et al.
(author)
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Patisiran, an RNAi Therapeutic, for Hereditary Transthyretin Amyloidosis
- 2018
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In: New England Journal of Medicine. - : Massachusetts Medical Society. - 0028-4793 .- 1533-4406. ; 379:1, s. 11-21
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Journal article (peer-reviewed)abstract
- BACKGROUND: Patisiran, an investigational RNA interference therapeutic agent, specifically inhibits hepatic synthesis of transthyretin.METHODS: In this phase 3 trial, we randomly assigned patients with hereditary transthyretin amyloidosis with polyneuropathy, in a 2:1 ratio, to receive intravenous patisiran (0.3 mg per kilogram of body weight) or placebo once every 3 weeks. The primary end point was the change from baseline in the modified Neuropathy Impairment Score+7 (mNIS+7; range, 0 to 304, with higher scores indicating more impairment) at 18 months. Other assessments included the Norfolk Quality of Life-Diabetic Neuropathy (Norfolk QOL-DN) questionnaire (range, -4 to 136, with higher scores indicating worse quality of life), 10-m walk test (with gait speed measured in meters per second), and modified body-mass index (modified BMI, defined as [weight in kilograms divided by square of height in meters] x albumin level in grams per liter; lower values indicated worse nutritional status).RESULTS: A total of 225 patients underwent randomization (148 to the patisiran group and 77 to the placebo group). The mean (+/- SD) mNIS+7 at baseline was 80.9 +/- 41.5 in the patisiran group and 74.6 +/- 37.0 in the placebo group; the least-squares mean (+/- SE) change from baseline was -6.0 +/- 1.7 versus 28.0 +/- 2.6 (difference, -34.0 points; P<0.001) at 18 months. The mean (+/- SD) baseline Norfolk QOL-DN score was 59.6 +/- 28.2 in the patisiran group and 55.5 +/- 24.3 in the placebo group; the least-squares mean (+/- SE) change from baseline was -6.7 +/- 1.8 versus 14.4 +/- 2.7 (difference, -21.1 points; P<0.001) at 18 months. Patisiran also showed an effect on gait speed and modified BMI. At 18 months, the least-squares mean change from baseline in gait speed was 0.08 +/- 0.02 m per second with patisiran versus -0.24 +/- 0.04 m per second with placebo (difference, 0.31 m per second; P<0.001), and the least-squares mean change from baseline in the modified BMI was -3.7 +/- 9.6 versus -119.4 +/- 14.5 (difference, 115.7; P<0.001). Approximately 20% of the patients who received patisiran and 10% of those who received placebo had mild or moderate infusion-related reactions; the overall incidence and types of adverse events were similar in the two groups.CONCLUSIONS: In this trial, patisiran improved multiple clinical manifestations of hereditary transthyretin amyloidosis.
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- Green, Jonathan M. H., et al.
(author)
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Research priorities for managing the impacts and dependencies of business upon food, energy, water and the environment
- 2017
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In: Sustainability Science. - : Springer Science and Business Media LLC. - 1862-4065 .- 1862-4057. ; 12:2, s. 319-331
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Journal article (peer-reviewed)abstract
- Delivering access to sufficient food, energy and water resources to ensure human wellbeing is a major concern for governments worldwide. However, it is crucial to account for the 'nexus' of interactions between these natural resources and the consequent implications for human wellbeing. The private sector has a critical role in driving positive change towards more sustainable nexus management and could reap considerable benefits from collaboration with researchers to devise solutions to some of the foremost sustainability challenges of today. Yet opportunities are missed because the private sector is rarely involved in the formulation of deliverable research priorities. We convened senior research scientists and influential business leaders to collaboratively identify the top forty questions that, if answered, would best help companies understand and manage their food-energy-water-environment nexus dependencies and impacts. Codification of the top order nexus themes highlighted research priorities around development of pragmatic yet credible tools that allow businesses to incorporate nexus interactions into their decision-making; demonstration of the business case for more sustainable nexus management; identification of the most effective levers for behaviour change; and understanding incentives or circumstances that allow individuals and businesses to take a leadership stance. Greater investment in the complex but productive relations between the private sector and research community will create deeper and more meaningful collaboration and cooperation.
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| 12. |
- Rabe, Patrick, et al.
(author)
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X-ray free-electron laser studies reveal correlated motion during isopenicillin N synthase catalysis
- 2021
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In: Science Advances. - : American Association for the Advancement of Science (AAAS). - 2375-2548. ; 7:34
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Journal article (peer-reviewed)abstract
- Isopenicillin N synthase (IPNS) catalyzes the unique reaction of L-delta-(alpha-aminoadipoyl)-L-cysteinyl-D-valine (ACV) with dioxygen giving isopenicillin N (IPN), the precursor of all natural penicillins and cephalosporins. X-ray free-electron laser studies including time-resolved crystallography and emission spectroscopy reveal how reaction of IPNS:Fe(II):ACV with dioxygen to yield an Fe(III) superoxide causes differences in active site volume and unexpected conformational changes that propagate to structurally remote regions. Combined with solution studies, the results reveal the importance of protein dynamics in regulating intermediate conformations during conversion of ACV to IPN. The results have implications for catalysis by multiple IPNS-related oxygenases, including those involved in the human hypoxic response, and highlight the power of serial femtosecond crystallography to provide insight into long-range enzyme dynamics during reactions presently impossible for nonprotein catalysts.
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| 13. |
- O'Riordan, C. M., et al.
(author)
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Galaxy mass profiles from strong lensing I : the circular power-law model
- 2019
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In: Monthly notices of the Royal Astronomical Society. - : Oxford University Press (OUP). - 0035-8711 .- 1365-2966. ; 487:4, s. 5143-5154
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Journal article (peer-reviewed)abstract
- In this series of papers, we develop a formalism for constraining mass profiles in strong gravitational lenses with extended images, using fluxes in addition to positional information. We start in this paper with a circular power-law profile and show that the slope gamma is uniquely determined by only two observables: the flux ratio f(1)/f(2) and the image position ratio theta(1)/theta(2) of the two images. We derive an analytic expression relating these two observables to the slope, a result that does not depend on the Einstein angle or the structure or brightness of the source. We then find an expression for the uncertainty on the slope sigma(gamma) that depends only on the position ratio theta(1)/theta(2) and the total signal-to-noise ratio (S/N) in the images. For example, in a system with position ratio theta(1)/theta(2)= 0.5, S/N=100, and gamma= 2 we find that gamma is constrained to a precision of +/- 0.03. We then test these results against a series of mock observations. We invert the images and fit an 11-parameter model, including ellipticity and position angle for both lens and source and measure the uncertainty on gamma. We find agreement with the theoretical estimate for all mock observations. In future papers, we will examine the radial range of the galaxy over which the constraint on the slope applies, and extend the analysis to elliptical lenses.
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| 14. |
- O'Riordan, C. M., et al.
(author)
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Galaxy mass profiles from strong lensing II : The elliptical power-law model
- 2020
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In: Monthly notices of the Royal Astronomical Society. - : Oxford University Press (OUP). - 0035-8711 .- 1365-2966. ; 496:3, s. 3424-3435
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Journal article (peer-reviewed)abstract
- We present a systematic analysis of the constraints σγ on the mass profile slope γ obtainable when fitting a singular power-law ellipsoid model to a typical strong lensing observation of an extended source. These results extend our previous analysis of circular systems, Paper I. We draw our results from 676 mock observations covering a range of image configurations, each created with a fixed signal to noise ratio S = 100 in the images. We analyse the results using a combination of theory and a simplified model which identifies the contribution to the constraints of the individual fluxes and positions in each of the lensed images. The main results are: 1. For any lens ellipticity, the constraints σγ for two image systems are well described by the results of Paper I, transformed to elliptical coordinates; 2. We derive an analytical expression for σγ for systems with the source aligned with the axis of the lens; 3. For both two-image systems and aligned systems, σγ is limited by the flux uncertainties; 4. The constraints for off-axis four-image systems are a factor of two to eight better, depending on source size, than for two-image systems, and improve with increasing lens ellipticity. We show that the constraints on γ in these systems derive from the complementary positional information of the images alone, without using flux. The complementarity improves as the offset of the source from the axis increases, such that the best constraints σγ < 0.01, for S = 100, occur when the source approaches the caustic.
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| 15. |
- O'Riordan, C. M., et al.
(author)
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Galaxy mass profiles from strong lensing - III. The two-dimensional broken power-law model
- 2021
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In: Monthly notices of the Royal Astronomical Society. - : Oxford University Press (OUP). - 0035-8711 .- 1365-2966. ; 501:3, s. 3687-3694
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Journal article (peer-reviewed)abstract
- When modelling strong gravitational lenses, i.e. where there are multiple images of the same source, the most widely used parametrization for the mass profile in the lens galaxy is the singular power-law model rho(r)proportional to r(-gamma). This model may be insufficiently flexible for very accurate work, for example, measuring the Hubble constant based on time delays between multiple images. Here, we derive the lensing properties - deflection angle, shear, and magnification - of a more adaptable model where the projected mass surface density is parametrized as a continuous two-dimensional broken power law (2DBPL). This elliptical 2DBPL model is characterized by power-law slopes t(1) and t(2) either side of the break radius theta(B). The key to the 2DBPL model is the derivation of the lensing properties of the truncated power-law (TPL) model, where the surface density is a power law out to the truncation radius theta(T) and zero beyond. This TPL model is also useful by itself. We create mock observations of lensing by a TPL profile where the images form outside the truncation radius, so there is no mass in the annulus covered by the images. We then show that the slope of the profile interior to the images may be accurately recovered for lenses of moderate ellipticity. This demonstrates that the widely held notion that lensing measures the slope of the mass profile in the annulus of the images, and is insensitive to the mass distribution at radii interior to the images, is incorrect.
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