Multisensor Data Fusion for Localization of Pollution Sources in Wastewater Networks

Illegal discharges of pollutants into sewage networks are a growing problem in large European cities. Such events often require restarting wastewater treatment plants, which cost up to a hundred thousand Euros. A system for localization and quantification of pollutants in utility networks could discourage such behavior and indicate a culprit if it happens. We propose an enhanced algorithm for multisensor data fusion for the detection, localization, and quantification of pollutants in wastewater networks. The algorithm processes data from multiple heterogeneous sensors in real-time, producing current estimates of network state and alarms if one or many sensors detect pollutants. Our algorithm models the network as a directed acyclic graph, uses adaptive peak detection, estimates the amount of specific compounds, and tracks the pollutant using a Kalman filter. We performed numerical experiments for several real and artificial sewage networks, and measured the quality of discharge event reconstruction. We report the correctness and performance of our system. We also propose a method to assess the importance of specific sensor locations. The experiments show that the algorithm’s success rate is equal to sensor coverage of the network. Moreover, the median distance between nodes pointed out by the fusion algorithm and nodes where the discharge was introduced equals zero when more than half of the network nodes contain sensors. The system can process around 5000 measurements per second, using 1 MiB of memory per 4600 measurements plus a constant of 97 MiB, and it can process 20 tracks per second, using 1.3 MiB of memory per 100 tracks.

Determining the neutrino mass ordering and oscillation parameters with KM3NeT/ORCA

The next generation of water Cherenkov neutrino telescopes in the Mediterranean Sea are under construction offshore France (KM3NeT/ORCA) and Sicily (KM3NeT/ARCA). The KM3NeT/ORCA detector features an energy detection threshold which allows to collect atmospheric neutrinos to study flavour oscillation. This paper reports the KM3NeT/ORCA sensitivity to this phenomenon. The event reconstruction, selection and classification are described. The sensitivity to determine the neutrino mass ordering was evaluated and found to be 4.4$$\sigma $$ σ if the true ordering is normal and 2.3$$\sigma $$ σ if inverted, after 3 years of data taking. The precision to measure $$\varDelta m^2_{32}$$ Δ m 32 2 and $$\theta _{23}$$ θ 23 were also estimated and found to be $$85 . 10^{-6}~{\mathrm{eV}^{2}}$$ 85 . 10 - 6 eV 2 and $$(^{+1.9}_{-3.1})^{\circ }$$ ( - 3.1 + 1.9 ) ∘ for normal neutrino mass ordering and, $$75 . 10^{-6}~{\mathrm{eV}^{2}}$$ 75 . 10 - 6 eV 2 and $$(^{+2.0}_{-7.0})^{\circ }$$ ( - 7.0 + 2.0 ) ∘ for inverted ordering. Finally, a unitarity test of the leptonic mixing matrix by measuring the rate of tau neutrinos is described. Three years of data taking were found to be sufficient to exclude "Equation missing" event rate variations larger than 20% at $$3\sigma $$ 3 σ level.

Higgs and top physics reconstruction challenges and opportunities at FCC-ee

The Higgs bosons and the top quark decay into rich and diverse final states, containing both light and heavy quarks, gluons, photons as well as W and Z bosons. This article reviews the challenges involved in reconstructing Higgs and top events at the FCC-ee and identifies the areas where novel developments are needed. The precise identification and reconstruction of these final states at the FCC-ee rely on the capability of the detector to provide excellent flavour tagging, jet energy and angular resolution, and global kinematic event reconstruction. Excellent flavour tagging performance requires low-material vertex and tracking detectors, and advanced machine learning techniques as successfully employed in LHC experiments. In addition, the Z pole run will provide abundant samples of heavy flavour partons that can be used for calibration of the tagging algorithms. For the reconstruction of jets, leptons, and missing energy, particle-flow algorithms are crucial to explore the full potential of the highly granular tracking and calorimeter systems, and give access to excellent energy–momentum resolution and precise identification of heavy bosons in their hadronic decays. This enables, among many other key elements, the reconstruction of Higgsstrahlung processes with leptonically and hadronically decaying Z bosons, and an almost background-free identification of top quark pair events. Exploiting the full available kinematic constraints together with exclusive jet clustering algorithms will allow for the optimisation of global event reconstruction with kinematic fitting techniques.

Concept “Immortal Regiment” in the Linguistic Consciousness of Teenagers

The article presents the results of an associative experiment that allow us to describe the structure of the concept "Immortal Regiment" in the linguistic consciousness of senior school pupils, college students and cadets. The research has made it possible to define concept core components (memory, war, pride, victory, veterans) and peripheral ones (unity, heroes, glory, posters, holiday, Motherland, etc.). Most of the components have a positive connotation. There are significant differences in the structure of the concept, identified in the linguistic consciousness of cadets (compared to schoolchildren and students). Associates appear in the concept core; they indicate that a personally significant connection with the events of the Great Patriotic War is preserved. This connection is almost lost among modern teenagers of the other social groups, which is caused by the "symbolic event reconstruction" that changes personal attitude to history in course of time. The periphery of the concept is specific in the view of the cadets; it includes the components that are not marked by the rest of the participants of the experiment. The concept "Immortal Regiment" is stated to have positive associates, which tend to be abstract. It means that to preserve the historical memory, it is necessary to personalize the concept. The fields of application include conceptology, social linguistics, cultural linguistics.

Full Detector Simulation with Unprecedented Background Occupancy at a Muon Collider

In recent years, a Muon collider has attracted a lot of interest in the high-energy physics community, thanks to its ability of achieving clean interaction signatures at multi-TeV collision energies in the most cost-effective way. Estimation of the physics potential of such an experiment must take into account the impact of beam-induced background on the detector performance, which has to be carefully evaluated using full detector simulation. Tracing of all the background particles entering the detector region in a single bunch crossing is out of reach for any realistic computing facility due to the unprecedented number of such particles. To make it feasible a number of optimisations have been applied to the detector simulation workflow. This contribution presents an overview of the main characteristics of the beam-induced background at a Muon collider, the detector technologies considered for the experiment and how they are taken into account to strongly reduce the number of irrelevant computations performed during the detector simulation. Special attention is dedicated to the optimisation of track reconstruction with the conformal tracking algorithm in this high-occupancy environment, which is the most computationally demanding part of event reconstruction.

CAESAR II Tool: Complementary Analyses for Emergency Planning Based on Seismic Risks Impact Evaluations

Italy is a country with high seismic hazard, however since the delay in the seismic classification of the national territory, most of the existing building heritage does not comply with the current technical standards for buildings. The seismic events that have hit different Italian regions in recent years have highlighted the complexity of the challenge for the public bodies both in the emergency management and post-event reconstruction and in the planning of effective risk prevention and mitigation measures to be implemented in ‘peacetime’. These difficulties concern, in particular, the capacity to properly manage the financial and technical resources available and to identify the intervention priorities throughout the entire emergency cycle. For correct management, the priority is to quantify and localize, through simulations, the quantification of probable damages and to evaluate in terms of cost-benefits the possible alternative strategies for mitigation, also taking into account the potential, in terms of cost-effectiveness, of integrated measures for seismic and energy retrofitting. In this framework, the project CAESAR II (Complementary Analyses for Emergency planning based on Seismic Risks impact evaluations) has been developed as a Decision Support System for Public Authorities in charge of developing Disaster Risk Reduction plans, with the possibility of programming mid to long-term investments for public and private properties, as well as defining custom financial support mechanisms and tax incentives.