| 1. |
- Dainotti, Maria Giovanna, et al.
(författare)
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Gamma-Ray Bursts as Distance Indicators by a Statistical Learning Approach
- 2024
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Ingår i: Astrophysical Journal Letters. - 2041-8205. ; 967:2
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Tidskriftsartikel (refereegranskat)abstract
- Gamma-ray bursts (GRBs) can be probes of the early Universe, but currently, only 26% of GRBs observed by the Neil Gehrels Swift Observatory have known redshifts (z) due to observational limitations. To address this, we estimated the GRB redshift (distance) via a supervised statistical learning model that uses optical afterglow observed by Swift and ground-based telescopes. The inferred redshifts are strongly correlated (a Pearson coefficient of 0.93) with the observed redshifts, thus proving the reliability of this method. The inferred and observed redshifts allow us to estimate the number of GRBs occurring at a given redshift (GRB rate) to be 8.47-9 yr−1 Gpc−1 for 1.9 < z < 2.3. Since GRBs come from the collapse of massive stars, we compared this rate with the star formation rate, highlighting a discrepancy of a factor of 3 at z < 1.
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| 2. |
- Dainotti, Maria Giovanna, et al.
(författare)
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Inferring the Redshift of More than 150 GRBs with a Machine-learning Ensemble Model
- 2024
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Ingår i: Astrophysical Journal, Supplement Series. - 0067-0049. ; 271:1
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Tidskriftsartikel (refereegranskat)abstract
- Gamma-ray bursts (GRBs), due to their high luminosities, are detected up to a redshift of 10, and thus have the potential to be vital cosmological probes of early processes in the Universe. Fulfilling this potential requires a large sample of GRBs with known redshifts, but due to observational limitations, only 11% have known redshifts (z). There have been numerous attempts to estimate redshifts via correlation studies, most of which have led to inaccurate predictions. To overcome this, we estimated GRB redshift via an ensemble-supervised machine-learning (ML) model that uses X-ray afterglows of long-duration GRBs observed by the Neil Gehrels Swift Observatory. The estimated redshifts are strongly correlated (a Pearson coefficient of 0.93) and have an rms error, namely, the square root of the average squared error <Δz2>, of 0.46 with the observed redshifts showing the reliability of this method. The addition of GRB afterglow parameters improves the predictions considerably by 63% compared to previous results in peer-reviewed literature. Finally, we use our ML model to infer the redshifts of 154 GRBs, which increase the known redshifts of long GRBs with plateaus by 94%, a significant milestone for enhancing GRB population studies that require large samples with redshift.
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| 3. |
- Dainotti, Maria Giovanna, et al.
(författare)
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Shedding new light on the Hubble constant tension through Supernovae Ia
- 2024
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Ingår i: Proceedings of Science. ; 447
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Konferensbidrag (refereegranskat)abstract
- The standard cosmological model, the ΓCDM model, is the most suitable description for our universe. This framework can explain the accelerated expansion phase of the universe but still is not immune to open problems when it comes to the comparison with observations. One of the most critical issues is the so-called Hubble constant (H0) tension, namely, the difference of about 5σ as an average between the value of H0estimated locally and the cosmological value measured from the Last Scattering Surface. The value of this tension changes from 4 to 6 σ according to the data used. The current analysis explores the H0tension in the Pantheon sample (PS) of SNe Ia. Through the division of the PS in 3 and 4 bins, the value of H0is estimated for each bin and all the values are fitted with a decreasing function of the redshift (z). Remarkably, H0undergoes a slow decreasing evolution with z, having an evolutionary coefficient compatible with zero up to 5.8σ. If this trend is not caused by hidden astrophysical biases or z-selection effects, then the f (R) modified theories of gravity represent a valid model for explaining such a trend.
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| 4. |
- Fiałkowska-Filipek, Małgorzata, 1985-, et al.
(författare)
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Beyond the box: enhancing the circular economy strategies through smart packaging
- 2024
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Konferensbidrag (refereegranskat)abstract
- This study examines the transition from linear to circular packaging, highlighting the role of smart packaging technologies in enhancing circular economy strategies. We explore the challenges and technological facilitators in adopting circular packaging through an embedded case study approach involving Scandinavian manufacturers. Our findings suggest that smart packaging, equipped with sensors and digital capabilities, helps address supply chain complexities and regulatory compliance issues. It also has the potential to improve consumer acceptance and foster collaboration among stakeholders. The paper underscores the potential of integrating smart technologies into packaging to accelerate sustainable practices within the CE framework.
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| 5. |
- Cooper, Nathaniel, et al.
(författare)
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Fermi LAT AGN classification using supervised machine learning
- 2023
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Ingår i: Monthly Notices of the Royal Astronomical Society. - 0035-8711. ; 525:2, s. 1731-1745
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Tidskriftsartikel (refereegranskat)abstract
- Classifying active galactic nuclei (AGNs) is a challenge, especially for BL Lacertae objects (BLLs), which are identified by their weak emission line spectra. To address the problem of classification, we use data from the fourth Fermi Catalog, Data Release 3. Missing data hinder the use of machine learning to classify AGNs. A previous paper found that Multivariate Imputation by Chain Equations (MICE) imputation is useful for estimating missing values. Since many AGNs have missing redshift and the highest energy, we use data imputation with MICE and k-nearest neighbours (kNN) algorithm to fill in these missing variables. Then, we classify AGNs into the BLLs or the flat spectrum radio quasars (FSRQs) using the SuperLearner, an ensemble method that includes several classification algorithms like logistic regression, support vector classifiers, Random Forest, Ranger Random Forest, multivariate adaptive regression spline (MARS), Bayesian regression, and extreme gradient boosting. We find that a SuperLearner model using MARS regression and Random Forest algorithms is 91.1 per cent accurate for kNN-imputed data and 91.2 per cent for MICE-imputed data. Furthermore, the kNN-imputed SuperLearner model predicts that 892 of the 1519 unclassified blazars are BLLs and 627 are FSRQs, while the MICE-imputed SuperLearner model predicts 890 BLLs and 629 FSRQs in the unclassified set. Thus, we can conclude that both imputation methods work efficiently and with high accuracy and that our methodology ushers the way for using SuperLearner as a novel classification method in the AGN community and, in general, in the astrophysics community.
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| 6. |
- Dainotti, Maria Giovanna, et al.
(författare)
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Reducing the Uncertainty on the Hubble Constant up to 35% with an Improved Statistical Analysis : Different Best-fit Likelihoods for Type Ia Supernovae, Baryon Acoustic Oscillations, Quasars, and Gamma-Ray Bursts
- 2023
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Ingår i: Astrophysical Journal. - 0004-637X. ; 951:1
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Tidskriftsartikel (refereegranskat)abstract
- Cosmological models and their parameters are widely debated, especially about whether the current discrepancy between the values of the Hubble constant, H 0, obtained by Type Ia supernovae (SNe Ia) and the Planck data from the cosmic microwave background radiation could be alleviated when alternative cosmological models are considered. Thus, combining high-redshift probes, such as gamma-ray bursts (GRBs) and quasi-stellar objects (QSOs, or quasars), together with baryon acoustic oscillations and SNe Ia is important to assess the viability of these alternative models and whether they can cast further light on the Hubble tension. In this work, for GRBs, we use a three-dimensional relation between the peak prompt luminosity, the rest-frame time at the end of the X-ray plateau, and its corresponding luminosity in X-rays: the 3D Dainotti fundamental plane relation. Regarding QSOs, we use the Risaliti−Lusso relation among the UV and X-ray luminosities for a sample of 2421 sources. We correct both the QSO and GRB relations by accounting for selection and evolutionary effects with a reliable statistical method. We here use both the traditional Gaussian likelihoods and the new best-fit likelihoods to infer cosmological parameters of nonflat Lambda cold dark matter (ΛCDM) and flat wCDM models. We obtain for all the parameters reduced uncertainties, up to 35% for H 0, when applying the new likelihoods in place of the Gaussian ones. Our results remain consistent with a flat ΛCDM model, although with a shift of the dark energy parameter w toward w < −1 and a curvature density parameter toward Ωk < 0.
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| 7. |
- Marto, João Pedro, et al.
(författare)
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Safety and Outcome of Revascularization Treatment in Patients With Acute Ischemic Stroke and COVID-19: The Global COVID-19 Stroke Registry.
- 2023
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Ingår i: Neurology. - 1526-632X. ; 100:7
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Tidskriftsartikel (refereegranskat)abstract
- COVID-19-related inflammation, endothelial dysfunction, and coagulopathy may increase the bleeding risk and lower the efficacy of revascularization treatments in patients with acute ischemic stroke (AIS). We aimed to evaluate the safety and outcomes of revascularization treatments in patients with AIS and COVID-19.This was a retrospective multicenter cohort study of consecutive patients with AIS receiving intravenous thrombolysis (IVT) and/or endovascular treatment (EVT) between March 2020 and June 2021 tested for severe acute respiratory syndrome coronavirus 2 infection. With a doubly robust model combining propensity score weighting and multivariate regression, we studied the association of COVID-19 with intracranial bleeding complications and clinical outcomes. Subgroup analyses were performed according to treatment groups (IVT-only and EVT).Of a total of 15,128 included patients from 105 centers, 853 (5.6%) were diagnosed with COVID-19; of those, 5,848 (38.7%) patients received IVT-only and 9,280 (61.3%) EVT (with or without IVT). Patients with COVID-19 had a higher rate of symptomatic intracerebral hemorrhage (SICH) (adjusted OR 1.53; 95% CI 1.16-2.01), symptomatic subarachnoid hemorrhage (SSAH) (OR 1.80; 95% CI 1.20-2.69), SICH and/or SSAH combined (OR 1.56; 95% CI 1.23-1.99), 24-hour mortality (OR 2.47; 95% CI 1.58-3.86), and 3-month mortality (OR 1.88; 95% CI 1.52-2.33). Patients with COVID-19 also had an unfavorable shift in the distribution of the modified Rankin score at 3 months (OR 1.42; 95% CI 1.26-1.60).Patients with AIS and COVID-19 showed higher rates of intracranial bleeding complications and worse clinical outcomes after revascularization treatments than contemporaneous non-COVID-19 patients receiving treatment. Current available data do not allow direct conclusions to be drawn on the effectiveness of revascularization treatments in patients with COVID-19 or to establish different treatment recommendations in this subgroup of patients with ischemic stroke. Our findings can be taken into consideration for treatment decisions, patient monitoring, and establishing prognosis.The study was registered under ClinicalTrials.gov identifier NCT04895462.
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| 8. |
- Rakoczy, Łukasz, et al.
(författare)
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The role of the strengthening phases on the HAZ liquation cracking in a cast Ni-based superalloy used in industrial gas turbines
- 2023
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Ingår i: Archives of Civil and Mechanical Engineering. - : Springer. - 1644-9665. ; 23:2
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Tidskriftsartikel (refereegranskat)abstract
- This work presents the influence of microstructural constituents on liquation crack formation in the cast Ni-based superalloy, René 108. The investigation was divided into three parts: characterisation of the material's microstructure in pre-weld condition, hot ductility studies and analysis of liquation cracking induced by the gas tungsten arc welding process. Using advanced electron microscopy techniques it is shown that the base material in pre-weld condition is characterised by a complex microstructure. The phases identified in René 108 include γ matrix, γ' precipitates, MC and M23C6 carbides, and M5B3 borides. Based on Gleeble testing, it was found that René 108 is characterised by high strength at elevated temperatures with a maximum of 1107 MPa at 975 °C. As a result of constitutional liquation, the superalloy’s strength and ductility were significantly reduced. The nil strength temperature was equal to 1292 °C, while the nil ductility temperature was 1225 °C. The low ductility recovery rate (32.1), ratio of ductility recovery (36.2) and hot cracking factor (Rf = 0.05) values confirmed the low weldability of Renѐ 108. In the heat-affected zone (HAZ) induced by welding, constitutional liquation of mainly γ' precipitates, with a contribution of M23C6 carbides and M5B3 borides, was observed. The thin non-equilibrium liquid film, which formed along high-angle grain boundaries, led to crack initiation and their further propagation during cooling. The eutectic γ–γ' re-solidification products are visible on the crack edges.
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| 9. |
- Dainotti, Maria Giovanna, et al.
(författare)
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On the Evolution of the Hubble Constant with the SNe Ia Pantheon Sample and Baryon Acoustic Oscillations : A Feasibility Study for GRB-Cosmology in 2030
- 2022
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Ingår i: Galaxies. - : MDPI AG. - 2075-4434. ; 10:1
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Tidskriftsartikel (refereegranskat)abstract
- The difference from 4 to 6 σ in the Hubble constant (H0 ) between the values observed with the local (Cepheids and Supernovae Ia, SNe Ia) and the high-z probes (Cosmic Microwave Background obtained by the Planck data) still challenges the astrophysics and cosmology community. Previous analysis has shown that there is an evolution in the Hubble constant that scales as f (z) = H0/(1 + z)η, where H0 is H0 (z = 0) and η is the evolutionary parameter. Here, we investigate if this evolution still holds by using the SNe Ia gathered in the Pantheon sample and the Baryon Acoustic Oscillations. We assume H0 = 70 km s−1 Mpc−1 as the local value and divide the Pantheon into three bins ordered in increasing values of redshift. Similar to our previous analysis but varying two cosmological parameters contemporaneously (H0, Ω0m in the ΛCDM model and H0, wa in the w0waCDM model), for each bin we implement a Markov-Chain Monte Carlo analysis (MCMC) obtaining the value of H0 assuming Gaussian priors to restrict the parameters spaces to values we expect from our prior knowledge of the current cosmological models and to avoid phantom Dark Energy models with w < −1. Subsequently, the values of H0 are fitted with the model f (z). Our results show that a decreasing trend with η ∼ 10−2 is still visible in this sample. The η coefficient reaches zero in 2.0 σ for the ΛCDM model up to 5.8 σ for w0waCDM model. This trend, if not due to statistical fluctuations, could be explained through a hidden astrophysical bias, such as the effect of stretch evolution, or it requires new theoretical models, a possible proposition is the modified gravity theories, f (R). This analysis is meant to further cast light on the evolution of H0 and it does not specifically focus on constraining the other parameters. This work is also a preparatory to understand how the combined probes still show an evolution of the H0 by redshift and what is the current status of simulations on GRB cosmology to obtain the uncertainties on the Ω0m comparable with the ones achieved through SNe Ia.
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| 10. |
- Frommlet, Florian, et al.
(författare)
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Selecting predictive biomarkers from genomic data
- 2022
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Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 17:6 6
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Tidskriftsartikel (refereegranskat)abstract
- Recently there have been tremendous efforts to develop statistical procedures which allow to determine subgroups of patients for which certain treatments are effective. This article focuses on the selection of prognostic and predictive genetic biomarkers based on a relatively large number of candidate Single Nucleotide Polymorphisms (SNPs). We consider models which include prognostic markers as main effects and predictive markers as interaction effects with treatment. We compare different high-dimensional selection approaches including adaptive lasso, a Bayesian adaptive version of the Sorted L-One Penalized Estimator (SLOBE) and a modified version of the Bayesian Information Criterion (mBIC2). These are compared with classical multiple testing procedures for individual markers. Having identified predictive markers we consider several different approaches how to specify subgroups susceptible to treatment. Our main conclusion is that selection based on mBIC2 and SLOBE has similar predictive performance as the adaptive lasso while including substantially fewer biomarkers.
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