Multiplicity dependence of (anti-)deuteron production in pp collisions at root s=7 TeV

none1019siIn this letter, the production of deuterons and anti-deuterons in pp collisions at root s = 7 TeV is studied as a function of the charged-particle multiplicity density at mid-rapidity with the ALICE detector at the LHC. Production yields are measured at mid-rapidity in five multiplicity classes and as a function of the deuteron transverse momentum (p(T)). The measurements are discussed in the context of hadron-coalescence models. The coalescence parameter B-2, extracted from the measured spectra of (anti-)deuteronsand primary (anti-)protons, exhibits no significant p(T)-dependence for p(T) < 3 GeV/c, in agreement with the expectations of a simple coalescence picture. At fixed transverse momentum per nucleon, the B-2 parameter is found to decrease smoothly from low multiplicity pp to Pb-Pb collisions, in qualitative agreement with more elaborate coalescence models. The measured mean transverse momentum of (anti-)deuterons in pp is not reproduced by the Blast-Wave model calculations that simultaneously describe pion, kaon and proton spectra, in contrast to central Pb-Pb collisions. The ratio between the p(T)-integrated yield of deuterons to protons, d/p, is found to increase with the charged-particle multiplicity, as observed in inelastic pp collisions at different centre-of-mass energies. The d/p ratios are reported in a wide range, from the lowest to the highest multiplicity values measured in pp collisions at the LHC. (C) 2019 The Author(s). Published by Elsevier B.VnoneAcharya, S.; Acosta, F. T.; Adamova, D.; Adhya, S. P.; Adler, A.; Adolfsson, J.; Aggarwal, M. M.; Rinella, G. Aglieri; Agnello, M.; Ahammed, Z.; Ahmad, S.; Ahn, S. U.; Aiola, S.; Akindinov, A.; Al-Turany, M.; Alam, S. N.; Albuquerque, D. S. D.; Aleksandrov, D.; Alessandro, B.; Alfanda, H. M.; Alfaro Molina, R.; Ali, B.; Ali, Y.; Alici, A.; Alkin, A.; Alme, J.; Alt, T.; Altenkamper, L.; Altsybeev, I; Anaam, M. N.; Andrei, C.; Andreou, D.; Andrews, H. A.; Andronic, A.; Angeletti, M.; Anguelov, V; Anson, C.; Anticic, T.; Antinori, F.; Antonioli, P.; Anwar, R.; Apadula, N.; Aphecetche, L.; Appelshaeuser, H.; Arcelli, S.; Arnaldi, R.; Arratia, M.; Arsene, I. C.; Arslandok, M.; Augustinus, A.; Averbeck, R.; Azmi, M. D.; Badala, A.; Baek, Y. W.; Bagnasco, S.; Bailhache, R.; Bala, R.; Baldisseri, A.; Ball, M.; Baral, R. C.; Barbera, R.; Barioglio, L.; Barnafoldi, G. G.; Barnby, L. S.; Barret, V; Bartalini, P.; Barth, K.; Bartsch, E.; Bastid, N.; Basu, S.; Batigne, G.; Batyunya, B.; Batzing, P. C.; Bauri, D.; Bazo Alba, J. L.; Bearden, I. G.; Bedda, C.; Behera, N. K.; Belikov, I; Bellini, F.; Bello Martinez, H.; Bellwied, R.; Beltran, L. G. E.; Belyaev, V; Bencedi, G.; Beole, S.; Bercuci, A.; Berdnikov, Y.; Berenyi, D.; Bertens, R. A.; Berzano, D.; Betev, L.; Bhasin, A.; Bhat, I. R.; Bhatt, H.; Bhattacharjee, B.; Bianchi, A.; Bianchi, L.; Bianchi, N.; Bielcik, J.; Bielcikova, J.; Bilandzic, A.; Biro, G.; Biswas, R.; Biswas, S.; Blair, J. T.; Blau, D.; Blume, C.; Boca, G.; Bock, F.; Bogdanov, A.; Boldizsar, L.; Bolozdynya, A.; Bombara, M.; Bonomi, G.; Bonora, M.; Borel, H.; Borissov, A.; Borri, M.; Botta, E.; Bourjau, C.; Bratrud, L.; Braun-Munzinger, P.; Bregant, M.; Broker, T. A.; Broz, M.; Brucken, E. J.; Bruna, E.; Bruno, G. E.; Buckland, M. D.; Budnikov, D.; Buesching, H.; Bufalino, S.; Buhler, P.; Buncic, P.; Busch, O.; Buthelezi, Z.; Butt, J. B.; Buxton, J. T.; Caffarri, D.; Caines, H.; Caliva, A.; Calvo Villar, E.; Camacho, R. S.; Camerini, P.; Capon, A. A.; Carnesecchi, F.; Castellanos, J. Castillo; Castro, A. J.; Casula, E. A. R.; Sanchez, C. Ceballos; Chakraborty, P.; Chandra, S.; Chang, B.; Chang, W.; Chapeland, S.; Chartier, M.; Chattopadhyay, S.; Chauvin, A.; Cheshkov, C.; Cheynis, B.; Barroso, V. Chibante; Chinellato, D. D.; Cho, S.; Chochula, P.; Chowdhury, T.; Christakoglou, P.; Christensen, C. H.; Christiansen, P.; Chujo, T.; Cicalo, C.; Cifarelli, L.; Cindolo, F.; Cleymans, J.; Colamaria, F.; Colella, D.; Collu, A.; Colocci, M.; Concas, M.; Balbastre, G. Conesa; del Valle, Z. Conesa; Contin, G.; Contreras, J. G.; Cormier, T. M.; Morales, Y. Corrales; Cortese, P.; Cosentino, M. R.; Costa, F.; Costanza, S.; Crkovska, J.; Crochet, P.; Cuautle, E.; Cunqueiro, L.; Dabrowski, D.; Dahms, T.; Dainese, A.; Damas, F. P. A.; Dani, S.; Danisch, M. C.; Danu, A.; Das, D.; Das, I; Das, S.; Dash, A.; Dash, S.; Dashi, A.; De, S.; De Caro, A.; de Cataldo, G.; de Conti, C.; de Cuveland, J.; De Falco, A.; De Gruttola, D.; De Marco, N.; De Pasquale, S.; De Souza, R. D.; Degenhardt, H. F.; Deisting, A.; Deloff, A.; Delsanto, S.; Dhankher, P.; Di Bari, D.; Di Mauro, A.; Diaz, R. A.; Dietel, T.; Dillenseger, P.; Ding, Y.; Divia, R.; Djuvsland, O.; Dobrin, A.; Domenicis Gimenez, D.; Doenigus, B.; Dordic, O.; Dubey, A. K.; Dubla, A.; Dudi, S.; Duggal, A. K.; Dukhishyam, M.; Dupieux, P.; Ehlers, R. J.; Elia, D.; Engel, H.; Epple, E.; Erazmus, B.; Erhardt, F.; Erokhin, A.; Ersdal, M. R.; Espagnon, B.; Eulisse, G.; Eum, J.; Evans, D.; Evdokimov, S.; Fabbietti, L.; Faggin, M.; Faivre, J.; Fantoni, A.; Fasel, M.; Feldkamp, L.; Feliciello, A.; Feofilov, G.; Fernandez Tellez, A.; Ferrero, A.; Ferretti, A.; Festanti, A.; Feuillard, V. J. G.; Figiel, J.; Filchagin, S.; Finogeev, D.; Fionda, F. M.; Fiorenza, G.; Flor, F.; Floris, M.; Foertsch, S.; Foka, P.; Fokin, S.; Fragiacomo, E.; Francisco, A.; Frankenfeld, U.; Fronze, G. G.; Fuchs, U.; Furget, C.; Furs, A.; Girard, M. Fusco; Gaardhoje, J. J.; Gagliardi, M.; Gago, A. M.; Gajdosova, K.; Galvan, C. D.; Ganoti, P.; Garabatos, C.; Garcia-Solis, E.; Garg, K.; Gargiulo, C.; Garner, K.; Gasik, P.; Gauger, E. 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C.; Arslandok, M.; Augustinus, A.; Averbeck, R.; Azmi, M. D.; Badala, A.; Baek, Y. W.; Bagnasco, S.; Bailhache, R.; Bala, R.; Baldisseri, A.; Ball, M.; Baral, R. C.; Barbera, R.; Barioglio, L.; Barnafoldi, G. G.; Barnby, L. S.; Barret, V; Bartalini, P.; Barth, K.; Bartsch, E.; Bastid, N.; Basu, S.; Batigne, G.; Batyunya, B.; Batzing, P. C.; Bauri, D.; Bazo Alba, J. L.; Bearden, I. G.; Bedda, C.; Behera, N. K.; Belikov, I; Bellini, F.; Bello Martinez, H.; Bellwied, R.; Beltran, L. G. E.; Belyaev, V; Bencedi, G.; Beole, S.; Bercuci, A.; Berdnikov, Y.; Berenyi, D.; Bertens, R. A.; Berzano, D.; Betev, L.; Bhasin, A.; Bhat, I. R.; Bhatt, H.; Bhattacharjee, B.; Bianchi, A.; Bianchi, L.; Bianchi, N.; Bielcik, J.; Bielcikova, J.; Bilandzic, A.; Biro, G.; Biswas, R.; Biswas, S.; Blair, J. T.; Blau, D.; Blume, C.; Boca, G.; Bock, F.; Bogdanov, A.; Boldizsar, L.; Bolozdynya, A.; Bombara, M.; Bonomi, G.; Bonora, M.; Borel, H.; Borissov, A.; Borri, M.; Botta, E.; Bourjau, C.; Bratrud, L.; Braun-Munzinger, P.; Bregant, M.; Broker, T. A.; Broz, M.; Brucken, E. J.; Bruna, E.; Bruno, G. E.; Buckland, M. D.; Budnikov, D.; Buesching, H.; Bufalino, S.; Buhler, P.; Buncic, P.; Busch, O.; Buthelezi, Z.; Butt, J. B.; Buxton, J. T.; Caffarri, D.; Caines, H.; Caliva, A.; Calvo Villar, E.; Camacho, R. S.; Camerini, P.; Capon, A. A.; Carnesecchi, F.; Castellanos, J. Castillo; Castro, A. J.; Casula, E. A. R.; Sanchez, C. Ceballos; Chakraborty, P.; Chandra, S.; Chang, B.; Chang, W.; Chapeland, S.; Chartier, M.; Chattopadhyay, S.; Chauvin, A.; Cheshkov, C.; Cheynis, B.; Barroso, V. Chibante; Chinellato, D. D.; Cho, S.; Chochula, P.; Chowdhury, T.; Christakoglou, P.; Christensen, C. H.; Christiansen, P.; Chujo, T.; Cicalo, C.; Cifarelli, L.; Cindolo, F.; Cleymans, J.; Colamaria, F.; Colella, D.; Collu, A.; Colocci, M.; Concas, M.; Balbastre, G. Conesa; del Valle, Z. Conesa; Contin, G.; Contreras, J. G.; Cormier, T. M.; Morales, Y. Corrales; Cortese, P.; Cosentino, M. R.; Costa, F.; Costanza, S.; Crkovska, J.; Crochet, P.; Cuautle, E.; Cunqueiro, L.; Dabrowski, D.; Dahms, T.; Dainese, A.; Damas, F. P. A.; Dani, S.; Danisch, M. C.; Danu, A.; Das, D.; Das, I; Das, S.; Dash, A.; Dash, S.; Dashi, A.; De, S.; De Caro, A.; de Cataldo, G.; de Conti, C.; de Cuveland, J.; De Falco, A.; De Gruttola, D.; De Marco, N.; De Pasquale, S.; De Souza, R. D.; Degenhardt, H. F.; Deisting, A.; Deloff, A.; Delsanto, S.; Dhankher, P.; Di Bari, D.; Di Mauro, A.; Diaz, R. A.; Dietel, T.; Dillenseger, P.; Ding, Y.; Divia, R.; Djuvsland, O.; Dobrin, A.; Domenicis Gimenez, D.; Doenigus, B.; Dordic, O.; Dubey, A. K.; Dubla, A.; Dudi, S.; Duggal, A. K.; Dukhishyam, M.; Dupieux, P.; Ehlers, R. 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K.; Kollegger, T.; Kondratyeva, N.; Kondratyuk, E.; Konopka, P. J.; Konyushikhin, M.; Koska, L.; Kovalenko, O.; Kovalenko, V; Kowalski, M.; Kralik, I; Krav

Road user abnormal trajectory detection using a deep autoencoder

In this paper, we focus on the development of a method that detects abnormal trajectories of road users at traffic intersections. The main difficulty with this is the fact that there are very few abnormal data and the normal ones are insufficient for the training of any kinds of machine learning model. To tackle these problems, we proposed the solution of using a deep autoencoder network trained solely through augmented data considered as normal. By generating artificial abnormal trajectories, our method is tested on four different outdoor urban users scenes and performs better compared to some classical outlier detection methods.Comment: This paper has been accepted for oral presentation at ISVC'1

A Robust Fusion Model for Estimating Respiratory Rate From Photoplethysmography and Electrocardiography

Objective: Respiratory rate (RR) estimation algorithms based on the photoplethymogram (PPG) and electrocardiogram (ECG) lack clinical robustness. This is because the PPG and ECG respiratory modulations are dependent on patient physiology, regardless of general signal quality. The present work describes an RR estimation algorithm using respiratory quality indices (RQIs) which assess the presence or absence of the PPGand ECG-derived respiratory modulations. Methods: Six respiratory waveforms are derived from the amplitude modulation, frequency modulation, and baseline wander of the PPG and ECG. The respiratory quality of each modulation is assessed using RQIs based on the FFT, autoregression, and autocorrelation. The individual RQIs are fused to obtain a single RQI per modulation per time window. Based on a tunable threshold, the RQIs are used to discard poor modulations and weight the remaining modulations to provide a single RR estimation per time window. Results: The proposed method was tested on two independent data sets and found that using a conservative threshold, the mean absolute error (MAE) was 0.71 andplusmn; 0.89 and 3.12 andplusmn; 4.39 brpm while discarding only 1.3% and 23.2% of all time windows, for each data set, respectively. Conclusion: These errors are either better than or comparable to current methods, and the number of windows discarded is far lower demonstrating improved robustness. Significance: This work describes a novel pre-processing algorithm that can be implemented in conjunction with other RR estimation techniques to improve robustness by specifically considering the quality of the respiratory information.</p

The Effect of Fractional Inspired Oxygen Concentration on Early Warning Score Performance: a database analysis

Objectives To calculate fractional inspired oxygen concentration (FiO2) thresholds in ward patients and add these to the National Early Warning Score (NEWS). To evaluate the performance of NEWS-FiO2 against NEWS when predicting in-hospital death and unplanned intensive care unit (ICU) admission. Methods A multi-centre, retrospective, observational cohort study was carried out in five hospitals from two UK NHS Trusts. Adult admissions with at least one complete set of vital sign observations recorded electronically were eligible. The primary outcome measure was an ‘adverse event’ which comprised either in-hospital death or unplanned ICU admission. Discrimination was assessed using the Area Under the Receiver Operating Characteristic curve (AUROC). Results A cohort of 83,304 patients from a total of 271,363 adult admissions were prescribed oxygen. In this cohort, NEWS-FiO2 (AUROC 0.823, 95% CI 0.819–0.824) outperformed NEWS (AUORC 0.811, 95% CI 0.809–0.814) when predicting in-hospital death or unplanned ICU admission within 24 h of a complete set of vital sign observations. Conclusions NEWS-FiO2 generates a performance gain over NEWS when studied in ward patients requiring oxygen. This warrants further study, particularly in patients with respiratory disorders

Concept drift adaption for online anomaly detection in structural health monitoring

© 2019 Association for Computing Machinery. Despite its success for anomaly detection in the scenario where only data representing normal behavior are available, one-class support vector machine (OCSVM) still has challenge in dealing with non-stationary data stream, where the underlying distributions of data are time-varying. Existing OCSVM-based online learning methods incrementally update the model to address the challenge, however, they solely rely on the location relationship between a test sample and error support vectors. To better accommodate normal behavior evolution, online anomaly detection in non-stationary data stream is formulated as a concept drift adaptation problem in this paper. It is proposed that OCSVM-based incremental learning is only performed in the case of a normal drift. For an incoming sample, its relative relationship with three sets of vectors in OCSVM, namely margin support vectors, error support vectors, and reserve vectors is fully utilized to estimate whether a normal drift is emerging. Extensive experiments in the field of structural health monitoring have been conducted and the results have shown that the proposed simple approach outperforms the existing OCSVM-based online learning algorithms for anomaly detection

Digital Signal Processing for Audio Applications: Then, Now and the Future

none7noneFrancesco Piazza, Stefano Squartini, Stefania Cecchi, Simone Fiori, Simone Orcioni, Susanna Spinsante, Stefano PiraniPiazza, Francesco; Squartini, Stefano; Cecchi, Stefania; Fiori, Simone; Orcioni, Simone; Spinsante, Susanna; Pirani, Stefan

Multiplicity dependence of (anti-)deuteron production in pp collisions at 1as=7TeV

In this letter, the production of deuterons and anti-deuterons in pp collisions at 1as = 7 TeV is studied as a function of the charged-particle multiplicity density at mid-rapidity with the ALICE detector at the LHC. Production yields are measured at mid-rapidity in five multiplicity classes and as a function of the deuteron transverse momentum (pT). The measurements are discussed in the context of hadron\u2013coalescence models. The coalescence parameter B2, extracted from the measured spectra of (anti-)deuterons and primary (anti-)protons, exhibits no significant pT-dependence for pT < 3 GeV/c, in agreement with the expectations of a simple coalescence picture. At fixed transverse momentum per nucleon, the B2 parameter is found to decrease smoothly from low multiplicity pp to Pb\u2013Pb collisions, in qualitative agreement with more elaborate coalescence models. The measured mean transverse momentum of (anti-)deuterons in pp is not reproduced by the Blast-Wave model calculations that simultaneously describe pion, kaon and proton spectra, in contrast to central Pb\u2013Pb collisions. The ratio between the pT-integrated yield of deuterons to protons, d/p, is found to increase with the charged- particle multiplicity, as observed in inelastic pp collisions at different centre-of-mass energies. The d/p ratios are reported in a wide range, from the lowest to the highest multiplicity values measured in pp collisions at the LHC

Measurement of electrons from semileptonic heavy-flavour hadron decays at midrapidity in pp and Pb–Pb collisions at √sNN = 5.02 TeV

The differential invariant yield as a function of transverse momentum (pT) of electrons from semileptonic heavy-flavour hadron decays was measured at midrapidity in central (0–10%), semi-central (30–50%) and peripheral (60–80%) lead–lead (Pb–Pb) collisions at √sNN = 5.02 TeV in the pT intervals 0.5–26 GeV/c (0–10% and 30–50%) and 0.5–10 GeV/c (60–80%). The production cross section in proton–proton (pp) collisions at √s = 5.02 TeV was measured as well in 0.5 < pT < 10 GeV/c and it lies close to the upper band of perturbative QCD calculation uncertainties up to pT = 5 GeV/c and close to the mean value for larger pT. The modification of the electron yield with respect to what is expected for an incoherent superposition of nucleon–nucleon collisions is evaluated by measuring the nuclear modification factor RAA. The measurement of the RAA in different centrality classes allows in-medium energy loss of charm and beauty quarks to be investigated. The RAA shows a suppression with respect to unity at intermediate pT, which increases while moving towards more central collisions. Moreover, the measured RAA is sensitive to the modification of the parton distribution functions (PDF) in nuclei, like nuclear shadowing, which causes a suppression of the heavy-quark production at low pT in heavy-ion collisions at LHC