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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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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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English |
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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 |
LHCb Collaboration (Aaij, R. et al); Garcia Martin, L.M.; Martinez-Vidal, F.; Oyanguren, A.; Remon Alepuz, C.; Ruiz Valls, P.; Sanchez Mayordomo, C. |
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Title |
Observation of B-c(+) -> (DK+)-K-0 Decays |
Type |
Journal Article |
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Year |
2017 |
Publication |
Physical Review Letters |
Abbreviated Journal |
Phys. Rev. Lett. |
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Volume |
118 |
Issue |
11 |
Pages |
111803 - 9pp |
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Keywords |
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Abstract |
Using proton-proton collision data corresponding to an integrated luminosity of 3.0 fb(-1), recorded by the LHCb detector at center-of-mass energies of 7 and 8 TeV, the B-c(+) -> (DK+)-K-0 decay is observed with a statistical significance of 5.1 standard deviations. By normalizing to B-c(+) -> (D) over bar (0)pi(+) decays, a measurement of the branching fraction multiplied by the production rates for B-c(+) relative to B+ mesons in the LHCb acceptance is obtained, R-D0K = (f(c)/f(u)) x B(B-c(+) -> (DK+)-K-0) = (9.3(-2.5)(+2.8) +/- 0.6) x 10(-7), where the first uncertainty is statistical and the second is systematic. This decay is expected to proceed predominantly through weak annihilation and penguin amplitudes, and is the first B-c(+) decay of this nature to be observed. |
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Address |
[Bediaga, I.; De Miranda, J. M.; Gomes, A.; Massafferri, A.; Rodriguez, J. Molina; dos Reis, A. C.; Rodrigues, A. B.; Guimaraes, V. Salustino; Lavra, L. Soares] Ctr Brasileiro Pesquisas Fis, Rio De Janeiro, Brazil |
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Publisher |
Amer Physical Soc |
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English |
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0031-9007 |
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Notes |
WOS:000396267100005 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
2963 |
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Author |
Agullo, I.; del Rio, A.; Navarro-Salas, J. |
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Title |
Electromagnetic Duality Anomaly in Curved Spacetimes |
Type |
Journal Article |
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Year |
2017 |
Publication |
Physical Review Letters |
Abbreviated Journal |
Phys. Rev. Lett. |
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Volume |
118 |
Issue |
11 |
Pages |
111301 - 5pp |
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Abstract |
The source-free Maxwell action is invariant under electric-magnetic duality rotations in arbitrary spacetimes. This leads to a conserved classical Noether charge. We show that this conservation law is broken at the quantum level in the presence of a background classical gravitational field with a nontrivial Chern-Pontryagin invariant, in parallel with the chiral anomaly for massless Dirac fermions. Among the physical consequences, the net polarization of the quantum electromagnetic field is not conserved. |
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Address |
[Agullo, Ivan; del Rio, Adrian] Louisiana State Univ, Dept Phys & Astron, Baton Rouge, LA 70803 USA, Email: agullo@lsu.edu; |
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Amer Physical Soc |
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English |
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ISSN |
0031-9007 |
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Notes |
WOS:000396267100003 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
2964 |
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Author |
LHCb Collaboration (Aaij, R. et al); Garcia Martin, L.M.; Martinez-Vidal, F.; Oyanguren, A.; Remon Alepuz, C.; Ruiz Valls, P.; Sanchez Mayordomo, C. |
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Title |
Observation of the Annihilation Decay Mode B-0 -> K+K- |
Type |
Journal Article |
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Year |
2017 |
Publication |
Physical Review Letters |
Abbreviated Journal |
Phys. Rev. Lett. |
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Volume |
118 |
Issue |
8 |
Pages |
081801 - 9pp |
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Abstract |
A search for the B-0 -> K+K- decay is performed using pp-collision data collected by LHCb. The data set corresponds to integrated luminosities of 1.0 and 2.0 fb(-1) at center-of-mass energies of 7 and 8 TeV, respectively. This decay is observed for the first time, with a significance of more than 5 standard deviations. The analysis also results in an improved measurement of the branching fraction for the B-s(0) -> pi(+)pi(-) decay. The measured branching fractions are B(B-0 -> K+K-) = (7.80 +/- 1.27 +/- 0.81 +/- 0.21) x 10(-8) and B(B-s(0) -> pi(+)p(-)) = (6.91 +/- 0.54 +/- 0.63 +/- 0.19 +/- 0.40) x 10(-7). The first uncertainty is statistical, the second is systematic, the third is due to the uncertainty on the B-0 -> K+pi(-) branching fraction used as a normalization. For the B-s(0) mode, the fourth accounts for the uncertainty on the ratio of the probabilities for b quarks to hadronize into B-s(0) and B-0 mesons. |
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Address |
[Bediaga, I.; De Miranda, J. M.; Rodrigues, F. Ferreira; Gomes, A.; Massafferri, A.; dos Reis, A. C.; Rodrigues, A. B.; Vieira, D.] CBPF, Rio De Janeiro, Brazil |
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Amer Physical Soc |
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English |
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0031-9007 |
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Notes |
WOS:000394667300004 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
2965 |
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Author |
LHCb Collaboration (Aaij, R. et al); Garcia Martin, L.M.; Martinez-Vidal, F.; Oyanguren, A.; Remon Alepuz, C.; Ruiz Valls, P.; Sanchez Mayordomo, C. |
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Title |
Observation of the Decay Xi(-)(b) -> pK(-)K(-) |
Type |
Journal Article |
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Year |
2017 |
Publication |
Physical Review Letters |
Abbreviated Journal |
Phys. Rev. Lett. |
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Volume |
118 |
Issue |
7 |
Pages |
071801 - 11pp |
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Abstract |
Decays of the Xi(-)(b) and Omega(-)(b) baryons to the charmless final states ph(-)h'(-), where h((')) denotes a kaon or pion, are searched for with the LHCb detector. The analysis is based on a sample of proton-proton collision data collected at center-of-mass energies root s = 7 and 8 TeV, corresponding to an integrated luminosity of 3 fb(-1). The decay Xi(-)(b) -> pK(-)K(-) is observed with a significance of 8.7 standard deviations, and evidence at the level of 3.4 standard deviations is found for the Xi(-)(b) -> pK(-)pi(-) decay. Results are reported, relative to the B- -> K+K-K- normalization channel, for the products of branching fractions and b-hadron production fractions. The branching fractions of Xi(-)(b) -> pK(-)pi(-) and Xi(-)(b) -> p pi(-)pi(-) relative to Xi(-)(b) -> pK(-)K(-) decays are also measured. |
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Address |
[Bediaga, I.; Collazuol, G.; De Miranda, J. M.; Gomes, A.; Lucchesi, D.; Massafferri, A.; Molina Rodriguez, J.; dos Reis, A. C.; Rodrigues, A. B.; Salustino Guimaraes, V.; Soares Lavra, L.] CBPF, Rio De Janeiro, Brazil |
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Publisher |
Amer Physical Soc |
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English |
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ISSN |
0031-9007 |
ISBN |
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Conference |
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Notes |
WOS:000394096000003 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
2966 |
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Author |
AGATA Collaboration (Vogt, A. et al); Gadea, A. |
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Title |
Isomers and high-spin structures in the N=81 isotones Xe-135 and Ba-137 |
Type |
Journal Article |
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Year |
2017 |
Publication |
Physical Review C |
Abbreviated Journal |
Phys. Rev. C |
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Volume |
95 |
Issue |
2 |
Pages |
024316 - 17pp |
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Keywords |
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Abstract |
The high-spin structures and isomers of the N = 81 isotones Xe-135 and Ba-137 are investigated after multinucleon-transfer (MNT) and fusion-evaporation reactions. Both nuclei are populated (i) in Xe-136+ U-238 and (ii) Xe-136+ Pb-208 MNT reactions employing the high-resolution Advanced Gamma Tracking Array (AGATA) coupled to the magnetic spectrometer PRISMA, (iii) in the Xe-136+ Pt-198 MNT reaction employing the gamma-ray array GAMMASPHERE in combination with the gas-detector array CHICO, and (iv) via a B-11+ Te-130 fusion-evaporation reaction with the HORUS gamma-ray array at the University of Cologne. The high-spin level schemes of Xe-135 and Ba-137 are considerably extended to higher energies. The 2058-keV (19/2(-)) state in Xe-135 is identified as an isomer, closing a gap in the systematics along the N = 81 isotones. Its half-life is measured to be 9.0(9) ns, corresponding to a reduced transition probability of B(E2,19/2(-) -> 15/2(-)) = 0.52(6) W.u. The experimentally deduced reduced transition probabilities of the isomeric states are compared to shell-model predictions. Latest shell-model calculations reproduce the experimental findings generally well and provide guidance to the interpretation of the new levels. |
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Address |
[Vogt, A.; Birkenbach, B.; Reiter, P.; Blazhev, A.; Arnswald, K.; Eberth, J.; Fu, B.; Geibel, K.; Hess, H.; Hirsch, R.; Jolie, J.; Kaya, L.; Lewandowski, L.; Liang, X.; Mueller-Gatermann, C.; Queiser, M.; Radeck, F.; Rosiak, D.; Saed-Samii, N.; Schneiders, D.; Seidlitz, M.; Siebeck, B.; Steinbach, T.; Wiens, A.; Zell, K. O.] Univ Cologne, Inst Kernphys, D-50937 Cologne, Germany, Email: andreas.vogt@ikp.uni-koeln.de |
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Amer Physical Soc |
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English |
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2469-9985 |
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WOS:000393944100004 |
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no |
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yes |
International Collaboration |
yes |
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IFIC @ pastor @ |
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2967 |
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