Simplified Quantum Process Characterization by Specialised Neural Networks

Characterization of quantum objects based on previous knowledge is a valuable approach, especially as it leads to routine procedures for real-life components. To this end, Machine Learning algorithms have demonstrated to successfully operate in presence of noise. However, there might be instances in which unknown parasitic effects occur in tandem with the sought one we aim at characterizing. Here we show that the accurate design of a two-stage neural network can account for these class of disturbances as well, applying our technique to the characterization of several quantum channels. We demonstrate that a stable and reliable characterization is achievable by training the network only with simulated data. The obtained results show the viability of this approach as an effective tool based on a completely new paradigm for the employment of NNs in the quantum domain

Remote Colorimetric and Structural Diagnosis by RGB-ITR Color Laser Scanner Prototype

Since several years ENEA's Artificial Vision laboratory is involved in electrooptics systems development. In the last period the efforts are concentrated on cultural heritage remote diagnosis, trying to develop instruments suitable for multiple purposes concerning restoration, cataloguing, and education. Since last five years a new 3D (three-dimensional) laser scanner prototype (RGB-ITR) based on three amplitude-modulated monochromatic laser sources mixed together by dichroic filters is under development. Five pieces of information per each sampled point (pixel) are collected by three avalanche photodiodes and dedicated electronics: two distances and three target reflectivity signals for each channel, red, green, and blue. The combination of these pieces of information opens new scenarios for remote colorimetry allowing diagnoses without the use of scaffolds. Results concerning the use of RGB-ITR as colorimeter are presented

Radiation Tolerant 3D Laser Scanner for Structural Inspections in Nuclear Reactor Vessels and Fuel Storage Pools

Accurate and timely assessment of displacements and/or structural damages in nuclear reactor vessels' components is a key action in routine inspections for planning maintenance and repairs but also in emergency situations for mitigating consequences of nuclear incidents. Nevertheless, all these components are maintained underwater and reside in high-radiation fields thus imposing harsh operative conditions to inspection devices which must cope with effects such as Cerenkov radiation background, Total Ionizing Radiation (TID), and occlusions in the detectors' field of view. To date, ultrasonic techniques and video cameras are in use for inspection of components' integrity and with measurements of volumetric and surface crack opening displacements, respectively. The present work reports the realization of a radiation tolerant laser scanner and the results of tests in a nuclear research reactor vessel for acquisition of 3D models of critical components. The device, qualified for underwater operation and for withstanding up to 1 MGy of TID, is based on a 515 nm laser diode and a fast-scanning electro-optic unit. To evaluate performances in a significant but controlled environment, the device has been deployed in the vessel of a research reactor operated by ENEA in the Casaccia Research Centre in Rome (Italy). A 3D model of the fuel rods assembly through a cooling water column of 7 m has been acquired. The system includes proprietary postprocessing software that automatically recognizes components of interest and provides dimensional analysis. Possible application fields of the system stretch to dimensional analysis also in spent nuclear fuel storage pools

Remote and contactless infrared imaging techniques for stratigraphical investigations in paintings on canvas

AbstractIn the analysis of complex stratigraphical structures like painted artefact, infrared (IR) techniques can provide precious information about elements hidden under superficial layers of the artwork, such as pictorial features and structural defects. This paper presents a novel complementary use of reflectographic and thermographic techniques for the survey of three baroque paintings, preserved at the Chigi Palace in Ariccia (Italy). First, the IR-ITR laser scanner prototype has been used for the preliminary and remote near-IR reflectographic survey of the areas where the canvas was located. The resulting map was then used for planning the thermographic and mid-IR reflectographic studies, focusing the analyses on the most interesting areas of one of the paintings, called "La Primavera". The combination of the three imaging techniques revealed several details not visible by the naked eye, such as restored lacunas and pentimenti, demonstrating the validity and complementarity of the proposed combined methodologies

Psoriasis and psoriasiform reactions secondary to immune checkpoint inhibitors

The advent of Immune Checkpoint Inhibitors (ICIs) as a standard of care for several cancers, including melanoma and head/neck squamous cell carcinoma has changed the therapeutic approach to these conditions, drawing at the same time the attention on some safety issues related to their use. To assess the incidence of psoriasis as a specific immune-related cutaneous adverse event attributing to ICIs using the Eudravigilance reporting system. All reports of adverse drug reactions (ADRs) concerning either exacerbation of psoriasis or de novo onset of psoriasis/psoriasiform reactions associated to the use of Cytotoxic T-Lymphocyte Antigen-4 (CTLA-4) inhibitors ipilimumab and tremelimumab, and the Programmed cell Death protein 1/Programmed Death-Ligand 1 (PD-1/PD-L1) inhibitors nivolumab, pembrolizumab, atezolizumab, durvalumab, avelumab, and cemiplimab were identified and extracted from the Eudravigilance reporting system, during the period between the date of market licensing (for each study drug) and 30 October 2020. 8213 reports of cutaneous ADRs associated with at least one of study drug have been recorded, of which 315 (3.8%) reporting psoriasis and/or psoriasiform reactions as ADR. In 70.8% of reports patients had pre-existing disease. ICIs-related skin toxicity is a well-established phenomenon, presenting with several conditions, sustained by an immune background based on the activity of some cells (CD4+/CD8+ T-cells, neutrophils, eosinophils, and plasmocytes), inflammatory mediators, chemokines, and tumor-specific antibodies. In this setting, psoriasis represents probably the most paradigmatic model of these reactions, thus requiring adequate recognition as no guidelines on management are now available

A Quadratic Model with Nonpolynomial Terms for Remote Colorimetric Calibration of 3D Laser Scanner Data Based on Piecewise Cubic Hermite Polynomials

The processing of intensity data from terrestrial laser scanners has attracted considerable attention in recent years. Accurate calibrated intensity could give added value for laser scanning campaigns, for example, in producing faithful 3D colour models of real targets and classifying easier and more reliable automatic tools. In cultural heritage area, the purely geometric information provided by the vast majority of currently available scanners is not enough for most applications, where indeed accurate colorimetric data is needed. This paper presents a remote calibration method for self-registered RGB colour data provided by a 3D tristimulus laser scanner prototype. Such distinguishing colour information opens new scenarios and problems for remote colorimetry. Using piecewise cubic Hermite polynomials, a quadratic model with nonpolynomial terms for reducing inaccuracies occurring in remote colour measurement is implemented. Colorimetric data recorded by the prototype on certified diffusive targets is processed for generating a remote Lambertian model used for assessing the accuracy of the proposed algorithm. Results concerning laser scanner digitizations of artworks are reported to confirm the effectiveness of the method

3D models acquisition and image processing for virtual musealization of the spezieria di Santa Maria della Scala, Rome

This study was carried out within the project 'Roma Hispana. Nuevas tecnologías aplicadas al estudio histórico, la musealización y la puesta en valor de Patrimonio Cultural español en Roma: la spezieria di Santa Maria della Scala' (Universitat de València Spain), which is funded by the Conselleria d'Innovació, Universitats, Ciència i Societat Digital of the Generalitat Valenciana (2020-2021) and authorized by the Sovrintendenza Speciale Archeologia Belle Arti e Paesaggio (Special Superintendence of Archeology, Fine Arts and Landscape) of Rome, Italy. The spezieria di Santa Maria della Scala was the oldest apothecary in Europe managed by the order of Discalced Carmelite friars. Operating between the second half of the seventeenth century and the mid-twentieth century, over time it acquired great prestige, becoming known as the Pharmacy of the Popes. The aims of the 'Roma Hispana' project are to study, musealize and disseminate the material and immaterial cultural heritage of this historical spezieria by combining physicochemical and cultural studies, new 3D technologies, and artificial intelligence. As a case study, in this paper we report the application of a laser scanner prototype for 3D color imaging of the spezieria's sales room and use a simpler photogrammetry method to collect analogous data in the small nearby storeroom coupled to the high-power capabilities of the ENEA parallel computer facility. Digital data were collected to enable a virtual tour that provides a fully navigable, faithful, high-resolution 3D color model to render this ancient Roman apothecary accessible and usable to interested members of the public and experts in the sector (art historians, restorers, etc.). We also describe the 3D technology used to obtain threedimensional images of the cultural assets of these spaces (mostly drug containers) and its results. The ultimate aim of this study is to achieve the virtual musealization of the heritage complex

A Neural-Network-Based Model for the Dynamic Simulation of the Tire/Suspension System While Traversing Road Irregularities

This paper deals with the simulation of the tire/suspension dynamics by using recurrent neural networks (RNNs). RNNs are derived from the multilayer feedforward neural networks, by adding feedback connections between output and input layers. The optimal network architecture derives from a parametric analysis based on the optimal tradeoff between network accuracy and size. The neural network can be trained with experimental data obtained in the laboratory from simulated road profiles (cleats). The results obtained from the neural network demonstrate good agreement with the experimental results over a wide range of operation conditions. The NN model can be effectively applied as a part of vehicle system model to accurately predict elastic bushings and tire dynamics behavior. Although the neural network model, as a black-box model, does not provide a good insight of the physical behavior of the tire/suspension system, it is a useful tool for assessing vehicle ride and noise, vibration, harshness (NVH) performance due to its good computational efficiency and accuracy

Efficient multi-level design optimization using analytical targetcascading and sequential quadratic programming

Decomposition-based optimization techniques are attractive for designing complex systems in industrial practice, such as design of structural, aerospace or automotive systems. Decomposition is attractive when a possibly intractable problem can be converted to a set of smaller, simpler problems; it also helps to understand better relationships and tradeoffs among subsystems which determine the overall behavior of the system to be optimized. A practical drawback is the increased computational cost for coordinating subproblem solutions and linking variable values to achieve overall system consistency and optimality. In this article, we exploit the problem partitioning structure to improve coordination efficiency when using analytical target cascading to solve multilevel problems. A simple modification in the coordination process allows for reduced function evaluations, as demonstrated in a structural and an automotive suspension example