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Author |
Carrasco-Ribelles, L.A.; Pardo-Mas, J.R.; Tortajada, S.; Saez, C.; Valdivieso, B.; Garcia-Gomez, J.M. |
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Title |
Predicting morbidity by local similarities in multi-scale patient trajectories |
Type |
Journal Article |
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Year |
2021 |
Publication |
Journal of Biomedical Informatics |
Abbreviated Journal |
J. Biomed. Inform. |
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Volume |
120 |
Issue |
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Pages |
103837 - 9pp |
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Keywords |
Patient trajectory; Risk prediction; Local alignment; Dynamic programming; Diabetes; Cardiovascular disease |
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Abstract |
Patient Trajectories (PTs) are a method of representing the temporal evolution of patients. They can include information from different sources and be used in socio-medical or clinical domains. PTs have generally been used to generate and study the most common trajectories in, for instance, the development of a disease. On the other hand, healthcare predictive models generally rely on static snapshots of patient information. Only a few works about prediction in healthcare have been found that use PTs, and therefore benefit from their temporal dimension. All of them, however, have used PTs created from single-source information. Therefore, the use of longitudinal multi-scale data to build PTs and use them to obtain predictions about health conditions is yet to be explored. Our hypothesis is that local similarities on small chunks of PTs can identify similar patients concerning their future morbidities. The objectives of this work are (1) to develop a methodology to identify local similarities between PTs before the occurrence of morbidities to predict these on new query individuals; and (2) to validate this methodology on risk prediction of cardiovascular diseases (CVD) occurrence in patients with diabetes. We have proposed a novel formal definition of PTs based on sequences of longitudinal multi-scale data. Moreover, a dynamic programming methodology to identify local alignments on PTs for predicting future morbidities is proposed. Both the proposed methodology for PT definition and the alignment algorithm are generic to be applied on any clinical domain. We validated this solution for predicting CVD in patients with diabetes and we achieved a precision of 0.33, a recall of 0.72 and a specificity of 0.38. Therefore, the proposed solution in the diabetes use case can result of utmost utility to secondary screening. |
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Address |
[Carrasco-Ribelles, Lucia A.; Pardo-Mas, Jose Ramon; Saez, Carlos; Garcia-Gomez, Juan M.] Univ Politecn Valencia, Biomed Data Sci Lab BDSLAB, Inst Tecnol Informat & Comunicac ITACA, Camino Vera S-N, Valencia 46022, Spain, Email: lucarri@etsii.upv.es; |
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Academic Press Inc Elsevier Science |
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English |
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ISSN |
1532-0464 |
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Notes |
WOS:000683527500003 |
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no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
4934 |
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Author |
Fanchiotti, H.; Garcia Canal, C.A.; Mayosky, M.; Veiga, A.; Vento, V. |
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Title |
Measuring the Hannay geometric phase |
Type |
Journal Article |
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Year |
2022 |
Publication |
American Journal of Physics |
Abbreviated Journal |
Am. J. Phys. |
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Volume |
90 |
Issue |
6 |
Pages |
430-435 |
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Abstract |
The Hannay geometric phase is the classical analog of the well-known Berry phase. Its most familiar example is the effect of the latitude lambda on the motion of a Foucault pendulum. We describe an electronic network whose behavior is exactly equivalent to that of the pendulum. The circuit can be constructed from off-the-shelf components using two matched transconductance amplifiers that comprise a gyrator to introduce the non-reciprocal behavior needed to mimic the pendulum. One may precisely measure the dependence of the Hannay phase on lambda by circuit simulation and by laboratory measurements on a constructed circuit. |
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Address |
[Fanchiotti, H.; Canal, C. A. Garcia] Univ Nacl La Plata, IFLP, CONICET, CC67, RA-1900 La Plata, Argentina |
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AIP Publishing |
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English |
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ISSN |
0002-9505 |
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Notes |
WOS:000804547100009 |
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no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5276 |
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Author |
Bernabeu, J.; Sabulsky, D.O.; Sanchez, F.; Segarra, A. |
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Title |
Neutrino mass and nature through its mediation in atomic clock interference |
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Journal Article |
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Year |
2024 |
Publication |
AVS Quantum Science |
Abbreviated Journal |
AVS Quantum Sci. |
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Volume |
6 |
Issue |
1 |
Pages |
014410 - 8pp |
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Abstract |
The absolute mass of neutrinos and their nature are presently unknown. Aggregate matter has a coherent weak charge leading to a repulsive interaction mediated by a neutrino pair. The virtual neutrinos are non-relativistic at micron distances, giving a distinct behavior for Dirac versus Majorana mass terms. This effective potential allows for the disentanglement of the Dirac or Majorana nature of the neutrino via magnitude and distance dependence. We propose an experiment to search for this potential based on the concept that the density-dependent interaction of an atomic probe with a material source in one arm of an atomic clock interferometer generates a differential phase. The appropriate geometry of the device is selected using the saturation of the weak potential as a guide. The proposed experiment has the added benefit of being sensitive to gravity at micron distances. A strategy to suppress the competing Casimir-Polder interaction, depending on the electronic structure of the material source, as well as a way to compensate the gravitational interaction in the two arms of the interferometer is discussed. |
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Address |
[Bernabeu, Jose; Segarra, Alejandro] Univ Valencia, Dept Theoret Phys, E-46100 Valencia, Spain, Email: jose.bernabeu@uv.es |
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AIP Publishing |
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Notes |
WOS:001186930100001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
6118 |
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Author |
Conde, D.; Castillo, F.L.; Escobar, C.; García, C.; Garcia Navarro, J.E.; Sanz, V.; Zaldívar, B.; Curto, J.J.; Marsal, S.; Torta, J.M. |
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Title |
Forecasting Geomagnetic Storm Disturbances and Their Uncertainties Using Deep Learning |
Type |
Journal Article |
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Year |
2023 |
Publication |
Space Weather |
Abbreviated Journal |
Space Weather |
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Volume |
21 |
Issue |
11 |
Pages |
e2023SW003474 - 27pp |
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Keywords |
geomagnetic storms; deep learning; forecasting; SYM-H; uncertainties; hyper-parameter optimization |
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Abstract |
Severe space weather produced by disturbed conditions on the Sun results in harmful effects both for humans in space and in high-latitude flights, and for technological systems such as spacecraft or communications. Also, geomagnetically induced currents (GICs) flowing on long ground-based conductors, such as power networks, potentially threaten critical infrastructures on Earth. The first step in developing an alarm system against GICs is to forecast them. This is a challenging task given the highly non-linear dependencies of the response of the magnetosphere to these perturbations. In the last few years, modern machine-learning models have shown to be very good at predicting magnetic activity indices. However, such complex models are on the one hand difficult to tune, and on the other hand they are known to bring along potentially large prediction uncertainties which are generally difficult to estimate. In this work we aim at predicting the SYM-H index characterizing geomagnetic storms multiple-hour ahead, using public interplanetary magnetic field (IMF) data from the Sun-Earth L1 Lagrange point and SYM-H data. We implement a type of machine-learning model called long short-term memory (LSTM) network. Our scope is to estimate the prediction uncertainties coming from a deep-learning model in the context of forecasting the SYM-H index. These uncertainties will be essential to set reliable alarm thresholds. The resulting uncertainties turn out to be sizable at the critical stages of the geomagnetic storms. Our methodology includes as well an efficient optimization of important hyper-parameters of the LSTM network and robustness tests. |
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Address |
[Conde, D.; Escobar, C.; Garcia, C.; Garcia, J. E.; Sanz, V.; Zaldivar, B.] Univ Valencia, CSIC, Ctr Mixto, Inst Fis Corpuscular IFIC, Valencia, Spain, Email: Daniel.Conde@ific.uv.es |
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Publisher |
Amer Geophysical Union |
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English |
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Notes |
WOS:001104189700001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5804 |
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Author |
Schaffter, T. et al; Albiol, F.; Caballero, L. |
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Title |
Evaluation of Combined Artificial Intelligence and Radiologist Assessment to Interpret Screening Mammograms |
Type |
Journal Article |
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Year |
2020 |
Publication |
JAMA Network Open |
Abbreviated Journal |
JAMA Netw. Open |
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Volume |
3 |
Issue |
3 |
Pages |
e200265 - 15pp |
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Abstract |
Importance Mammography screening currently relies on subjective human interpretation. Artificial intelligence (AI) advances could be used to increase mammography screening accuracy by reducing missed cancers and false positives. Objective To evaluate whether AI can overcome human mammography interpretation limitations with a rigorous, unbiased evaluation of machine learning algorithms. Design, Setting, and Participants In this diagnostic accuracy study conducted between September 2016 and November 2017, an international, crowdsourced challenge was hosted to foster AI algorithm development focused on interpreting screening mammography. More than 1100 participants comprising 126 teams from 44 countries participated. Analysis began November 18, 2016. Main Outcomes and Measurements Algorithms used images alone (challenge 1) or combined images, previous examinations (if available), and clinical and demographic risk factor data (challenge 2) and output a score that translated to cancer yes/no within 12 months. Algorithm accuracy for breast cancer detection was evaluated using area under the curve and algorithm specificity compared with radiologists' specificity with radiologists' sensitivity set at 85.9% (United States) and 83.9% (Sweden). An ensemble method aggregating top-performing AI algorithms and radiologists' recall assessment was developed and evaluated. Results Overall, 144231 screening mammograms from 85580 US women (952 cancer positive <= 12 months from screening) were used for algorithm training and validation. A second independent validation cohort included 166578 examinations from 68008 Swedish women (780 cancer positive). The top-performing algorithm achieved an area under the curve of 0.858 (United States) and 0.903 (Sweden) and 66.2% (United States) and 81.2% (Sweden) specificity at the radiologists' sensitivity, lower than community-practice radiologists' specificity of 90.5% (United States) and 98.5% (Sweden). Combining top-performing algorithms and US radiologist assessments resulted in a higher area under the curve of 0.942 and achieved a significantly improved specificity (92.0%) at the same sensitivity. Conclusions and Relevance While no single AI algorithm outperformed radiologists, an ensemble of AI algorithms combined with radiologist assessment in a single-reader screening environment improved overall accuracy. This study underscores the potential of using machine learning methods for enhancing mammography screening interpretation. Question How do deep learning algorithms perform compared with radiologists in screening mammography interpretation? Findings In this diagnostic accuracy study using 144231 screening mammograms from 85580 women from the United States and 166578 screening mammograms from 68008 women from Sweden, no single artificial intelligence algorithm outperformed US community radiologist benchmarks; including clinical data and prior mammograms did not improve artificial intelligence performance. However, combining best-performing artificial intelligence algorithms with single-radiologist assessment demonstrated increased specificity. Meaning Integrating artificial intelligence to mammography interpretation in single-radiologist settings could yield significant performance improvements, with the potential to reduce health care system expenditures and address resource scarcity experienced in population-based screening programs. This diagnostic accuracy study evaluates whether artificial intelligence can overcome human mammography interpretation limits with a rigorous, unbiased evaluation of machine learning algorithms. |
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Address |
[Schaffter, Thomas; Hoff, Bruce; Yu, Thomas; Neto, Elias Chaibub; Friend, Stephen; Guinney, Justin] Sage Bionetworks, Computat Oncol, Seattle, WA USA, Email: gustavo@us.ibm.com |
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Publisher |
Amer Medical Assoc |
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English |
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ISSN |
2574-3805 |
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Notes |
WOS:000519249800002 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
4683 |
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Author |
Chatterjee, S.S.; Pasquini, P.; Valle, J.W.F. |
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Title |
Resolving the atmospheric octant by an improved measurement of the reactor angle |
Type |
Journal Article |
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Year |
2017 |
Publication |
Physical Review D |
Abbreviated Journal |
Phys. Rev. D |
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Volume |
96 |
Issue |
1 |
Pages |
011303 - 6pp |
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Keywords |
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Abstract |
Taking into account the current global information on neutrino oscillation parameters we forecast the capabilities of future long-baseline experiments such as DUNE and T2HK in settling the atmospheric octant puzzle. We find that a good measurement of the reactor angle theta(13) plays a key role in fixing the octant of the atmospheric angle theta(23) with such future accelerator neutrino studies. |
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Address |
[Chatterjee, Sabya Sachi] Inst Phys, Sachivalaya Marg,Sainik Sch Post, Bhubaneswar 751005, Orissa, India, Email: sabya@iopb.res.in; |
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Amer Physical Soc |
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English |
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ISSN |
2470-0010 |
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Notes |
WOS:000405925300001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
3204 |
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Author |
Song, T.; Berrehrah, H.; Torres-Rincon, J.M.; Tolos, L.; Cabrera, D.; Cassing, W.; Bratkovskaya, E. |
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Title |
Single electrons from heavy-flavor mesons in relativistic heavy-ion collisions |
Type |
Journal Article |
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Year |
2017 |
Publication |
Physical Review C |
Abbreviated Journal |
Phys. Rev. C |
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Volume |
96 |
Issue |
1 |
Pages |
014905 - 18pp |
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Abstract |
We study the single electron spectra from D- and B-meson semileptonic decays in Au + Au collisions at root s(NN) = 200, 62.4, and 19.2 GeV by employing the parton-hadron-string dynamics (PHSD) transport approach that has been shown to reasonably describe the charm dynamics at Relativistic Heavy Ion Collider and Large Hadron Collider energies on a microscopic level. In this approach the initial charm and bottom quarks are produced by using the PYTHIA event generator which is tuned to reproduce the fixed-order next-to-leading logarithm calculations for charm and bottom production. The produced charm and bottom quarks interact with off-shell (massive) partons in the quark-gluon plasma with scattering cross sections which are calculated in the dynamical quasiparticle model that is matched to reproduce the equation of state of the partonic system above the deconfinement temperature T-c. At energy densities close to the critical energy density (approximate to 0.5 GeV/fm(3)) the charm and bottom quarks are hadronized intoD and B mesons through either coalescence or fragmentation. After hadronization the D and B mesons interact with the light hadrons by employing the scattering cross sections from an effective Lagrangian. The final D and B mesons then produce single electrons through semileptonic decay. We find that the PHSD approach well describes the nuclear modification factor R-AA and elliptic flow upsilon(2) of single electrons in d + Au and Au + Au collisions at root s(NN) = 200 GeV and the elliptic flow in Au + Au reactions at root s(NN) = 62.4 GeV from the PHENIX Collaboration, however, the large RAA at root s(NN) = 62.4 GeV is not described at all. Furthermore, we make predictions for the RAA of D mesons and of single electrons at the lower energy of root s(NN) = 19.2 GeV. Additionally, the medium modification of the azimuthal angle phi between a heavy quark and a heavy antiquark is studied. We find that the transverse flow enhances the azimuthal angular distributions close to phi = 0 because the heavy flavors strongly interact with nuclear medium in relativistic heavy-ion collisions and almost flow with the bulk matter. |
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Address |
[Song, Taesoo; Berrehrah, Hamza; Bratkovskaya, Elena] Goethe Univ Frankfurt, Inst Theoret Phys, Frankfurt, Germany, Email: song@fias.uni-frankfurt.de |
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Amer Physical Soc |
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English |
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ISSN |
2469-9985 |
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Notes |
WOS:000405203800005 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
3202 |
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Author |
Motohashi, H.; Hu, W. |
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Title |
Generalized slow roll in the unified effective field theory of inflation |
Type |
Journal Article |
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Year |
2017 |
Publication |
Physical Review D |
Abbreviated Journal |
Phys. Rev. D |
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Volume |
96 |
Issue |
2 |
Pages |
023502 - 17pp |
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Abstract |
We provide a compact and unified treatment of power spectrum observables for the effective field theory (EFT) of inflation with the complete set of operators that lead to second-order equations of motion in metric perturbations in both space and time derivatives, including Horndeski and Gleyzes-Langlois-Piazza-Vernizzi theories. We relate the EFT operators in ADM form to the four additional free functions of time in the scalar and tensor equations. Using the generalized slow-roll formalism, we show that each power spectrum can be described by an integral over a single source that is a function of its respective sound horizon. With this correspondence, existing model independent constraints on the source function can be simply reinterpreted in the more general inflationary context. By expanding these sources around an optimized freeze-out epoch, we also provide characterizations of these spectra in terms of five slow-roll hierarchies whose leading-order forms are compact and accurate as long as EFT coefficients vary only on time scales greater than an e-fold. We also clarify the relationship between the unitary gauge observables employed in the EFT and the comoving gauge observables of the postinflationary universe. |
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Address |
[Motohashi, Hayato] Univ Valencia, CSIC, Inst Fis Corpuscular IFIC, E-46980 Valencia, Spain |
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Amer Physical Soc |
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English |
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ISSN |
2470-0010 |
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Notes |
WOS:000405205400001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
3203 |
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Author |
Chala, M. |
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Title |
Direct bounds on heavy toplike quarks with standard and exotic decays |
Type |
Journal Article |
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Year |
2017 |
Publication |
Physical Review D |
Abbreviated Journal |
Phys. Rev. D |
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Volume |
96 |
Issue |
1 |
Pages |
015028 - 14pp |
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Abstract |
Heavy vectorlike quarks with electric charge Q = 2/3 (also called heavy tops) appear naturally in many extensions of the Standard Model. Although these typically predict the existence of further particles below the TeV scale, direct searches for heavy tops have been performed assuming that they decay only into SM particles. The aim of this paper is to overcome this situation. We consider the most constraining experimental LHC searches for vectorlike quarks, including analyses of the 36 fb(-1) of data collected in the latest run at 13 TeV of center of mass energy, as well as searches sensitive to heavy tops decaying into a new scalar, S. Combining all these, we derive bounds for arbitrary values of the heavy top branching ratios. A simple code that automatizes this process is also provided. At the physics level, we demonstrate that bounds on heavy tops are not inevitably weaker in the presence of new light scalars. We find that heavy tops with masses below similar to 900 GeV are excluded by direct searches, independently of whether they decay into Zt, Ht, Wb or St (with S giving either missing energy of bottom quarks) or into any combination of them. |
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Address |
[Chala, Mikael] Univ Valencia, Dept Fis Teor, Dr Moliner 50, E-46100 Burjassot, Spain |
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Amer Physical Soc |
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English |
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ISSN |
2470-0010 |
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Conference |
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Notes |
WOS:000406298500008 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
3211 |
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Author |
Debastiani, V.R.; Dias, J.M.; Oset, E. |
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Title |
Study of the DKK and DK(K)over-bar systems |
Type |
Journal Article |
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Year |
2017 |
Publication |
Physical Review D |
Abbreviated Journal |
Phys. Rev. D |
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Volume |
96 |
Issue |
1 |
Pages |
016014 - 9pp |
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Keywords |
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Abstract |
Using the fixed center approximation to Faddeev equations, we investigate the DKK and DK (K) over bar three-body systems, considering that the DK dynamically generates, through its I = 0 component, the D(so)(*()2317) molecule. According to our findings, for the DK (K) over bar interaction we find evidence of a state I(J(p)) = 1/2 (0(-)) just above the D-s0(*)(2317) (K) over bar threshold and around the Df(0)(980) threshold, with mass of about 2833-2858 MeV, made mostly of Df(0)(980). On the other hand, no evidence related to a state from the DKK interaction is found. The state found could be seen in the ppD invariant mass. |
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Address |
[Debastiani, V. R.; Dias, J. M.; Oset, E.] Ctr Mixto Univ Valencia CSIC, Inst Invest Paterna, Dept Fis Teor, Apartado 22085, Valencia 46071, Spain, Email: vinicius.rodrigues@ific.uv.es; |
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Publisher |
Amer Physical Soc |
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Language |
English |
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Series Volume |
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Edition |
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ISSN |
2470-0010 |
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Notes |
WOS:000406298500009 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
3212 |
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