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Article: Supervised learning for improving the accuracy of robot-mounted 3D camera applied to human gait analysis.

Guffanti, Diego / Brunete, Alberto / Hernando, Miguel / Álvarez, David / Rueda, Javier / Navarro, Enrique

2024 Volume 10, Issue 4, Page(s) e26227

Abstract: Background and objective: the use of 3D cameras for gait analysis has been highly questioned due to the low accuracy they have demonstrated in the past. The objective of the study presented in this paper is to improve the accuracy of the estimations ... ...

Abstract	Background and objective: the use of 3D cameras for gait analysis has been highly questioned due to the low accuracy they have demonstrated in the past. The objective of the study presented in this paper is to improve the accuracy of the estimations made by robot-mounted 3D cameras in human gait analysis by applying a supervised learning stage. Methods: the 3D camera was mounted in a mobile robot to obtain a longer walking distance. This study shows an improvement in detection of kinematic gait signals and gait descriptors by post-processing the raw estimations of the camera using artificial neural networks trained with the data obtained from a certified Vicon system. To achieve this, 37 healthy participants were recruited and data of 207 gait sequences were collected using an Orbbec Astra 3D camera. There are two basic possible approaches for training and both have been studied in order to see which one achieves a better result. The artificial neural network can be trained either to obtain more accurate kinematic gait signals or to improve the gait descriptors obtained after initial processing. The former seeks to improve the waveforms of kinematic gait signals by reducing the error and increasing the correlation with respect to the Vicon system. The second is a more direct approach, focusing on training the artificial neural networks using gait descriptors directly. Results: the accuracy of the 3D camera to objectify human gait was measured before and after training. In both training approaches, a considerable improvement was observed. Kinematic gait signals showed lower errors and higher correlations with respect to the ground truth. The accuracy of the system to detect gait descriptors also showed a substantial improvement, mostly for kinematic descriptors rather than spatio-temporal. When comparing both training approaches, it was not possible to define which was the absolute best. Conclusions: supervised learning improves the accuracy of 3D cameras but the selection of the training approach will depend on the purpose of the study to be conducted. This study reveals the great potential of 3D cameras and encourages the research community to continue exploring their use in gait analysis.
Language	English
Publishing date	2024-02-13
Publishing country	England
Document type	Journal Article
ZDB-ID	2835763-2
ISSN	2405-8440
ISSN	2405-8440
DOI	10.1016/j.heliyon.2024.e26227
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Performance of a Mobile 3D Camera to Evaluate Simulated Pathological Gait in Practical Scenarios.

Guffanti, Diego / Lemus, Daniel / Vallery, Heike / Brunete, Alberto / Hernando, Miguel / Horemans, Herwin

Sensors (Basel, Switzerland)

2023 Volume 23, Issue 15

Abstract: Three-dimensional (3D) cameras used for gait assessment obviate the need for bodily markers or sensors, making them particularly interesting for clinical applications. Due to their limited field of view, their application has predominantly focused on ... ...

Abstract	Three-dimensional (3D) cameras used for gait assessment obviate the need for bodily markers or sensors, making them particularly interesting for clinical applications. Due to their limited field of view, their application has predominantly focused on evaluating gait patterns within short walking distances. However, assessment of gait consistency requires testing over a longer walking distance. The aim of this study is to validate the accuracy for gait assessment of a previously developed method that determines walking spatiotemporal parameters and kinematics measured with a 3D camera mounted on a mobile robot base (ROBOGait). Walking parameters measured with this system were compared with measurements with Xsens IMUs. The experiments were performed on a non-linear corridor of approximately 50 m, resembling the environment of a conventional rehabilitation facility. Eleven individuals exhibiting normal motor function were recruited to walk and to simulate gait patterns representative of common neurological conditions: Cerebral Palsy, Multiple Sclerosis, and Cerebellar Ataxia. Generalized estimating equations were used to determine statistical differences between the measurement systems and between walking conditions. When comparing walking parameters between paired measures of the systems, significant differences were found for eight out of 18 descriptors: range of motion (ROM) of trunk and pelvis tilt, maximum knee flexion in loading response, knee position at toe-off, stride length, step time, cadence; and stance duration. When analyzing how ROBOGait can distinguish simulated pathological gait from physiological gait, a mean accuracy of 70.4%, a sensitivity of 49.3%, and a specificity of 74.4% were found when compared with the Xsens system. The most important gait abnormalities related to the clinical conditions were successfully detected by ROBOGait. The descriptors that best distinguished simulated pathological walking from normal walking in both systems were step width and stride length. This study underscores the promising potential of 3D cameras and encourages exploring their use in clinical gait analysis.
MeSH term(s)	Humans ; Gait/physiology ; Walking/physiology ; Lower Extremity ; Knee ; Knee Joint ; Biomechanical Phenomena
Language	English
Publishing date	2023-08-04
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2052857-7
ISSN	1424-8220 ; 1424-8220
ISSN (online)	1424-8220
ISSN	1424-8220
DOI	10.3390/s23156944
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Article: The Effect of Flushing on the Nitrate Content and Postharvest Quality of Lettuce (Lactuca sativa L. Var. Acephala) and Rocket (Eruca sativa Mill.) Grown in a Vertical Farm

Guffanti, Davide / Cocetta, Giacomo / Franchetti, Benjamin M. / Ferrante, Antonio

Horticulturae. 2022 July 04, v. 8, no. 7

2022

Abstract: Hydroponics is the most widely used technique in closed cultivation environments, and this system is often used for the cultivation of baby leaf vegetables. These species can accumulate high levels of nitrates; for this reason, the control of growing ... ...

Abstract	Hydroponics is the most widely used technique in closed cultivation environments, and this system is often used for the cultivation of baby leaf vegetables. These species can accumulate high levels of nitrates; for this reason, the control of growing conditions is a crucial factor for limiting their content, especially in protected cultivations. The aim of this work was to reduce nitrate accumulation in leafy vegetables grown in a vertical farm while preserving the quality at harvest as well as during storage. This objective was achieved by completely replacing the nutrient solution with water a few hours before harvest (“flushing”). The trials were carried out on lettuce (Lactuca sativa L. Var. Acephala, cv. Greenet) and rocket (Eruca sativa Mill., cv. Rome). Three independent trials were conducted on lettuce, applying the flushing treatment 24 h and 48 h prior to harvest. One trial was conducted on rocket, applying the treatment 48 h before harvesting. Sampling and related analyses were carried out at harvest and during the storage period to determine chlorophyll, leaf fluorescence, total sugars, chlorophyll (a + b), carotenoids, phenolic index, anthocyanins and nitrate content. Moreover, relative humidity (RH%), O₂% and CO₂% determination inside the package headspace were monitored during storage. The results obtained indicate that it is possible to reduce the nitrate concentration by up to 56% in lettuce and 61% in rocket while maintaining the product quality of baby leaves by replacing the nutrient solution with tap water before harvest.
Keywords	Eruca vesicaria subsp. sativa ; Lactuca sativa ; anthocyanins ; carotenoids ; chlorophyll ; fluorescence ; headspace analysis ; hydroponics ; leaves ; lettuce ; nitrates ; nutrient solutions ; relative humidity ; storage quality ; storage time ; tap water ; vertical farming
Language	English
Dates of publication	2022-0704
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article
ZDB-ID	2813983-5
ISSN	2311-7524
ISSN	2311-7524
DOI	10.3390/horticulturae8070604
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: ROBOGait: A Mobile Robotic Platform for Human Gait Analysis in Clinical Environments.

Guffanti, Diego / Brunete, Alberto / Hernando, Miguel / Rueda, Javier / Navarro, Enrique

Sensors (Basel, Switzerland)

2021 Volume 21, Issue 20

Abstract: Mobile robotic platforms have made inroads in the rehabilitation area as gait assistance devices. They have rarely been used for human gait monitoring and analysis. The integration of mobile robots in this field offers the potential to develop multiple ... ...

Abstract	Mobile robotic platforms have made inroads in the rehabilitation area as gait assistance devices. They have rarely been used for human gait monitoring and analysis. The integration of mobile robots in this field offers the potential to develop multiple medical applications and achieve new discoveries. This study proposes the use of a mobile robotic platform based on depth cameras to perform the analysis of human gait in practical scenarios. The aim is to prove the validity of this robot and its applicability in clinical settings. The mechanical and software design of the system is presented, as well as the design of the controllers of the lane-keeping, person-following, and servoing systems. The accuracy of the system for the evaluation of joint kinematics and the main gait descriptors was validated by comparison with a Vicon-certified system. Some tests were performed in practical scenarios, where the effectiveness of the lane-keeping algorithm was evaluated. Clinical tests with patients with multiple sclerosis gave an initial impression of the applicability of the instrument in patients with abnormal walking patterns. The results demonstrate that the system can perform gait analysis with high accuracy. In the curved sections of the paths, the knee joint is affected by occlusion and the deviation of the person in the camera reference system. This issue was greatly improved by adjusting the servoing system and the following distance. The control strategy of this robot was specifically designed for the analysis of human gait from the frontal part of the participant, which allows one to capture the gait properly and represents one of the major contributions of this study in clinical practice.
MeSH term(s)	Biomechanical Phenomena ; Gait ; Gait Analysis ; Gait Disorders, Neurologic ; Humans ; Robotic Surgical Procedures ; Robotics ; Walking
Language	English
Publishing date	2021-10-13
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2052857-7
ISSN	1424-8220 ; 1424-8220
ISSN (online)	1424-8220
ISSN	1424-8220
DOI	10.3390/s21206786
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Book ; Online: Supervised learning for improving the accuracy of robot-mounted 3D camera applied to human gait analysis

Guffanti, Diego / Brunete, Alberto / Hernando, Miguel / Álvarez, David / Rueda, Javier / Navarro, Enrique

2022

Abstract: The use of 3D cameras for gait analysis has been highly questioned due to the low accuracy they have demonstrated in the past. The objective of the study presented in this paper is to improve the accuracy of the estimations made by robot-mounted 3D ... ...

Abstract	The use of 3D cameras for gait analysis has been highly questioned due to the low accuracy they have demonstrated in the past. The objective of the study presented in this paper is to improve the accuracy of the estimations made by robot-mounted 3D cameras in human gait analysis by applying a supervised learning stage. The 3D camera was mounted in a mobile robot to obtain a longer walking distance. This study shows an improvement in detection of kinematic gait signals and gait descriptors by post-processing the raw estimations of the camera using artificial neural networks trained with the data obtained from a certified Vicon system. To achieve this, 37 healthy participants were recruited and data of 207 gait sequences were collected using an Orbbec Astra 3D camera. There are two basic possible approaches for training: using kinematic gait signals and using gait descriptors. The former seeks to improve the waveforms of kinematic gait signals by reducing the error and increasing the correlation with respect to the Vicon system. The second is a more direct approach, focusing on training the artificial neural networks using gait descriptors directly. The accuracy of the 3D camera was measured before and after training. In both training approaches, an improvement was observed. Kinematic gait signals showed lower errors and higher correlations with respect to the ground truth. The accuracy of the system to detect gait descriptors also showed a substantial improvement, mostly for kinematic descriptors rather than spatio-temporal. When comparing both training approaches, it was not possible to define which was the absolute best. Therefore, we believe that the selection of the training approach will depend on the purpose of the study to be conducted. This study reveals the great potential of 3D cameras and encourages the research community to continue exploring their use in gait analysis. Comment: This manuscript is in a review process in the Journal of Artificial Intelligence in Medicine, Elsevier
Keywords	Computer Science - Computer Vision and Pattern Recognition ; Computer Science - Artificial Intelligence
Subject code	629
Publishing date	2022-07-03
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: The Accuracy of the Microsoft Kinect V2 Sensor for Human Gait Analysis. A Different Approach for Comparison with the Ground Truth.

Guffanti, Diego / Brunete, Alberto / Hernando, Miguel / Rueda, Javier / Navarro Cabello, Enrique

Sensors (Basel, Switzerland)

2020 Volume 20, Issue 16

Abstract: Several studies have examined the accuracy of the Kinect V2 sensor during gait analysis. Usually the data retrieved by the Kinect V2 sensor are compared with the ground truth of certified systems using a Euclidean comparison. Due to the Kinect V2 sensor ... ...

Abstract	Several studies have examined the accuracy of the Kinect V2 sensor during gait analysis. Usually the data retrieved by the Kinect V2 sensor are compared with the ground truth of certified systems using a Euclidean comparison. Due to the Kinect V2 sensor latency, the application of a uniform temporal alignment is not adequate to compare the signals. On that basis, the purpose of this study was to explore the abilities of the dynamic time warping (DTW) algorithm to compensate for sensor latency (3 samples or 90 ms) and develop a proper accuracy estimation. During the experimental stage, six iterations were performed using the a dual Kinect V2 system. The walking tests were developed at a self-selected speed. The sensor accuracy for Euclidean matching was consistent with that reported in previous studies. After latency compensation, the sensor accuracy demonstrated considerably lower error rates for all joints. This demonstrated that the accuracy was underestimated due to the use of inappropriate comparison techniques. On the contrary, DTW is a potential method that compensates for the sensor latency, and works sufficiently in comparison with certified systems.
MeSH term(s)	Algorithms ; Biomechanical Phenomena ; Gait ; Gait Analysis ; Humans ; Software ; Walk Test
Language	English
Publishing date	2020-08-07
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2052857-7
ISSN	1424-8220 ; 1424-8220
ISSN (online)	1424-8220
ISSN	1424-8220
DOI	10.3390/s20164405
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Book ; Online: Assessment of few-hits machine learning classification algorithms for low energy physics in liquid argon detectors

Biassoni, Matteo / Giachero, Andrea / Grossi, Michele / Guffanti, Daniele / Labranca, Danilo / Moretti, Roberto / Rossi, Marco / Terranova, Francesco / Vallecorsa, Sofia

2023

Abstract: The physics potential of massive liquid argon TPCs in the low-energy regime is still to be fully reaped because few-hits events encode information that can hardly be exploited by conventional classification algorithms. Machine learning (ML) techniques ... ...

Abstract	The physics potential of massive liquid argon TPCs in the low-energy regime is still to be fully reaped because few-hits events encode information that can hardly be exploited by conventional classification algorithms. Machine learning (ML) techniques give their best in these types of classification problems. In this paper, we evaluate their performance against conventional (deterministic) algorithms. We demonstrate that both Convolutional Neural Networks (CNN) and Transformer-Encoder methods outperform deterministic algorithms in one of the most challenging classification problems of low-energy physics (single- versus double-beta events). We discuss the advantages and pitfalls of Transformer-Encoder methods versus CNN and employ these methods to optimize the detector parameters, with an emphasis on the DUNE Phase II detectors ("Module of Opportunity").
Keywords	Physics - Instrumentation and Detectors ; Computer Science - Machine Learning ; Physics - Data Analysis ; Statistics and Probability
Subject code	006
Publishing date	2023-05-16
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: A Call to Arms Control

Akindele, T. / Anderson, T. / Anderssen, E. / Askins, M. / Bohles, M. / Bacon, A. J. / Bagdasarian, Z. / Baldoni, A. / Barna, A. / Barros, N. / Bartoszek, L. / Bat, A. / Beier, E. W. / Benson, T. / Bergevin, M. / Bernstein, A. / Birrittella, B. / Blucher, E. / Boissevain, J. /

Bonventre, R. / Borusinki, J. / Bourret, E. / Brown, D. / Callaghan, E. J. / Caravaca, J. / Chen, M. / Cowen, D. F. / Crow, B. / Dalnoki-Veress, F. / Danielson, D. / Dazeley, S. / Diwan, M. / Djurcic, Z. / Druetzler, A. / Dye, S. / Dye, S. T. / Eisch, J. / Elagin, A. / Enqvist, T. / Erlandson, Andrew / Fahrendholz, U. / Fienberg, A. / Fischer, V. / Frankiewicz, K. / Garzelli, M. V. / Gooding, D. / Graham, C. / Grant, C. / Griskevich, J. / Guffanti, D.

Synergies between Nonproliferation Applications of Neutrino Detectors and Large-Scale Fundamental Neutrino Physics Experiments

2022

Abstract: The High Energy Physics community can benefit from a natural synergy in research activities into next-generation large-scale water and scintillator neutrino detectors, now being studied for remote reactor monitoring, discovery and exclusion applications ... ...

Abstract	The High Energy Physics community can benefit from a natural synergy in research activities into next-generation large-scale water and scintillator neutrino detectors, now being studied for remote reactor monitoring, discovery and exclusion applications in cooperative nonproliferation contexts. Since approximately 2010, US nonproliferation researchers, supported by the National Nuclear Security Administration (NNSA), have been studying a range of possible applications of relatively large (100 ton) to very large (hundreds of kiloton) water and scintillator neutrino detectors. In parallel, the fundamental physics community has been developing detectors at similar scales and with similar design features for a range of high-priority physics topics, primarily in fundamental neutrino physics. These topics include neutrino oscillation studies at beams and reactors, solar, and geological neutrino measurements, supernova studies, and others. Examples of ongoing synergistic work at U.S. national laboratories and universities include prototype gadolinium-doped water and water-based and opaque scintillator test-beds and demonstrators, extensive testing and industry partnerships related to large area fast position-sensitive photomultiplier tubes, and the development of concepts for a possible underground kiloton-scale water-based detector for reactor monitoring and technology demonstrations. Some opportunities for engagement between the two communities include bi-annual Applied Antineutrino Physics conferences, collaboration with U.S. National Laboratories engaging in this research, and occasional NNSA funding opportunities supporting a blend of nonproliferation and basic science R&D, directed at the U.S. academic community. Comment: contribution to Snowmass 2021
Keywords	Physics - Instrumentation and Detectors ; High Energy Physics - Experiment ; Physics - Physics and Society
Subject code	306
Publishing date	2022-02-28
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: First Directional Measurement of Sub-MeV Solar Neutrinos with Borexino.

Agostini, M / Altenmüller, K / Appel, S / Atroshchenko, V / Bagdasarian, Z / Basilico, D / Bellini, G / Benziger, J / Biondi, R / Bravo, D / Caccianiga, B / Calaprice, F / Caminata, A / Cavalcante, P / Chepurnov, A / D'Angelo, D / Davini, S / Derbin, A / Di Giacinto, A /

Di Marcello, V / Ding, X F / Di Ludovico, A / Di Noto, L / Drachnev, I / Formozov, A / Franco, D / Galbiati, C / Ghiano, C / Giammarchi, M / Goretti, A / Göttel, A S / Gromov, M / Guffanti, D / Ianni, Aldo / Ianni, Andrea / Jany, A / Jeschke, D / Kobychev, V / Korga, G / Kumaran, S / Laubenstein, M / Litvinovich, E / Lombardi, P / Lomskaya, I / Ludhova, L / Lukyanchenko, G / Lukyanchenko, L / Machulin, I / Martyn, J / Meroni, E / Meyer, M / Miramonti, L / Misiaszek, M / Muratova, V / Neumair, B / Nieslony, M / Nugmanov, R / Oberauer, L / Orekhov, V / Ortica, F / Pallavicini, M / Papp, L / Pelicci, L / Penek, Ö / Pietrofaccia, L / Pilipenko, N / Pocar, A / Raikov, G / Ranalli, M T / Ranucci, G / Razeto, A / Re, A / Redchuk, M / Romani, A / Rossi, N / Schönert, S / Semenov, D / Settanta, G / Skorokhvatov, M / Singhal, A / Smirnov, O / Sotnikov, A / Suvorov, Y / Tartaglia, R / Testera, G / Thurn, J / Unzhakov, E / Vishneva, A / Vogelaar, R B / von Feilitzsch, F / Wessel, A / Wojcik, M / Wonsak, B / Wurm, M / Zavatarelli, S / Zuber, K / Zuzel, G

Physical review letters

2022 Volume 128, Issue 9, Page(s) 91803

Abstract: We report the measurement of sub-MeV solar neutrinos through the use of their associated Cherenkov radiation, performed with the Borexino detector at the Laboratori Nazionali del Gran Sasso. The measurement is achieved using a novel technique that ... ...

Abstract	We report the measurement of sub-MeV solar neutrinos through the use of their associated Cherenkov radiation, performed with the Borexino detector at the Laboratori Nazionali del Gran Sasso. The measurement is achieved using a novel technique that correlates individual photon hits of events to the known position of the Sun. In an energy window between 0.54 to 0.74 MeV, selected using the dominant scintillation light, we have measured 10 887_{-2103}^{+2386}(stat)±947(syst) (68% confidence interval) solar neutrinos out of 19 904 total events. This corresponds to a ^{7}Be neutrino interaction rate of 51.6_{-12.5}^{+13.9} counts/(day·100 ton), which is in agreement with the standard solar model predictions and the previous spectroscopic results of Borexino. The no-neutrino hypothesis can be excluded with >5σ confidence level. For the first time, we have demonstrated the possibility of utilizing the directional Cherenkov information for sub-MeV solar neutrinos, in a large-scale, high light yield liquid scintillator detector. This measurement provides an experimental proof of principle for future hybrid event reconstruction using both Cherenkov and scintillation signatures simultaneously.
Language	English
Publishing date	2022-03-18
Publishing country	United States
Document type	Journal Article
ZDB-ID	208853-8
ISSN	1079-7114 ; 0031-9007
ISSN (online)	1079-7114
ISSN	0031-9007
DOI	10.1103/PhysRevLett.128.091803
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Article: Scintillation light detection in the 6-m drift-length ProtoDUNE Dual Phase liquid argon TPC.

Abud, A Abed / Abi, B / Acciarri, R / Acero, M A / Adames, M R / Adamov, G / Adamowski, M / Adams, D / Adinolfi, M / Aduszkiewicz, A / Aguilar, J / Ahmad, Z / Ahmed, J / Aimard, B / Ali-Mohammadzadeh, B / Alion, T / Allison, K / Monsalve, S Alonso / AlRashed, M /

Alt, C / Alton, A / Alvarez, R / Amedo, P / Anderson, J / Andreopoulos, C / Andreotti, M / Andrews, M / Andrianala, F / Andringa, S / Anfimov, N / Ankowski, A / Antoniassi, M / Antonova, M / Antoshkin, A / Antusch, S / Aranda-Fernandez, A / Arellano, L / Arnold, L O / Arroyave, M A / Asaadi, J / Asquith, L / Aurisano, A / Aushev, V / Autiero, D / Lara, V Ayala / Ayala-Torres, M / Azfar, F / Back, A / Back, H / Back, J J / Backhouse, C / Bagaturia, I / Bagby, L / Balashov, N / Balasubramanian, S / Baldi, P / Baller, B / Bambah, B / Barao, F / Barenboim, G / Alzas, P Barham / Barker, G / Barkhouse, W / Barnes, C / Barr, G / Monarca, J Barranco / Barros, A / Barros, N / Barrow, J L / Basharina-Freshville, A / Bashyal, A / Basque, V / Batchelor, C / Chagas, E Batista das / Battat, J B R / Battisti, F / Bay, F / Bazetto, M C Q / Alba, J L L Bazo / Beacom, J F / Bechetoille, E / Behera, B / Beigbeder, C / Bellantoni, L / Bellettini, G / Bellini, V / Beltramello, O / Benekos, N / Montiel, C Benitez / Neves, F Bento / Berger, J / Berkman, S / Bernardini, P / Berner, R M / Bersani, A / Bertolucci, S / Betancourt, M / Rodríguez, A Betancur / Bevan, A / Bezawada, Y / Bezerra, T J C / Bhardwaj, A / Bhatnagar, V / Bhattacharjee, M / Bhattarai, D / Bhuller, S / Bhuyan, B / Biagi, S / Bian, J / Biassoni, M / Biery, K / Bilki, B / Bishai, M / Bitadze, A / Blake, A / Blaszczyk, F / Blazey, G C / Blucher, E / Boissevain, J / Bolognesi, S / Bolton, T / Bomben, L / Bonesini, M / Bongrand, M / Bonilla-Diaz, C / Bonini, F / Booth, A / Boran, F / Bordoni, S / Borkum, A / Bostan, N / Bour, P / Bourgeois, C / Boyden, D / Bracinik, J / Braga, D / Brailsford, D / Branca, A / Brandt, A / Bremer, J / Breton, D / Brew, C / Brice, S J / Brizzolari, C / Bromberg, C / Brooke, J / Bross, A / Brunetti, G / Brunetti, M / Buchanan, N / Budd, H / Butorov, I / Cagnoli, I / Cai, T / Caiulo, D / Calabrese, R / Calafiura, P / Calcutt, J / Calin, M / Calvez, S / Calvo, E / Caminata, A / Campanelli, M / Caratelli, D / Carber, D / Carceller, J C / Carini, G / Carlus, B / Carneiro, M F / Carniti, P / Terrazas, I Caro / Carranza, H / Carroll, T / Forero, J F Castaño / Castillo, A / Castromonte, C / Catano-Mur, E / Cattadori, C / Cavalier, F / Cavallaro, G / Cavanna, F / Centro, S / Cerati, G / Cervelli, A / Villanueva, A Cervera / Chalifour, M / Chappell, A / Chardonnet, E / Charitonidis, N / Chatterjee, A / Chattopadhyay, S / Neyra, M S S Chavarry / Chen, H / Chen, M / Chen, Y / Chen, Z / Chen-Wishart, Z / Cheon, Y / Cherdack, D / Chi, C / Childress, S / Chirco, R / Chiriacescu, A / Chisnall, G / Cho, K / Choate, S / Chokheli, D / Chong, P S / Christensen, A / Christian, D / Christodoulou, G / Chukanov, A / Chung, M / Church, E / Cicero, V / Clarke, P / Cline, G / Coan, T E / Cocco, A G / Coelho, J A B / Colton, N / Conley, E / Conley, R / Conrad, J / Convery, M / Copello, S / Cova, P / Cremaldi, L / Cremonesi, L / Crespo-Anadón, J I / Crisler, M / Cristaldo, E / Crnkovic, J / Cross, R / Cudd, A / Cuesta, C / Cui, Y / Cussans, D / Dalager, O / da Motta, H / Da Silva Peres, L / David, C / David, Q / Davies, G S / Davini, S / Dawson, J / De, K / De, S / Debbins, P / De Bonis, I / Decowski, M P / De Gouvêa, A / De Holanda, P C / De Icaza Astiz, I L / Deisting, A / De Jong, P / Delbart, A / Delepine, D / Delgado, M / Dell'Acqua, A / Delmonte, N / De Lurgio, P / de Mello Neto, J R T / DeMuth, D M / Dennis, S / Densham, C / Deptuch, G W / De Roeck, A / De Romeri, V / De Souza, G / Devi, R / Dharmapalan, R / Dias, M / Diaz, F / Díaz, J S / Domizio, S Di / Giulio, L Di / Ding, P / Noto, L Di / Dirkx, G / Distefano, C / Diurba, R / Diwan, M / Djurcic, Z / Doering, D / Dolan, S / Dolek, F / Dolinski, M / Domine, L / Donon, Y / Douglas, D / Douillet, D / Dragone, A / Drake, G / Drielsma, F / Duarte, L / Duchesneau, D / Duffy, K / Dunne, P / Dutta, B / Duyang, H / Dvornikov, O / Dwyer, D / Dyshkant, A / Eads, M / Earle, A / Edmunds, D / Eisch, J / Emberger, L / Emery, S / 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/ Pennacchio, E / Penzo, A / Peres, O L G / Perry, J / Pershey, D / Pessina, G / Petrillo, G / Petta, C / Petti, R / Pia, V / Piastra, F / Pickering, L / Pietropaolo, F / Pimentel, V L / Pinaroli, G / Plows, K / Plunkett, R / Poling, R / Pompa, F / Pons, X / Poonthottathil, N / Poppi, F / Pordes, S / Porter, J / Potekhin, M / Potenza, R / Potukuchi, B V K S / Pozimski, J / Pozzato, M / Prakash, S / Prakash, T / Prest, M / Prince, S / Psihas, F / Pugnere, D / Qian, X / Raaf, J L / Radeka, V / Rademacker, J / Radics, B / Rafique, A / Raguzin, E / Rai, M / Rajaoalisoa, M / Rakhno, I / Rakotonandrasana, A / Rakotondravohitra, L / Rameika, R / Delgado, M A Ramirez / Ramson, B / Rappoldi, A / Raselli, G / Ratoff, P / Raut, S / Razakamiandra, R F / Rea, E M / Real, J S / Rebel, B / Rechenmacher, R / Reggiani-Guzzo, M / Reichenbacher, J / Reitzner, S D / Sfar, H Rejeb / Renshaw, A / Rescia, S / Resnati, F / Ribas, M / Riboldi, S / Riccio, C / Riccobene, G / Rice, L C J / Ricol, J S / 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Zennamo, J / Zeug, K / Zhang, C / Zhang, S / Zhang, Y / Zhao, M / Zhivun, E / Zhu, G / Zimmerman, E D / Zucchelli, S / Zuklin, J / Zutshi, V / Zwaska, R

The European physical journal. C, Particles and fields

2022 Volume 82, Issue 7, Page(s) 618

Abstract: DUNE is a dual-site experiment for long-baseline neutrino oscillation studies, neutrino astrophysics and nucleon decay searches. ProtoDUNE Dual Phase (DP) is a ... ...

Abstract	DUNE is a dual-site experiment for long-baseline neutrino oscillation studies, neutrino astrophysics and nucleon decay searches. ProtoDUNE Dual Phase (DP) is a 6
Language	English
Publishing date	2022-07-16
Publishing country	France
Document type	Journal Article
ZDB-ID	1459069-4
ISSN	1434-6052 ; 1434-6044
ISSN (online)	1434-6052
ISSN	1434-6044
DOI	10.1140/epjc/s10052-022-10549-w
Database	MEDical Literature Analysis and Retrieval System OnLINE

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