Towards Automatic Digitalization of Railway Engineering Schematics

Relay-based Railways Interlocking Systems (RRIS) carry out critical functions to control stations. Despite being based on old and hard-to-maintain electro-mechanical technology, RRIS are still pervasive. A powerful CAD modeling and analysis approach based on symbolic logic has been recently proposed to support the re-engineering of relay diagrams into more maintainable computer-based technologies. However, the legacy engineering drawings that need to be digitized consist of large, hand-drawn diagrams dating back several decades. Manually transforming such diagrams into the format of the CAD tool is labor-intensive and error-prone, effectively a bottleneck in the reverse-engineering process. In this paper, we tackle the problem of automatic digitalization of RRIS schematics into the corresponding CAD format with an integrative Artificial Intelligence approach. Deep learning-based methods, segment detection, and clustering techniques for the automated digitalization of engineering schematics are used to detect and classify the single elements of the diagram. These elementary elements can then be aggregated into more complex objects leveraging the domain ontology. First results of the method’s capability of automatically reconstructing the engineering schematics are presented

A multi-variate predictability framework to assess invasive cardiac activity and interactions during atrial fibrillation

Objective: This study introduces a predictability framework based on the concept of Granger causality (GC), in order to analyze the activity and interactions between different intracardiac sites during atrial fibrillation (AF). Methods: GC-based interactions were studied using a three-electrode analysis scheme with multi-variate autoregressive models of the involved preprocessed intracardiac signals. The method was evaluated in different scenarios covering simulations of complex atrial activity as well as endocardial signals acquired from patients. Results: The results illustrate the ability of the method to determine atrial rhythm complexity and to track and map propagation during AF. Conclusion: The proposed framework provides information on the underlying activation and regularity, does not require activation detection or postprocessing algorithms and is applicable for the analysis of any multielectrode catheter. Significance: The proposed framework can potentially help to guide catheter ablation interventions of AF

Isotopic characterization of groundwater for drinking use in multilayer aquifers of the Milano and Monza provinces

Groundwater, drinking water, isotopes, EU directives, hydrogeolog

Gamma-Ray Burst observations by the high-energy charged particle detector on board the CSES-01 satellite between 2019 and 2021

In this paper we report the detection of five strong Gamma-Ray Bursts (GRBs) by the High-Energy Particle Detector (HEPD-01) mounted on board the China Seismo-Electromagnetic Satellite (CSES-01), operational since 2018 on a Sun-synchronous polar orbit at a $\sim$ 507 km altitude and 97$^\circ$ inclination. HEPD-01 was designed to detect high-energy electrons in the energy range 3 - 100 MeV, protons in the range 30 - 300 MeV, and light nuclei in the range 30 - 300 MeV/n. Nonetheless, Monte Carlo simulations have shown HEPD-01 is sensitive to gamma-ray photons in the energy range 300 keV - 50 MeV, even if with a moderate effective area above $\sim$ 5 MeV. A dedicated time correlation analysis between GRBs reported in literature and signals from a set of HEPD-01 trigger configuration masks has confirmed the anticipated detector sensitivity to high-energy photons. A comparison between the simultaneous time profiles of HEPD-01 electron fluxes and photons from GRB190114C, GRB190305A, GRB190928A, GRB200826B and GRB211211A has shown a remarkable similarity, in spite of the different energy ranges. The high-energy response, with peak sensitivity at about 2 MeV, and moderate effective area of the detector in the actual flight configuration explain why these five GRBs, characterised by a fluence above $\sim$ 3 $\times$ 10$^{-5}$ erg cm$^{-2}$ in the energy interval 300 keV - 50 MeV, have been detected.Comment: Accepted for publication in The Astrophysical Journal (ApJ

Laser Induced Breakdown Spectroscopy for Elemental Analysis in Environmental, Cultural Heritage and Space Applications: A Review of Methods and Results

Analytical applications of Laser Induced Breakdown Spectroscopy (LIBS), namely optical emission spectroscopy of laser-induced plasmas, have been constantly growing thanks to its intrinsic conceptual simplicity and versatility. Qualitative and quantitative analysis can be performed by LIBS both by drawing calibration lines and by using calibration-free methods and some of its features, so as fast multi-elemental response, micro-destructiveness, instrumentation portability, have rendered it particularly suitable for analytical applications in the field of environmental science, space exploration and cultural heritage. This review reports and discusses LIBS achievements in these areas and results obtained for soils and aqueous samples, meteorites and terrestrial samples simulating extraterrestrial planets, and cultural heritage samples, including buildings and objects of various kinds

Model-Based Approach for the Semi-Automatic Analysis of Collagen Birefringence in Polarized Light Microscopy

Collagen is a key determinant of physio-pathological processes in different tissues. Polarization light microscopy (PLM) of histological sections is the gold-standard for birefringence-based collagen quantification, but post-session image analysis can be time-consuming and subjective. We propose an efficient semi-automatic computational approach for the quantification of collagen content from the analysis of PLM images of birefringent histological sections. The method is based on a physical model of light-sample interaction and birefringence effect production. It combines the information of bright and dark-field PLM images to segment the luminal region and detect the birefringent signal associated with collagen in the tissue region. User input is limited to the selection of a threshold on an image subset and the supervision of the processing, enabling fast analysis of large datasets. Modeling of the birefringence signal compensates for variability factors related to sample processing and image acquisition, such as section thickness variability and nonuniform illumination and transmittance. As a proof-of-concept, the method was applied to human cardiac tissue PLM images, acquired in 14 cardiac surgery patients with different arrhythmic profiles. The method was able to detect a significantly larger amount and higher heterogeneity of fibrosis in the atrium of patients with as opposed to without atrial fibrillation (p < 0.05). The proposed method can be a valid aid to quicken and reinforce the analysis of large sets of PLM images for the quantification of collagen distribution in different tissues and pathologies