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Assam, I., Vijande, J., Ballester, F., Perez-Calatayud, J., Poppe, B., & Siebert, F. A. (2022). Evaluation of dosimetric effects of metallic artifact reduction and tissue assignment on Monte Carlo dose calculations for I-125 prostate implants. Med. Phys., 49, 6195–6208.
Abstract: Purpose Monte Carlo (MC) simulation studies, aimed at evaluating the magnitude of tissue heterogeneity in I-125 prostate permanent seed implant brachytherapy (BT), customarily use clinical post-implant CT images to generate a virtual representation of a realistic patient model (virtual patient model). Metallic artifact reduction (MAR) techniques and tissue assignment schemes (TAS) are implemented on the post-implant CT images to mollify metallic artifacts due to BT seeds and to assign tissue types to the voxels corresponding to the bright seed spots and streaking artifacts, respectively. The objective of this study is to assess the combined influence of MAR and TAS on MC absorbed dose calculations in post-implant CT-based phantoms. The virtual patient models used for I-125 prostate implant MC absorbed dose calculations in this study are derived from the CT images of an external radiotherapy prostate patient without BT seeds and prostatic calcifications, thus averting the need to implement MAR and TAS. Methods The geometry of the IsoSeed I25.S17plus source is validated by comparing the MC calculated results of the TG-43 parameters for the line source approximation with the TG-43U1S2 consensus data. Four MC absorbed dose calculations are performed in two virtual patient models using the egs_brachy MC code: (1) TG-43-based D-w,w-TG(43), (2) D-w,D-w-MBDC that accounts for interseed scattering and attenuation (ISA), (3) D-m,D-m that examines ISA and tissue heterogeneity by scoring absorbed dose in tissue, and (4) D-w,D-m that unlike D-m,D-m scores absorbed dose in water. The MC absorbed doses (1) and (2) are simulated in a TG-43 patient phantom derived by assigning the densities of every voxel to 1.00 g cm(-3) (water), whereas MC absorbed doses (3) and (4) are scored in the TG-186 patient phantom generated by mapping the mass density of each voxel to tissue according to a CT calibration curve. The MC absorbed doses calculated in this study are compared with VariSeed v8.0 calculated absorbed doses. To evaluate the dosimetric effect of MAR and TAS, the MC absorbed doses of this work (independent of MAR and TAS) are compared to the MC absorbed doses of different I-125 source models from previous studies that were calculated with different MC codes using post-implant CT-based phantoms generated by implementing MAR and TAS on post-implant CT images. Results The very good agreement of TG-43 parameters of this study and the published consensus data within 3% validates the geometry of the IsoSeed I25.S17plus source. For the clinical studies, the TG-43-based calculations show a D-90 overestimation of more than 4% compared to the more realistic MC methods due to ISA and tissue composition. The results of this work generally show few discrepancies with the post-implant CT-based dosimetry studies with respect to the D-90 absorbed dose metric parameter. These discrepancies are mainly Type B uncertainties due to the different I-125 source models and MC codes. Conclusions The implementation of MAR and TAS on post-implant CT images have no dosimetric effect on the I-125 prostate MC absorbed dose calculation in post-implant CT-based phantoms.
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Hirn, J., Garcia, J. E., Montesinos-Navarro, A., Sanchez-Martin, R., Sanz, V., & Verdu, M. (2022). A deep Generative Artificial Intelligence system to predict species coexistence patterns. Methods Ecol. Evol., 13, 1052–1061.
Abstract: Predicting coexistence patterns is a current challenge to understand diversity maintenance, especially in rich communities where these patterns' complexity is magnified through indirect interactions that prevent their approximation with classical experimental approaches. We explore cutting-edge Machine Learning techniques called Generative Artificial Intelligence (GenAI) to predict species coexistence patterns in vegetation patches, training generative adversarial networks (GAN) and variational AutoEncoders (VAE) that are then used to unravel some of the mechanisms behind community assemblage. The GAN accurately reproduces real patches' species composition and plant species' affinity to different soil types, and the VAE also reaches a high level of accuracy, above 99%. Using the artificially generated patches, we found that high-order interactions tend to suppress the positive effects of low-order interactions. Finally, by reconstructing successional trajectories, we could identify the pioneer species with larger potential to generate a high diversity of distinct patches in terms of species composition. Understanding the complexity of species coexistence patterns in diverse ecological communities requires new approaches beyond heuristic rules. Generative Artificial Intelligence can be a powerful tool to this end as it allows to overcome the inherent dimensionality of this challenge.
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Giare, W., Renzi, F., Melchiorri, A., Mena, O., & Di Valentino, E. (2022). Cosmological forecasts on thermal axions, relic neutrinos, and light elements. Mon. Not. Roy. Astron. Soc., 511(1), 1373–1382.
Abstract: One of the targets of future cosmic microwave background (CMB) and baryon acoustic oscillation measurements is to improve the current accuracy in the neutrino sector and reach a much better sensitivity on extra dark radiation in the early Universe. In this paper, we study how these improvements can be translated into constraining power for well-motivated extensions of the standard model of elementary particles that involve axions thermalized before the quantum chromodynamics (QCD) phase transition by scatterings with gluons. Assuming a fiducial Lambda cold dark matter cosmological model, we simulate future data for Stage-IV CMB-like and Dark Energy Spectroscopic Instrument (DESI)-like surveys and analyse a mixed scenario of axion and neutrino hot dark matter. We further account also for the effects of these QCD axions on the light element abundances predicted by big bang nucleosynthesis. The most constraining forecasted limits on the hot relic masses are m(a) less than or similar to 0.92 eV and n-ary sumation m(nu) less than or similar to 0.12 eV at 95 per cent Confidence Level, showing that future cosmic observations can substantially improve the current bounds, supporting multimessenger analyses of axion, neutrino, and primordial light element properties.
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MoEDAL Collaboration(Acharya, B. et al), Mitsou, V. A., Papavassiliou, J., Ruiz de Austri, R., Santra, A., Vento, V., et al. (2022). Search for magnetic monopoles produced via the Schwinger mechanism. Nature, 602(7895), 63–67.
Abstract: Electrically charged particles can be created by the decay of strong enough electric fields, a phenomenon known as the Schwinger mechanism(1). By electromagnetic duality, a sufficiently strong magnetic field would similarly produce magnetic monopoles, if they exist(2). Magnetic monopoles are hypothetical fundamental particles that are predicted by several theories beyond the standard model(3-7) but have never been experimentally detected. Searching for the existence of magnetic monopoles via the Schwinger mechanism has not yet been attempted, but it is advantageous, owing to the possibility of calculating its rate through semi-classical techniques without perturbation theory, as well as that the production of the magnetic monopoles should be enhanced by their finite size(8,9) and strong coupling to photons(2,10). Here we present a search for magnetic monopole production by the Schwinger mechanism in Pb-Pb heavy ion collisions at the Large Hadron Collider, producing the strongest known magnetic fields in the current Universe(11). It was conducted by the MoEDAL experiment, whose trapping detectors were exposed to 0.235 per nanobarn, or approximately 1.8 x 10(9), of Pb-Pb collisions with 5.02-teraelectronvolt center-of-mass energy per collision in November 2018. A superconducting quantum interference device (SQUID) magnetometer scanned the trapping detectors of MoEDAL for the presence of magnetic charge, which would induce a persistent current in the SQUID. Magnetic monopoles with integer Dirac charges of 1, 2 and 3 and masses up to 75 gigaelectronvolts per speed of light squared were excluded by the analysis at the 95% confidence level. This provides a lower mass limit for finite-size magnetic monopoles from a collider search and greatly extends previous mass bounds.
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ATLAS Collaboration. (2022). A detailed map of Higgs boson interactions by the ATLAS experiment ten years after the discovery. Nature, 607(7917), 52–59.
Abstract: The standard model of particle physics(1-4) describes the known fundamental particles and forces that make up our Universe, with the exception of gravity. One of the central features of the standard model is a field that permeates all of space and interacts with fundamental particles(5-9). The quantum excitation of this field, known as the Higgs field, manifests itself as the Higgs boson, the only fundamental particle with no spin. In 2012, a particle with properties consistent with the Higgs boson of the standard model was observed by the ATLAS and CMS experiments at the Large Hadron Collider at CERN10,11. Since then, more than 30 times as many Higgs bosons have been recorded by the ATLAS experiment, enabling much more precise measurements and new tests of the theory. Here, on the basis of this larger dataset, we combine an unprecedented number of production and decay processes of the Higgs boson to scrutinize its interactions with elementary particles. Interactions with gluons, photons, and W and Z bosons-the carriers of the strong, electromagnetic and weak forces-are studied in detail. Interactions with three third-generation matter particles (bottom (b) and top (t) quarks, and tau leptons (tau)) are well measured and indications of interactions with a second-generation particle (muons, mu) are emerging. These tests reveal that the Higgs boson discovered ten years ago is remarkably consistent with the predictions of the theory and provide stringent constraints on many models of new phenomena beyond the standard model.
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