An Efficient Hybrid Planning Framework for In-Station Train Dispatching

In-station train dispatching is the problem of optimising the effective utilisation of available railway infrastructures for mitigating incidents and delays. This is a fundamental problem for the whole railway network efficiency, and in turn for the transportation of goods and passengers, given that stations are among the most critical points in networks since a high number of interconnections of trains’ routes holds therein. Despite such importance, nowadays in-station train dispatching is mainly managed manually by human operators. In this paper we present a framework for solving in-station train dispatching problems, to support human operators in dealing with such task. We employ automated planning languages and tools for solving the task: PDDL+ for the specification of the problem, and the ENHSP planning engine, enhanced by domain-specific techniques, for solving the problem. We carry out a in-depth analysis using real data of a station of the North West of Italy, that shows the effectiveness of our approach and the contribution that domain-specific techniques may have in efficiently solving the various instances of the problem. Finally, we also present a visualisation tool for graphically inspecting the generated plans

Societal issues in machine learning: When learning from data is not enough

It has been argued that Artificial Intelligence (AI) is experiencing a fast process of commodification. Such characterization is on the interest of big IT companies, but it correctly reflects the current industrialization of AI. This phenomenon means that AI systems and products are reaching the society at large and, therefore, that societal issues related to the use of AI and Machine Learning (ML) cannot be ignored any longer. Designing ML models from this human-centered perspective means incorporating human-relevant requirements such as safety, fairness, privacy, and interpretability, but also considering broad societal issues such as ethics and legislation. These are essential aspects to foster the acceptance of ML-based technologies, as well as to ensure compliance with an evolving legislation concerning the impact of digital technologies on ethically and privacy sensitive matters. The ESANN special session for which this tutorial acts as an introduction aims to showcase the state of the art on these increasingly relevant topics among ML theoreticians and practitioners. For this purpose, we welcomed both solid contributions and preliminary relevant results showing the potential, the limitations and the challenges of new ideas, as well as refinements, or hybridizations among the different fields of research, ML and related approaches in facing real-world problems involving societal issues

A communication platform demonstrator for new generation railway traffic management systems: Testing and validation

Current rail traffic management and control systems cannot be easily upgraded to the new needs and challenges of modern railway systems because they do not offer interoperable data structures and standardized communication interfaces. To meet this need, the Horizon 2020 Shift2Rail OPTIMA project has developed a communication platform for testing and validating the new generation of traffic management systems (TMS), whose main innovative features are the interoperability of the data structures used, standardization of communications, continuous access to real-time and persistent data from heterogeneous data sources, modularity of components and scalability of the platform. This paper presents the main components, their functions and characteristics, then describes the testing and validation of the platform, even when federated with other innovative TMS modules developed in separate projects. The successful validation of the system has confirmed the achievement of the objectives set and allowed a new set of objectives to be defined for the reference platform for the railway TMS/Traffic Control systems

Comparison between Two Different Two-Stage Transperineal Approaches to Treat Urethral Strictures or Bladder Neck Contracture Associated with Severe Urinary Incontinence that Occurred after Pelvic Surgery: Report of Our Experience

Introduction. The recurrence of urethral/bladder neck stricture after multiple endoscopic procedures is a rare complication that can follow prostatic surgery and its treatment is still controversial. Material and Methods. We retrospectively analyzed our data on 17 patients, operated between September 2001 and January 2010, who presented severe urinary incontinence and urethral/bladder neck stricture after prostatic surgery and failure of at least four conservative endoscopic treatments. Six patients underwent a transperineal urethrovesical anastomosis and 11 patients a combined transperineal suprapubical (endoscopic) urethrovesical anastomosis. After six months the patients that presented complete incontinence and no urethral stricture underwent the implantation of an artificial urethral sphincter (AUS). Results. After six months 16 patients were completely incontinent and presented a patent, stable lumen, so that they underwent an AUS implantation. With a mean followup of 50.5 months, 14 patients are perfectly continent with no postvoid residual urine. Conclusions. Two-stage procedures are safe techniques to treat these challenging cases. In our opinion, these cases could be managed with a transperineal approach in patients who present a perfect operative field; on the contrary, in more difficult cases, it would be preferable to use the other technique, with a combined transperineal suprapubical access, to perform a pull-through procedure

A communication platform demonstrator for new generation railway traffic management systems: Testing and validation

\ua9 2023 The Author(s). Current rail traffic management and control systems cannot be easily upgraded to the new needs and challenges of modern railway systems because they do not offer interoperable data structures and standardized communication interfaces. To meet this need, the Horizon 2020 Shift2Rail OPTIMA project has developed a communication platform for testing and validating the new generation of traffic management systems (TMS), whose main innovative features are the interoperability of the data structures used, standardization of communications, continuous access to real-time and persistent data from heterogeneous data sources, modularity of components and scalability of the platform. This paper presents the main components, their functions and characteristics, then describes the testing and validation of the platform, even when federated with other innovative TMS modules developed in separate projects. The successful validation of the system has confirmed the achievement of the objectives set and allowed a new set of objectives to be defined for the reference platform for the railway TMS/Traffic Control systems

Basic tasks of sentiment analysis

Subjectivity detection is the task of identifying objective and subjective sentences. Objective sentences are those which do not exhibit any sentiment. So, it is desired for a sentiment analysis engine to find and separate the objective sentences for further analysis, e.g., polarity detection. In subjective sentences, opinions can often be expressed on one or multiple topics. Aspect extraction is a subtask of sentiment analysis that consists in identifying opinion targets in opinionated text, i.e., in detecting the specific aspects of a product or service the opinion holder is either praising or complaining about

Societal issues in machine learning: when learning from data is not enough

It has been argued that Artificial Intelligence (AI) is experiencing a fast process of commodification. Such characterization is on the interest of big IT companies, but it correctly reflects the current industrialization of AI. This phenomenon means that AI systems and products are reaching the society at large and, therefore, that societal issues related to the use of AI and Machine Learning (ML) cannot be ignored any longer. Designing ML models from this human-centered perspective means incorporating human-relevant requirements such as safety, fairness, privacy, and interpretability, but also considering broad societal issues such as ethics and legislation. These are essential aspects to foster the acceptance of ML-based technologies, as well as to ensure compliance with an evolving legislation concerning the impact of digital technologies on ethically and privacy sensitive matters. The ESANN special session for which this tutorial acts as an introduction aims to showcase the state of the art on these increasingly relevant topics among ML theoreticians and practitioners. For this purpose, we welcomed both solid contributions and preliminary relevant results showing the potential, the limitations and the challenges of new ideas, as well as refinements, or hybridizations among the different fields of research, ML and related approaches in facing real-world problems involving societal issues.Peer ReviewedPostprint (published version

Patterns on the numerical duplication by their admissibility degree

We develop the theory of patterns on numerical semigroups in terms of the admissibility degree. We prove that the Arf pattern induces every strongly admissible pattern, and determine all patterns equivalent to the Arf pattern. We study patterns on the numerical duplication $S \Join^d E$ when $d \gg0$. We also provide a definition of patterns on rings

Syngeneic transplantation in aplastic anemia: pre-transplant conditioning and peripheral blood are associated with improved engraftment: an observational study on behalf of the Severe Aplastic Anemia and Pediatric Diseases Working Parties of the European Group for Blood and Marrow Transplantation

Aplastic anemia is usually treated with immunosuppression or allogeneic transplant, depending on patient and disease characteristics. Syngeneic transplant offers a rare treatment opportunity with minimal transplant-related mortality, and offers an insight into disease mechanisms. We present here a retrospective analysis of all syngeneic transplants for aplastic anemia reported to the European Group for Blood and Marrow Transplantation. Between 1976 and 2009, 88 patients received 113 transplants. Most transplants (n=85) were preceded by a conditioning regimen, 22 of these including anti-thymocyte globulin. About half of transplants with data available (39 of 86) were followed by posttransplant immunosuppression. Graft source was bone marrow in the majority of cases (n=77). Transplant practice changed over time with more transplants with conditioning and anti-thymocyte globulin as well as peripheral blood stem cells performed in later years. Ten year overall survival was 93% with 5 transplant-related deaths. Graft failure occurred in 32% of transplants. Risk of graft failure was significantly increased in transplants without conditioning, and with bone marrow as graft source. Lack of posttransplant immunosuppression also showed a trend towards increased risk of graft failure, while anti-thymocyte globulin did not have an influence. In summary, syngeneic transplant is associated with a significant risk of graft failure when no conditioning is given, but has an excellent long-term outcome. Furthermore, our comparatively large series enables us to recommend the use of pre-transplant conditioning rather than not and possibly to prefer peripheral blood as a stem cell source

Exploiting the tunability of stimulated emission depletion microscopy for super-resolution imaging of nuclear structures

Imaging of nuclear structures within intact eukaryotic nuclei is imperative to understand the effect of chromatin folding on genome function. Recent developments of super-resolution fluorescence microscopy techniques combine high specificity, sensitivity, and less-invasive sample preparation procedures with the sub-diffraction spatial resolution required to image chromatin at the nanoscale. Here, we present a method to enhance the spatial resolution of a stimulated-emission depletion (STED) microscope based only on the modulation of the STED intensity during the acquisition of a STED image. This modulation induces spatially encoded variations of the fluorescence emission that can be visualized in the phasor plot and used to improve and quantify the effective spatial resolution of the STED image. We show that the method can be used to remove direct excitation by the STED beam and perform dual color imaging. We apply this method to the visualization of transcription and replication foci within intact nuclei of eukaryotic cells