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Author |
Davesne, D.; Pastore, A.; Navarro, J. |
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Title  |
Fitting (NLO)-L-3 pseudo-potentials through central plus tensor Landau parameters |
Type |
Journal Article |
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Year |
2014 |
Publication |
Journal of Physics G |
Abbreviated Journal |
J. Phys. G |
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Volume |
41 |
Issue |
6 |
Pages |
065104 - 12pp |
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Keywords |
Landau parameters; (NLO)-L-3; phenomenological interactions; fitting methods |
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Abstract |
Landau parameters determined from phenomenological finite-range interactions are used to get an estimation of next-to-next-to-next-to-leading order ((NLO)-L-3) pseudo-potentials parameters. The parameter sets obtained in this way are shown to lead to consistent results concerning saturation properties. The uniqueness of this procedure is discussed, and an estimate of the error induced by the truncation at (NLO)-L-3 is given. |
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Address |
[Davesne, D.] Univ Lyon, F-69622 Lyon, France, Email: davesne@inpl.in2p3.fr |
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Publisher |
Iop Publishing Ltd |
Place of Publication |
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Language |
English |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0954-3899 |
ISBN |
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Expedition |
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Conference |
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Notes |
WOS:000338425100009 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
1838 |
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Author |
Alcaide, J.; Salvado, J.; Santamaria, A. |
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Title |
Fitting flavour symmetries: the case of two-zero neutrino mass textures |
Type |
Journal Article |
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Year |
2018 |
Publication |
Journal of High Energy Physics |
Abbreviated Journal |
J. High Energy Phys. |
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Volume |
07 |
Issue |
7 |
Pages |
164 - 18pp |
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Keywords |
Neutrino Physics; Quark Masses and SM Parameters |
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Abstract |
We present a numeric method for the analysis of the fermion mass matrices predicted in flavour models. The method does not require any previous algebraic work, it offers a chi(2) comparison test and an easy estimate of confidence intervals. It can also be used to study the stability of the results when the predictions are disturbed by small perturbations. We have applied the method to the case of two-zero neutrino mass textures using the latest available fits on neutrino oscillations, derived the available parameter space for each texture and compared them. Textures A(1) and A(2) seem favoured because they give a small chi(2), allow for large regions in parameter space and give neutrino masses compatible with Cosmology limits. The other “allowed” textures remain allowed although with a very constrained parameter space, which, in some cases, could be in conflict with Cosmology. We have also revisited the “forbidden” textures and studied the stability of the results when the texture zeroes are not exact. Most of the forbidden textures remain forbidden, but textures F-1 and F-3 are particularly sensitive to small perturbations and could become allowed. |
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Address |
[Alcaide, Julien; Santamaria, Arcadi] Univ Valencia, Dept Fis Teor, Dr Moliner 50, E-46100 Valencia, Spain, Email: julien.alcaide@uv.es; |
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Corporate Author |
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Thesis |
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Publisher |
Springer |
Place of Publication |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Edition |
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ISSN |
1029-8479 |
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Area |
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Expedition |
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Conference |
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Notes |
WOS:000440091700010 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
3680 |
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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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Corporate Author |
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Thesis |
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Publisher |
Amer Geophysical Union |
Place of Publication |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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ISBN |
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Expedition |
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Conference |
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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 |
Ortiz Arciniega, J.L.; Carrio, F.; Valero, A. |
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Title |
FPGA implementation of a deep learning algorithm for real-time signal reconstruction in particle detectors under high pile-up conditions |
Type |
Journal Article |
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Year |
2019 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
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Volume |
14 |
Issue |
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Pages |
P09002 - 13pp |
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Keywords |
Data processing methods; Pattern recognition; cluster finding; calibration and fitting methods; Simulation methods and programs |
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Abstract |
The analog signals generated in the read-out electronics of particle detectors are shaped prior to the digitization in order to improve the signal to noise ratio (SNR). The real amplitude of the analog signal is then obtained using digital filters, which provides information about the energy deposited in the detector. The classical digital filters have a good performance in ideal situations with Gaussian electronic noise and no pulse shape distortion. However, high-energy particle colliders, such as the Large Hadron Collider (LHC) at CERN, can produce multiple simultaneous events, which produce signal pileup. The performance of classical digital filters deteriorates in these conditions since the signal pulse shape gets distorted. In addition, this type of experiments produces a high rate of collisions, which requires high throughput data acquisitions systems. In order to cope with these harsh requirements, new read-out electronics systems are based on high-performance FPGAs, which permit the utilization of more advanced real-time signal reconstruction algorithms. In this paper, a deep learning method is proposed for real-time signal reconstruction in high pileup particle detectors. The performance of the new method has been studied using simulated data and the results are compared with a classical FIR filter method. In particular, the signals and FIR filter used in the ATLAS Tile Calorimeter are used as benchmark. The implementation, resources usage and performance of the proposed Neural Network algorithm in FPGA are also presented. |
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Address |
[Ortiz Arciniega, J. L.] Univ Valencia, Avinguda Univ S-N, Burjassot, Spain, Email: orarjo@alumni.uv.es |
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Corporate Author |
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Thesis |
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Publisher |
Iop Publishing Ltd |
Place of Publication |
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Editor |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
1748-0221 |
ISBN |
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Medium |
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Area |
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Expedition |
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Conference |
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Notes |
WOS:000486990000002 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
4150 |
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Author |
de Souza, P.M.; Muller, A.; Beniaich, A.; Mayer-Miebach, E.; Oehlke, K.; Stahl, M.; Greiner, R.; Fernandez, A. |
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Title |
Functional properties and nutritional composition of liquid egg products treated in a coiled tube UV-C reactor |
Type |
Journal Article |
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Year |
2015 |
Publication |
Innovative Food Science & Emerging Technologies |
Abbreviated Journal |
Innov. Food Sci. Emerg. Technol. |
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Volume |
32 |
Issue |
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Pages |
156-164 |
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Keywords |
Ultraviolet; Liquid egg; Vitamins; Functional properties; Foaming; UV-C; Dean vortex |
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Abstract |
Pasteurization of eggs has adverse effects on nutrient composition and functionality of egg proteins. UV processing is an alternative technology with potentially fewer adverse effects as it is less intrusive. Egg white, whole egg and egg yolk vitamins (A, B-2, B-5, C and E), minerals (P, Cl, K, Na, Ca, Mg, Fe and Zn) and main secondary metabolites (lutein and zeaxanthin) were examined after exposure to UV in a coiled tube UV-C reactor at doses known to achieve microbiologically stable egg fractions. The studied nutrients were fairly stable to a treatment with UVC light with the exception of retinal, vitamin C and carotenoids, which showed loses up to 80%, 66% and 61%, respectively. Moreover, the functional properties of ultraviolet-treated eggs were investigated. Results showed a positive impact on the foam ability and foam stability, and an increase on the emulsifying activity index above 20% versus pasteurized samples. Processing with UV can maintain most of the egg nutritive properties, and retain or even improve the technological properties of foaming and emulsification in eggs. Industrial relevance:: This novel UV-C system can be applied successfully to the Food Industry. UV-C does not impair nutritional damage to egg-treated products, and even improve egg functional properties. |
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Address |
[Mendes de Souza, Poliana; Fernandez, Avelina] Inst Agroquim & Tecnol Alimentos, CSIC, Dept Conservat & Qual, Paterna 46980, Spain, Email: poliana.souza@ict.ufvjm.edu.br |
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Corporate Author |
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Thesis |
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Publisher |
Elsevier Sci Ltd |
Place of Publication |
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Editor |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
1466-8564 |
ISBN |
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Conference |
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Notes |
WOS:000366764200019 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
2506 |
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