High-Speed rail (HSR) infrastructures are developing all over the world. This represents a sustainable travel option according to sustainability goals. Recent works have proposed adopting the LARG (Lean, Agile, Resilient, Green) approach to realise new high-speed rail (HSR) lines. This is a paradigm derived from industry and logistics. The adoption of the LARG paradigm in transport systems and railway infrastructures has different implications. The main objective of this paper is to investigate the main implications of the Lean component for realising a new HSR line. The Lean paradigm focuses primarily on cost reduction by eliminating waste and activities that do not generate added value. In the context of High-Speed Rail systems, this approach directly influences both infrastructure design criteria and service planning. It requires comparing the requirements defined during the design phase with the actual, measurable outcomes observed during operation (ex post). This study focuses on the LEAN component applied to a case study relative to the extension of the Italian high-speed rail network along the southern corridor. The case study raises significant questions about the effectiveness of national infrastructure investments, emphasising the need for a broader discussion about the technical criteria used to develop existing high-speed rail lines. This work is of interest to the scientific community, as well as to public and private decision-makers involved in transportation planning connected to high-speed rail infrastructure.
Task scheduling in heterogeneous edge environments involves conflicting objectives related to completion time and energy consumption. Classical low-overhead heuristics usually optimize one dominant criterion, whereas population-based multi-objective methods provide richer trade-off analysis at a higher decision cost. This paper studies a batch scheduler, called avg_frontier, intended for repeated scheduling in such environments. The proposed method is organized as a two-stage procedure. First, it constructs an aggregated surrogate model of available devices using average time and energy coefficients over feasible tasks. The scheduler solves a discrete bi-objective allocation problem in the space of task counts, builds a surrogate Pareto frontier, and selects a compromise point according to the area_ratio policy controlled by α . Second, the selected allocation is restored into a real task-to-device assignment and re-evaluated by exact simulation. The algorithm is evaluated in SimGrid on two heterogeneous testbeds: a compact three-node profile with 60 tasks and a generated 100-node profile with 6000 tasks. The comparison includes classical heuristics and Pareto-based evolutionary methods. The results show that avg_frontier provides a controllable transition between time-oriented and energy-oriented regimes while keeping the scheduler overhead substantially lower than population-based Pareto baselines. The method is not intended to dominate all alternatives in every region of the trade-off, but to provide a computationally cheap mechanism for navigating this trade-off under repeated scheduling.
This paper proposes a new format for a digital Birth Certificate. It contains a color photograph of the child's face and facial biometric characteristics, documentary information (child's full name, year of birth, etc.), information about the educational institution, and the full names of the mother and father. The developed software enables the creation of a digital Birth Certificate in the form of a BIO QR code that stores all the necessary documentary information about the child, which can be read by standard barcode scanners and software. The BIO QR code is embedded in the LSB layers of the color image of the child's face, allowing for the concealment of information, as the resulting image with embedded data is indistinguishable from the original. The proposed digital Birth Certificate is a GIF file consisting of a set of multimedia files (graphic, biometric, and documentary) that compactly store information about the child. The Digital Birth Certificate is a document that can be updated at various stages of a child's development and allows for the adjustment of documentary information and the characterization of their facial biometrics.
The ongoing debate on proximity-based planning has produced a wide range of methods for assessing access to everyday services. Yet, most of these approaches remain centred on what can be reached within a given time threshold, while giving less attention to the spatial structure that makes some streets more strategically relevant than others. This paper argues that, particularly in suburban areas, streets should be evaluated for their structural strategic value. Special attention should be given to corridors that connect weakly linked sub-systems, as they could support future proximity-oriented interventions. Building on recent research about weak ties in spatial systems and the Kemeny-based centrality measure (KBC), this paper proposes a simple diagnostic approach to bridgeness, developed within the framework of the DUT-funded EMC2 project. The aim is not to compare alternative bridgeness metrics, but to examine whether high-KBC segments in a suburban area already coincide with local functions, or instead reveal structurally important yet underused corridors. The approach is tested in Turano, a suburban area of Massa, Italy, located within the wider Versilia conurbation. Using a road-centreline representation and a verified inventory of amenities, the study investigates the relationship between bridging structure and the distribution of Points of Interest through the concepts of alignment and mismatch. The results offer an exploratory but operational framework for distinguishing between corridors that already act as local functional anchors and latent spatial assets whose potential is not yet reflected in the current distribution of services. The paper concludes that bridgeness can provide a useful additional layer for proximity-oriented planning, particularly when combined with reliable local data and with broader assessments of walkability, public-space quality, and functional needs.
The spread of malicious information on social networks is often explosive and difficult to control, especially in small-world structures and echo chambers. Traditional intervention strategies based on degree centrality are effective in scale-free networks; however, they often perform poorly in relatively homogeneous community networks, where bridge nodes may be more important than hubs. In this paper, we propose SPID (Shortest-Path Interdiction for Diffusion), a corridor-based mitigation framework that targets fast-spreading “diffusion corridors”, defined as shortest paths connecting high-risk source regions to target communities. The experimental implementation uses SPID++, a residual-updated version of SPID that adapts to rerouted paths after each intervention step. Experiments on the Watts–Strogatz network show that SPID++ reduces the total number of infected nodes by approximately 2.2 times compared with Degree Centrality. Budget sensitivity analysis further shows that SPID++ can protect up to 444 more nodes than Degree as the intervention budget increases. Runtime results indicate that batched shortest-path computation reduces the intervention-selection time of SPID++ while preserving the selected intervention set.
