The aim of the present research is to validate the combined use, through data fusion, of a Laser Induced Fluorescence (LIF) scanning system and a radar scanner (RGB-ITR, Red Green Blue Imaging Topological Radar system), as a unique tool to address the need for non-invasive, rapid, and low-cost techniques for both diagnostic and operational needs. The integrated system has been applied to the House of Diana complex in Ostia Antica. The main diagnostic objective of this research was to trace the materials used in different phases of restoration, from antiquity to modernity, on both masonry and pictorial surfaces, to reconstruct the history of the building. Due to the significant interest in this insula, other studies have been recently carried out on the House of Diana, but they once again highlighted the necessity of multiple approaches and non-invasive methods capable of providing quasi-real-time answers, delivering point-by-point information on very large surfaces to overcome the limits related to representativeness of sampling. The data acquired by the RGB-ITR system are quantitative, allowing for morphological and 3-colour analysis of the investigated artwork. In this work, the sensor has been used to create coloured 3D models useful for structural assessments and for locating different classes of materials. In fact, the LIF maps, which integrate knowledge about the original constituent materials and previous conservation interventions, have been used as additional layers of the tridimensional models. Therefore, the method can direct possible new investigations and restoration actions, piecing together the history of the House of Diana to build for it a safer future.

The multispectral study and the digitalisation of large-scaled artworks is often a critical procedure due to the movement of the instrumentation, which need scaffolds, long timing and long data acquisition time, especially when artworks are also placed at large heights, such as painting hung on walls. This is the case of a series of paintings located at the Chigi Palace in Ariccia (Rome, Italy), studied with two prototypal laser scanner systems developed by ENEA. By the use of laser sources in the visible/infrared ranges and the double-amplitude modulation technique, the scanners detect the reflected signals from the investigated object working remotely for the colour-accurate digitalisation and the detection of subsurface features. The Red Green Blue-Imaging Topological Radar (RGB-ITR) system was employed on a large canvas depicting angels with symbols of the Passion of Christ for the remote 3D digitalisation in the visible range, while the Infrared Imaging Topological Radar (IR-ITR) system was endorsed on two paintings belonging to the Four Seasons series for the infrared analysis aimed at the identification of hidden elements and the recovery of features not clearly visible. The obtained results provided precious information on the conservative state and the artistic techniques of large-scale artworks, not studied before by advanced technologies.

Inferring a process matrix characterizing a quantum channel from experimental measurements is a key issue of quantum information. Noise affecting the measured counts could bring to matrices different from the expected ones and optimization methods usually employed, i.e. the maximum likelihood estimation (MLE), are characterized by several drawbacks. Lowering the noise could be necessary to increase the experimental resources, e.g. time for each measurement. In this paper, an alternative procedure, based on suitable Neural Networks, has been implemented and optimized to obtain a denoised process matrix and this approach has been tested with a specific quantum channel, i.e. a Control Phase. This promising method relies on the analogy that can be established between the elements of a process matrix and the pixels of an image.

The purpose of this paper is to identify an efficient, sustainable, and “green” approach to address the challenges of the preservation of hypogeum heritage, focusing on the problem of moisture, a recurring cause of degradation in porous materials, especially in catacombs. Conventional and novel technologies have been used to address this issue with a completely non-destructive approach. The article provides a multidisciplinary investigation making use of advanced technologies and analysis to quantify the extent and distribution of water infiltration in masonry before damage starts to be visible or irreversibly causes damage. Four different technologies, namely Portable Nuclear Magnetic Resonance (NMR), Audio Frequency–Acoustic Imaging (AF–AI), Laser-Induced Fluorescence (LIF), Infrared Thermography (IRT), and 3D Laser Scanning (RGB-ITR), were applied in the Priscilla catacombs in Rome (Italy). These imaging techniques allow the characterisation of the deterioration of painted surfaces within the delicate environment of the Greek chapel in the Priscilla catacombs. The resulting high-detailed 3D coloured model allowed for easily referencing the data collected by the other techniques aimed also at the study of the potential presence of salt efflorescence and/or microorganisms. The results supply an efficient and sustainable tool aimed at cultural heritage conservation but also at the creation of digital documentation obtained with green methodologies for a wider sharing, ensuring its preservation for future generations.

Characterization of quantum objects, being them states, processes, or measurements, complemented by previous knowledge about them 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, especially for estimating specific physical parameters. Here we show that a neural network (NN) can improve the tomographic estimate of parameters by including a convolutional stage. We applied our technique to quantum process tomography for the characterization of several quantum channels. We demonstrate that a stable and reliable operation 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 operating on classical data produced by quantum systems.

In the contemporary world, human and natural calamities are challenging our capabilities to preserve heritage and develop innovative safeguard strategies that also address the requirement of sustainability for restoration purposes, still considering the connection between tradition and innovation. This work introduces non-invasive diagnostic practices that offer a new insight of the built environment by studying two different elements of the same architecture of San Bevignate Templar church: a thermographic mapping obtained with special post-processing procedures provided interesting information about the hidden wall pattern, while a prototypal laser scanner, called RGB-ITR, and a UAV survey supplied new insights on the precious paintings. The assessment of the masonry quality constitutes an a priori condition for a reliable estimation of its seismic vulnerability and for the planning of effective yet conservative interventions. The access keys to 'sustainability' therefore consist in the improvement of these contactless investigations, which can be performed both in passive conditions, in the case of thermography surveys, and in active ones, such as for the RGB-ITR scanner, as necessary substitutes for destructive or partial-destructive tests. The research achieved promising results for the characterisation of the architectural structure and the paintings, with the aim of a long-term monitoring of the structure and the decorative apparatus of a monumental heritage located in an area vulnerable to seismic and environmental events.

This paper presents the preliminary results of an ongoing multidisciplinary study carried out in the Etr-uscan tomb called Querciola with a twofold aim: on one hand, the comprehension of the storytelling of its unique paintings, on the other, the collection and analyses of documentation for monitoring the state of preservation of the tomb and the paintings over the years. The investigations were carried out by studying historical and archival sources, ancient hand drawings and acquiring 3D-coloured models obtained by using a high-definition 3D laser scanner prototype. The ancient drawings were made with different techniques (pencil, tempera , watercolours) by several artists from 1831 to 1935 as a means of documentation, also by drawing on paper on a scale of 1:1. However, the reliability of graphic and colour transpositions is not entirely certain, raising art-historical doubts about the original appearance of the paintings and the presence of personal contributions of individual artists in each drawing. For this rea-son, the 3D model acquired by the laser scanner constitutes a very useful tool for scientific and reliable documentation, which can be also considered as a starting point for long-term monitoring. The acquired 3D models provided the accurate digitalisation of the entire tomb, collecting both colorimetric and struc-tural information, without the influence of the environmental illuminating conditions, for conservative, scientific and educational purposes. The post-processing of the images permitted the analysis of the state of health of the site and of its paintings, as well as improving the readability of some elements of the pictorial cycle of the tomb that are now barely visible. The preliminary results of this study demonstrated the importance of using multidisciplinary resources and the cooperation between scholars coming from different fields, for the comprehension and the recovery of partially lost paintings, improving the possi-bility to better understand iconography of the Etruscan art. (c) 2023 Consiglio Nazionale delle Ricerche (CNR). Published by Elsevier Masson SAS. All rights reserved.

Preventing terrorist attacks at soft targets has become a priority for our society. The realization of sensor systems for automatic threat detection in crowded spaces, such as airports and metro stations, is challenged by the limited sensing coverage capability of the devices in place due to the variety of dangerous materials, to the scanning rate of the devices, and to the detection area covered. In this context, effectiveness of the physical configuration of the system based on the detectors used, the coordination of the sensor data collection, and the real time data analysis for threat identification and localization to enable timely reactions by the security guards are essential requirements for such integrated sensor-based applications. This paper describes a modular distributed architecture of a command-and-control software, which is independent from the specific detectors and where sensor data fusion is supported by two intelligent video systems. Furthermore, the system installation can be replicated at different locations of a public space. Person tracking and later re-identification in a separate area, and tracking hand-over between different video components, provide the command-and-control with localization information of threats to timely activate alarm management and support the activity of subsequent detectors. The architecture has been implemented for the NATO-funded DEXTER program and has been successfully tested in a big city trial at a metro station in Rome both when integrated with two real detectors of weapons and explosives and as a stand-alone system. The discussion focuses on the software functions of the command-and-control and on the flexibility and re-use of the system in wider settings.

Counter terrorism is a huge challenge for public spaces. Therefore, it is essential to support early detection of threats, such as weapons or explosives. An integrated fusion engine was developed for the management of a plurality of sensors to detect threats without disrupting the flow of commuters. The system improves security of soft targets (such as airports, undergrounds and railway stations) by providing security operators with real-time information of the threat combined with image and position data of each person passing the monitored area. This paper describes the results of the fusion engine in a public-space trial in a metro station in Rome. The system consists of 2D-video tracking, person re-identification, 3D-video tracking, and command and control (C&C) formulating two co-existing data pipelines: one for visualization on smart glasses and another for hand-over to another sensor. Over multiple days, 586 commuters participated in the trial. The results of the trial show overall accuracy scores of 97.4% and 97.6% for the visualization and hand-over pipelines, respectively, and each component reached high accuracy values (2D Video = 98.0%, Re-identification = 100.0%, 3D Video = 99.7% and C&C = 99.5%).

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 three-dimensional 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.

The contemporary geopolitical environment and strategic uncertainty shaped by asymmetric and hybrid threats urge the future development of hands-on training in realistic environments. Training in immersive, virtual environments is a promising approach. Immersive training can support training for contexts that are otherwise hard to access, dangerous, or have high costs. This paper discusses the challenges for virtual reality training in the CBRN (chemical, biological, radioactive, nuclear) domain. Based on initial considerations and a literature review, we conducted a survey and three workshops to gather requirements for CBRN training in virtual environments. We structured the gathered insights into four overarching themes-the future of CBRN training, ethical and safety requirements, evaluation and feedback, and tangible objects and tools. We provide insights on these four themes and discuss recommendations.

This paper presents the results of a multidisciplinary study carried out for the characterisation of the colours of a famous Etruscan site: the Blue Daemons tomb. Here, 3D digitalisation and analytical investigations were necessary for conservative and educational purposes, in order to characterize the materials of the Etruscan art, preserve the memory of the archaeological remain and be able to transmit it to future generations. The 3D model of the tomb has been achieved with the multi-wavelengths laser scanner prototype developed by ENEA, allowing a truthful colour and structural digitalisation of the tomb without the influence of the bad illuminating conditions. Such a technique introduced a doubt about the validity of the tomb name: the daemons are really blue? Colorimetric measurements achieved with both the laser scanner prototype and a portable spectrophotometer have revealed greyish hue of the demoniac figures, requiring further and focused analyses on the colour palette of the painting in order to understand their composition and the state of conservation. For these purposes, Raman, XRF and LIF spectroscopies have been performed on the wall where the blue demons are represented. The results have detected the use of the pigment Egyptian blue for the daemons' skin and ochres for yellow and red details, confirming the legitimacy of the tomb name, although the presence of synthetic consolidants applied in previous restorations have altered colorimetric measurements. (C) 2020 Elsevier Masson SAS. All rights reserved.

Cultural Heritage objects located in turbulent areas with a significant risk of terrorist attacks or inside a war zone are at risk of suffering damages similar to those in scenarios of severe seismic events, which are associated with partial or total building collapse and the subsequent need for monitoring, consolidation and successive reconstruction. To this end the availability of digital data collected by optical and spectroscopic laser scanners before the catastrophic event and stored as digital high resolution 2D and 3D maps can be a unique valuable support for future reconstruction. Conversely, continuous fiber glass monitoring may ensure reference data to evaluate the event impact and aid in planning consolidation. Examples of successful application of high-performance ENEA laser scanner prototypes in central Italy on monuments exposed to severe seismic risk are reported so as to illustrate the importance of storing quality 3D optical data before the event. The importance of fiber sensor monitoring during and after a seismic event in the same area is also shown from the collected data. Different examples of 3D reconstructions based on optical and spectroscopic data obtained within regional projects dealing with archaeological fragments (Roman frescoes and relief sculpture) are discussed, as regards their use in reconstructing from fragments in the aftermath of a catastrophic event.

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.

In 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.

Cultural heritage protection and safeguarding is a clear problem for the worldwide community because the legacy and identity of communities has to be kept alive and transmitted to future generations. To this end optical technologies have an important role to play in defining state-of-the-art conservation, guiding restauration, and exploring new opportunities in virtual and augmented realities where other complementary information can be merged. ENEA has developed different laser-based sensors for remote and local diagnostics that have already been deployed in field campaigns implementing different spectroscopic techniques that supply prompt information in real time and are non-destructive and non-invasive as regards the artifact being studied. Here the technical characteristics and performances of the tools are briefly described, and examples provided of monitoring applications of paintings, statues, woods, metals and structural observations (tensions and vibrations).

Artistic surfaces at the Bishop’s Palace of Frascati have been investigated by an integrated approach involving different non-invasive diagnostic techniques. A LIF (Laser Induced Fluorescence) scanning system worked in synergy with the RGB-ITR ((Red Green and Blue – Imaging Topological Radar) 3D laser scanner and the SfM (Structure from Motion) technique for the 3D photogrammetric reconstruction. The presented case study shows how 3D multispectral information can reveal and locate previous restoration actions and deterioration processes as support for conservation, research and dissemination purposes.

In the last years the application of Artificial Intelligence algorithms has grown drastically in different sectors and aspects of our lives. One of the major successful sectors is the treatment of images, not only in terms of classification, but also in terms of processing and data improvements: one of the most diffuse examples are the mobile camera software, which uses neural-networks-based algorithms for obtaining high quality pictures from lenses with a reduced resolving power, if compared with professional optical ones. The present work aims to use unsupervised Convolutional Neural Networks for underwater images processing, so to try to obtain air-quality images and reduce all the effects caused by the interaction between light and water particles. Nowadays several works are presented for the correction of low contrast and blurriness effects, but most of them generate synthetic images obtained by applying complementary algorithms used for water effects correction. The present work aims to create a real dataset composed by air/water images by the use of an ad-hoc experimental setup for training an unsupervised Generative Adversarial Network (GAN). Because of their nature to be generative models of data, GANs can learn to estimate the underlying probability distribution of the data and the unsupervised GAN can make it without a one-to-one mapping.