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Author |
Hernandez, P.; Lopez-Pavon, J.; Rius, N.; Sandner, S. |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
Bounds on right-handed neutrino parameters from observable leptogenesis |
Type |
Journal Article |
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Year |
2022 |
Publication |
Journal of High Energy Physics |
Abbreviated Journal |
J. High Energy Phys. |
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Volume ![sorted by Volume (numeric) field, ascending order (up)](img/sort_asc.gif) |
12 |
Issue |
12 |
Pages |
012 - 58pp |
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Keywords |
Baryo-and Leptogenesis; Early Universe Particle Physics; Sterile or Heavy Neutrinos |
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Abstract |
We revisit the generation of a matter-antimatter asymmetry in the minimal extension of the Standard Model with two singlet heavy neutral leptons (HNL) that can explain neutrino masses. We derive an accurate analytical approximation to the solution of the complete linearized set of kinetic equations, which exposes the non-trivial parameter dependencies in the form of parameterization-independent CP invariants. The identification of various washout regimes relevant in different regions of parameter space sheds light on the relevance of the mass corrections in the interaction rates and clarifies the correlations of baryogenesis with other observables. In particular, by requiring that the measured baryon asymmetry is reproduced, we derive robust upper or lower bounds on the HNL mixings depending on their masses, and constraints on their flavour structure, as well as on the CP-violating phases of the PMNS mixing matrix, and the amplitude of neutrinoless double-beta decay. We also find certain correlations between low and high scale CP phases. Especially emphasizing the testable part of the parameter space we demonstrate that our findings are in very good agreement with numerical results. The methods developed in this work can help in exploring more complex scenarios. |
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Address |
[Hernandez, P.] Univ Valencia, Inst Fis Corpuscular, Edificio Inst Invest,Catedrat Jose Beltran 2, Paterna 46980, Spain, Email: m.pilar.hernandez@uv.es; |
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Springer |
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English |
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ISSN |
1029-8479 |
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Notes |
WOS:000914640400003 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
5467 |
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Permanent link to this record |
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Author |
Hirn, J.; Garcia, J.E.; Montesinos-Navarro, A.; Sanchez-Martin, R.; Sanz, V.; Verdu, M. |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
A deep Generative Artificial Intelligence system to predict species coexistence patterns |
Type |
Journal Article |
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Year |
2022 |
Publication |
Methods in Ecology and Evolution |
Abbreviated Journal |
Methods Ecol. Evol. |
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Volume ![sorted by Volume (numeric) field, ascending order (up)](img/sort_asc.gif) |
13 |
Issue |
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Pages |
1052-1061 |
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Keywords |
artificial intelligence; direct interactions; generative adversarial networks; indirect interactions; species coexistence; variational AutoEncoders |
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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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Address |
[Hirn, Johannes; Enrique Garcia, Jose; Sanz, Veronica] Univ Valencia, CSIC, Inst Fis Corpuscular IFIC, Valencia, Spain, Email: miguel.verdu@ext.uv.es |
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Wiley |
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English |
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2041-210x |
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Notes |
WOS:000765239700001 |
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no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5155 |
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Permanent link to this record |
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Author |
LHCb Collaboration (Aaij, R. et al); Jashal, B.K.; Martinez-Vidal, F.; Oyanguren, A.; Remon Alepuz, C.; Ruiz Vidal, J. |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
Study of the doubly charmed tetraquark T-cc(+) |
Type |
Journal Article |
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Year |
2022 |
Publication |
Nature Communications |
Abbreviated Journal |
Nat. Commun. |
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Volume ![sorted by Volume (numeric) field, ascending order (up)](img/sort_asc.gif) |
13 |
Issue |
1 |
Pages |
3351 - 19pp |
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Abstract |
Quantum chromodynamics, the theory of the strong force, describes interactions of coloured quarks and gluons and the formation of hadronic matter. Conventional hadronic matter consists of baryons and mesons made of three quarks and quark-antiquark pairs, respectively. Particles with an alternative quark content are known as exotic states. Here a study is reported of an exotic narrow state in the (DD0)-D-0 pi(+) mass spectrum just below the D*+D-0 mass threshold produced in proton-proton collisions collected with the LHCb detector at the Large Hadron Collider. The state is consistent with the ground isoscalar T-cc(+), tetraquark with a quark content of cc (u) over bar(d) over bar and spin-parity quantum numbers J(P) =1(+). Study of the DD mass spectra disfavours interpretation of the resonance as the isovector state. The decay structure via intermediate off-shell D*(+) mesons is consistent with the observed D-0 pi(+) mass distribution. To analyse the mass of the resonance and its coupling to the DID system, a dedicated model is developed under the assumption of an isoscalar axial-vector T-cc(+), state decaying to the D*D channel. Using this model, resonance parameters including the pole position, scattering length, effective range and compositeness are determined to reveal important information about the nature of the T-cc(+), state. In addition, an unexpected dependence of the production rate on track multiplicity is observed. |
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Address |
[Aaij, R.; Butter, J. S.; Akiba, K. Carvalho; Sole, S. Ferreres; Gabriel, E.; Geertsema, R. E.; Greeven, L. M.; Heijhoff, K.; Hulsbergen, W.; Hynds, D.; Jans, E.; Ketel, T.; Klaver, S.; Koppenburg, P.; Kostiuk, I; Kuindersma, H. S.; Martinez, M. Lucio; Lukashenko, V; Mauri, A.; Merk, M.; Pellegrino, A.; Raven, G.; Gras, C. Sanchez; Schubiger, M.; Soares, M. Senghi; Snoch, A.; Tuning, N.; Usachov, A.; van Beuzekom, M.; Veronesi, M.] Nikhef Natl Inst Subatom Phys, Amsterdam, Netherlands, Email: Ivan.Belyaev@cern.ch |
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Nature Portfolio |
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English |
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Notes |
WOS:000812556800001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5280 |
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Permanent link to this record |
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Author |
Albiol, A.; Albiol, F.; Paredes, R.; Plasencia-Martinez, J.M.; Blanco Barrio, A.; Garcia Santos, J.M.; Tortajada, S.; Gonzalez Montano, V.M.; Rodriguez Godoy, C.E.; Fernandez Gomez, S.; Oliver-Garcia, E.; de la Iglesia Vaya, M.; Marquez Perez, F.L.; Rayo Madrid, J.I. |
![find record details (via OpenURL) openurl](img/xref.gif)
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Title |
A comparison of Covid-19 early detection between convolutional neural networks and radiologists |
Type |
Journal Article |
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Year |
2022 |
Publication |
Insights into Imaging |
Abbreviated Journal |
Insights Imaging |
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Volume ![sorted by Volume (numeric) field, ascending order (up)](img/sort_asc.gif) |
13 |
Issue |
1 |
Pages |
122 - 12pp |
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Keywords |
Deep learning; Covid-19; Radiology |
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Abstract |
Background The role of chest radiography in COVID-19 disease has changed since the beginning of the pandemic from a diagnostic tool when microbiological resources were scarce to a different one focused on detecting and monitoring COVID-19 lung involvement. Using chest radiographs, early detection of the disease is still helpful in resource-poor environments. However, the sensitivity of a chest radiograph for diagnosing COVID-19 is modest, even for expert radiologists. In this paper, the performance of a deep learning algorithm on the first clinical encounter is evaluated and compared with a group of radiologists with different years of experience. Methods The algorithm uses an ensemble of four deep convolutional networks, Ensemble4Covid, trained to detect COVID-19 on frontal chest radiographs. The algorithm was tested using images from the first clinical encounter of positive and negative cases. Its performance was compared with five radiologists on a smaller test subset of patients. The algorithm's performance was also validated using the public dataset COVIDx. Results Compared to the consensus of five radiologists, the Ensemble4Covid model achieved an AUC of 0.85, whereas the radiologists achieved an AUC of 0.71. Compared with other state-of-the-art models, the performance of a single model of our ensemble achieved nonsignificant differences in the public dataset COVIDx. Conclusion The results show that the use of images from the first clinical encounter significantly drops the detection performance of COVID-19. The performance of our Ensemble4Covid under these challenging conditions is considerably higher compared to a consensus of five radiologists. Artificial intelligence can be used for the fast diagnosis of COVID-19. |
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Address |
[Albiol, Alberto] Univ Politecn Valencia, iTeam Inst, ETSI Telecomunicac, Camino Vera S-N, Valencia 46022, Spain, Email: alalbiol@iteam.upv.es |
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Springer |
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English |
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ISSN |
1869-4101 |
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Notes |
WOS:000832727200003 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
5302 |
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Permanent link to this record |
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Author |
Horak, J.; Ihssen, F.; Papavassiliou, J.; Pawlowski, J.M.; Weber, A.; Wetterich, C. |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
Gluon condensates and effective gluon mass |
Type |
Journal Article |
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Year |
2022 |
Publication |
Scipost Physics |
Abbreviated Journal |
SciPost Phys. |
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Volume ![sorted by Volume (numeric) field, ascending order (up)](img/sort_asc.gif) |
13 |
Issue |
2 |
Pages |
042 - 40pp |
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Keywords |
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Abstract |
Lattice simulations along with studies in continuum QCD indicate that non-perturbative quantum fluctuations lead to an infrared regularisation of the gluon propagator in covariant gauges in the form of an effective mass-like behaviour. In the present work we propose an analytic understanding of this phenomenon in terms of gluon condensation through a dynamical version of the Higgs mechanism, leading to the emergence of color condensates. Within the functional renormalisation group approach we compute the effective potential of covariantly constant field strengths, whose non-trivial minimum is related to the color condensates. In the physical case of an SU(3) gauge group this is an octet condensate. The value of the gluon mass obtained through this procedure compares very well to lattice results and the mass gap arising from alternative dynamical scenarios. |
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Address |
[Horak, Jan; Ihssen, Friederike; Pawlowski, Jan M.; Weber, Axel; Wetterich, Christof] Heidelberg Univ, Inst Theoret Phys, Philosophenweg 16, D-69120 Heidelberg, Germany |
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Scipost Foundation |
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English |
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Series Volume |
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Series Issue |
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ISSN |
2542-4653 |
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Notes |
WOS:000863121000008 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5379 |
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Permanent link to this record |