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7. BB84 decoy-state QKD protocol over long-distance optical fiber

Author

Guarda, Giulia, primary, Ribezzo, Domenico, additional, Salvoni, Daniela, additional, Bruscino, Ciro, additional, Ercolano, Pasquale, additional, Ejrnaes, Mikkel, additional, Parlato, Loredana, additional, Zhang, C., additional, Li, H., additional, You, L., additional, Vagniluca, Ilaria, additional, De Lazzari, Claudia, additional, Occhipinti, Tommaso, additional, Pepe, Giovanni Piero, additional, Zavatta, Alessandro, additional, and Bacco, Davide, additional

Published
2023
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12. Updates On PRISMA: Scientific Calibration/Validation Activities and Supporting Studies

Author

Lorenzo Genesio, Federica Braga, Mariano Bresciani, Mirco Boschetti, Federico Carotenuto, Sergio Cogliati, Simone Colella, Roberto Colombo, Claudia Giardino, Beniamino Gioli, Ettore Lopinto, Daniela Meloni, Monica Pepe, Simone Pascucci, Stefano Pignatti, Loredana Pompilio, Patrizia Sacco, Giuseppe Satalino, Franco Miglietta, Genesio, L, Braga, F, Bresciani, M, Boschetti, M, Carotenuto, F, Cogliati, S, Colella, S, Colombo, R, Giardino, C, Gioli, B, Lopinto, E, Meloni, D, Pepe, M, Pascucci, S, Pignatti, S, Pompilio, L, Sacco, P, Satalino, G, and Miglietta, F

Subjects
field measurement, spaceborne imaging spectrometry, natural surface, airborne data
Abstract

PRISMA (PRecursore IperSpettrale della Missione Applicativa) is a demonstrative spaceborne mission, fully deployed by the Italian Space Agency (ASI). To support the calibration/validation activities of the PRISMA hyperspectral mission, ASI and the National Research Council (CNR) started in 2019 the PRISCAV project (Scientific CAL/VAL of PRISMA mission). The main objective of PRISCAV is the comprehensive characterization of the performances of the PRISMA payload in orbit in different operational scenarios and the verification of the durability in time of the performances. To this end, PRISCAV created a network of 12 instrumented sites showing different land-use and surface settings (Snow; Sea; Inland and Coastal Water; Forest and Cropland) to obtain independent and traceable in-situ and airborne Fiducial Reference Measurements (FRM) simultaneous to PRISMA acquisitions in order to assess the required performance of sensor, data products, and processors at the different levels (i.e. Top-of-Atmosphere Level 1 Radiances and Bottom-of-Atmosphere Level 2 Reflectance standard products). Moreover, on some of these sites, simultaneous PRISMA and airborne AVIRISNG acquisitions were made coupling remote sensing with in-situ observations to support new mission development and in particular the Copernicus Hyperspectral Imaging Mission for the Environment (CHIME). Recent updates on CAL/VAL activities and on AVIRSNG campaigns are presented in this contribution.

Published
2022
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13. Development of an Embedded System-Based Dropper Payload for Drones

Author

Enzo Caputo, Giorgio de Alteriis, Claudia Conte, Martina Nocerino, Paola Pepe, Sonia Elia, Antonio Bosco, Giuseppe Cringoli, Laura Rinaldi, Giancarlo Rufino, Domenico Accardo, Caputo, E., De Alteriis, G., Conte, C., Nocerino, M., Pepe, P., Elia, S., Bosco, A., Cringoli, G., Rinaldi, L., Rufino, G., and Accardo, D.

Subjects
drone embedded system, GPS, UAV, dropper payload, Echinococcosi, canid
Abstract

Echinococcosis hydatidosis is a chronic disabling disease of parasitic origin that constitutes an exemplary case of one-health. According to data from the national epidemiological bulletin, is one of the most important zoonoses in terms of the number of cases, severity, and economic costs in Italy. This paper aims to contribute to the prevention of the spread of this infection by proposing the development of an embedded system on a drone that can release decoys containing canine medicine. To this aim has been chosen a microcontroller, which is responsible for interfacing and controlling the different peripherals required to accomplish the release of decoys from the custom payload. In addition to the hardware part of the embedded system, has been implemented an ad hoc program that is able to coordinate all the elements, satisfying the proposed purpose. In particular, suitable software architecture has been implemented by means of an ARM-Cortex microcontroller not only for the advantages related to size, cost, and power consumption but also to exploit their high-performance and safety requirements.

Published
2022
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26. Updates On PRISMA: Scientific Calibration/Validation Activities and Supporting Studies

Author

Genesio, Lorenzo, primary, Braga, Federica, additional, Bresciani, Mariano, additional, Boschetti, Mirco, additional, Carotenuto, Federico, additional, Cogliati, Sergio, additional, Colella, Simone, additional, Colombo, Roberto, additional, Giardino, Claudia, additional, Gioli, Beniamino, additional, Lopinto, Ettore, additional, Meloni, Daniela, additional, Pepe, Monica, additional, Pascucci, Simone, additional, Pignatti, Stefano, additional, Pompilio, Loredana, additional, Sacco, Patrizia, additional, Satalino, Giuseppe, additional, and Miglietta, Franco, additional

Published
2022
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28. Long-Term Continuously Updated Deformation Time Series From Multisensor InSAR in Xi'an, China From 2007 to 2021

Author

Baohang Wang, Chaoying Zhao, Qin Zhang, Zhong Lu, and Antonio Pepe

Subjects
Ocean engineering, robust sequential least squares (RSLS), QC801-809, Independent component analysis (ICA), Geophysics. Cosmic physics, multisensor synthetic aperture radar interferometry (InSAR), surface deformation update, TC1501-1800
Abstract

According to historical records, land subsidence has been occurring in Xi'an, China, since the 1960s, characterized by complex land subsidence patterns. This subsidence has the potential to cause serious societal and economic problems during the process of urbanization. Long-term, large-scale monitoring and dynamic high precision tracking of the evolution of surface deformation associated with geohazards is a prerequisite for effective prevention or advance warning of geological disasters. Synthetic aperture radar interferometry (InSAR), a satellite remote sensing technology, can facilitate such monitoring. Both currently operating and planned SAR satellites would provide extensive amounts of SAR data. In this article, we describe an approach for continuously updating long-term multisensor InSAR deformation time series using robust sequential least squares. It is successfully applied to near-real-time monitoring of the long-term evolution of surface deformation in Xi'an, China, from January 3, 2007 to February 12, 2021, using four SAR satellites: ALOS/PALSAR-1, TerraSAR-X, ALOS/PALSAR-2, and Sentinel-1A. In order to analyze deformation evolution, temporal independent component analysis was used to interpret deformation patterns. We found that land subsidence in Xi'an has slowed and even halted in some areas. However, large areas are uplifting, which presents a potential for geohazards. We conclude that the proposed approach using continuously updated deformation time series from multisensor InSAR can provide near-real-time deformation measurements, which are necessary for an early warning system.

Published
2021

34. Development of an Embedded System-Based Dropper Payload for Drones

Author

Caputo, Enzo, primary, de Alteriis, Giorgio, additional, Conte, Claudia, additional, Nocerino, Martina, additional, Pepe, Paola, additional, Elia, Sonia, additional, Bosco, Antonio, additional, Cringoli, Giuseppe, additional, Rinaldi, Laura, additional, Rufino, Giancarlo, additional, and Accardo, Domenico, additional

Published
2022
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37. Superconducting Microbridges for large area single photon detectors

Author

Salvoni, Daniela, primary, Parlato, Loredana, additional, Federico, Chianese, additional, Ejrnaes, Mikkel, additional, Bruscino, Ciro, additional, Ercolano, Pasquale, additional, Satariano, Roberta, additional, Cirillo, Carla, additional, Cassinese, Antonio, additional, Carmine, Attanasio, additional, and Pepe, Giovanni Piero, additional

Published
2022
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43. Investigation of the Superconducting Ti/PdAu Bilayer Films for Transition Edge Sensors

Author

Xiaolong Xu, Mauro Rajteri, Jinjin Li, Shuo Zhang, Eugenio Monticone, Jian Chen, Carlo Pepe, Huifang Gao, Wei Li, Xu Li, Qi Li, Ying Gao, Zheng Liu, and Xueshen Wang

Subjects
Proximity effect, superconductivity, Ti/PdAu, transition-edge sensor, Electrical and Electronic Engineering, Condensed Matter Physics, Electronic, Optical and Magnetic Materials
Published
2022

45. Lidar measurement of clouds profile with a Superconducting Nanowire Single Photon Detector

Author

Alessia Sannino, Salvatore Amoruso, Mikkel Ejrnaes, Xuan Wang, R. Cristiano, Lixing You, Giovanni Piero Pepe, Chengjun Zhang, Loredana Parlato, Daniela Salvoni, Antonella Boselli, Salvoni, D., Sannino, A., Parlato, L., Amoruso, S., Pepe, G. P., Boselli, A., Ejrnaes, M., Wang, X., Cristiano, R., Zhang, C., and You, L.

Subjects
Lidar, Materials science, aerosol, business.industry, Infrared, superconductivity, Detector, SNSPD, Measure (physics), Superconducting nanowire single-photon detector, clouds, Temperature measurement, Aerosol, infrared detectors, infrared detector, Wavelength, Optics, atmosphere, cloud, business, aerosols, Physics::Atmospheric and Oceanic Physics
Abstract

In this work the results of two Lidar measurements in the infrared range with a Superconducting Nanowire Single Photon Detector (SNSPD) are presented. In the first measurement, performed at the wavelength of 1550 nm, we determined the distance of two hard targets. This result was used to calibrate the experimental setup and to test the readout electronics. Then, we combined the SNSPD with the Lidar setup MALIA (Multiwavelength Lidar Apparatus) to measure the atmospheric aerosol profile at 1064 nm during a cloudy day. For the last measurement the backscattering coefficient was also calculated.

Published
2021
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50. Deep Learning-Based 3D Segmentation of True Lumen, False Lumen, and False Lumen Thrombosis in Type-B Aortic Dissection

Author

Liana D. Wobben, Marina Codari, Gabriel Mistelbauer, Antonio Pepe, Kai Higashigaito, Lewis D. Hahn, Domenico Mastrodicasa, Valery L. Turner, Virginia Hinostroza, Kathrin Baumler, Michael P. Fischbein, Dominik Fleischmann, and Martin J. Willemink

Subjects
Aortic Dissection, Deep Learning, Aortic Aneurysm, Thoracic, Humans, Thrombosis, Article, Retrospective Studies
Abstract

Patients with initially uncomplicated type-B aortic dissection (uTBAD) remain at high risk for developing late complications. Identification of morphologic features for improving risk stratification of these patients requires automated segmentation of computed tomography angiography (CTA) images. We developed three segmentation models utilizing a 3D residual U-Net for segmentation of the true lumen (TL), false lumen (FL), and false lumen thrombosis (FLT). Model 1 segments all labels at once, whereas model 2 segments them sequentially. Best results for TL and FL segmentation were achieved by model 2, with median (interquartiles) Dice similarity coefficients (DSC) of 0.85 (0.77–0.88) and 0.84 (0.82–0.87), respectively. For FLT segmentation, model 1 was superior to model 2, with median (interquartiles) DSCs of 0.63 (0.40–0.78). To purely test the performance of the network to segment FLT, a third model segmented FLT starting from the manually segmented FL, resulting in median (interquartiles) DSCs of 0.99 (0.98–0.99) and 0.85 (0.73–0.94) for patent FL and FLT, respectively. While the ambiguous appearance of FLT on imaging remains a significant limitation for accurate segmentation, our pipeline has the potential to help in segmentation of aortic lumina and thrombosis in uTBAD patients. CLINICAL RELEVANCE—: Most predictors of aortic dissection (AD) degeneration are identified through anatomical modeling, which is currently prohibitive in clinical settings due to the time-intense human interaction. False lumen thrombosis, which often develops in patients with type B AD, has proven to show significant prognostic value for predicting late adverse events. Our automated segmentation algorithm offers the potential of personalized treatment for AD patients, leading to an increase in long-term survival.

Published
2021
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