Dispatching and Rescheduling Tasks and Their Interactions with Travel Demand and the Energy Domain: Models and Algorithms

Abstract The paper aims to provide an overview of the key factors to consider when performing reliable modelling of rail services. Given our underlying belief that to build a robust simulation environment a rail service cannot be considered an isolated system, also the connected systems, which influence and, in turn, are influenced by such services, must be properly modelled. For this purpose, an extensive overview of the rail simulation and optimisation models proposed in the literature is first provided. Rail simulation models are classified according to the level of detail implemented (microscopic, mesoscopic and macroscopic), the variables involved (deterministic and stochastic) and the processing techniques adopted (synchronous and asynchronous). By contrast, within rail optimisation models, both planning (timetabling) and management (rescheduling) phases are discussed. The main issues concerning the interaction of rail services with travel demand flows and the energy domain are also described. Finally, in an attempt to provide a comprehensive framework an overview of the main metaheuristic resolution techniques used in the planning and management phases is shown

Defining Reserve Times for Metro Systems: An Analytical Approach

The aim of this paper is to provide an analytical approach for determining operational parameters for metro systems so as to support the planning and implementation of energy-saving strategies. Indeed, one of the main targets of train operating companies is to identify and implement suitable strategies for reducing energy consumption. For this purpose, researchers and practitioners have developed energy-efficient driving profiles with the aim of optimising train motion. However, as such profiles generally entail an increase in travel times, the operating parameters in the planned timetable need to be appropriately recalibrated. Against this background, this paper develops a suitable methodology for estimating reserve times which represent the main rate of extra time needed to put ecodriving strategies in place. Our proposal is to exploit layover times (i.e., times spent by a train at the terminus waiting for the next trip) for energy-saving purposes, keeping buffer times intact in order to preserve the flexibility and robustness of the timetable in case of delays. In order to show its feasibility, the approach was applied in the case of a real metro context, whose service frequency was duly taken into account. In particular, after stochastic analysis of the parameters involved for calibrating suitable buffer times, different operating schemes were simulated by analysing the relationship between layover times, number of convoys, and feasible headway values. Finally, some operation configurations are analysed in order to quantify the amount of energy that can be saved

Methodology for Determining Dwell Times Consistent with Passenger Flows in the Case of Metro Services

Abstract The importance of a mobility system based on railway technology as the backbone of public transport is now widely acknowledged. Indeed, rail systems are green, high performing, smart and able to ensure a high degree of safety. Therefore, modal split should be steered towards rail transport by increasing the attractiveness of this transport mode. In this context, a key element is represented by the timetabling design phase, which must aim to guarantee an appropriate degree of robustness of rail operations in order to ensure a high degree of system reliability and increase service quality. A crucial factor in the task of timetabling entails evaluating dwell times at stations. The innovative feature of this paper is the analytical definition of dwell times as flow dependent. Our proposal is based on estimating dwell times according to the crowding level at platforms and related interaction between passengers and the rail service in terms of user behaviour when a train arrives. An application in the case of a real metro system is provided in order to show the feasibility of the proposed approach

A scale space approach for unsupervised feature selection in mass spectra classification for ovarian cancer detection

<p>Abstract</p> <p>Background</p> <p>Mass spectrometry spectra, widely used in proteomics studies as a screening tool for protein profiling and to detect discriminatory signals, are high dimensional data. A large number of local maxima (a.k.a. <it>peaks</it>) have to be analyzed as part of computational pipelines aimed at the realization of efficient predictive and screening protocols. With this kind of data dimensions and samples size the risk of over-fitting and selection bias is pervasive. Therefore the development of bio-informatics methods based on unsupervised feature extraction can lead to general tools which can be applied to several fields of predictive proteomics.</p> <p>Results</p> <p>We propose a method for feature selection and extraction grounded on the theory of multi-scale spaces for high resolution spectra derived from analysis of serum. Then we use support vector machines for classification. In particular we use a database containing 216 samples spectra divided in 115 cancer and 91 control samples. The overall accuracy averaged over a large cross validation study is 98.18. The area under the ROC curve of the best selected model is 0.9962.</p> <p>Conclusion</p> <p>We improved previous known results on the problem on the same data, with the advantage that the proposed method has an unsupervised feature selection phase. All the developed code, as MATLAB scripts, can be downloaded from <url>http://medeaserver.isa.cnr.it/dacierno/spectracode.htm</url></p

Self-adaptive integrated photonic receiver for turbulence compensation in free space optical links

: In Free Space Optical (FSO) communication systems, atmospheric turbulence distorts the propagating beams, causing a random fading in the received power. This perturbation can be compensated using a multi-aperture receiver that samples the distorted wavefront on different points and adds the various signals coherently. In this work, we report on an adaptive optical receiver that compensates in real time for scintillation in FSO links. The optical front-end of the receiver is entirely integrated in a silicon photonic chip hosting a 2D Optical Antenna Array and a self-adaptive analog Programmable Optical Processor made of a mesh of tunable Mach-Zehnder interferometers. The photonic chip acts as an adaptive interface to couple turbulent FSO beams to single-mode guided optics, enabling energy and cost-effective operation, scalability to systems with a larger number of apertures, modulation-format and data-protocol transparency, and pluggability with commercial fiber optics transceivers. Experimental results demonstrate the effectiveness of the proposed receiver with optical signals at a data rate of 10 Gbit/s transmitted in indoor FSO links where different turbulent conditions, even stronger than those expected in outdoor links of hundreds of meters, are reproduced

A methodology for long-term analysis of innovative signalling systems on regional rail lines

A rail system may be considered a useful tool for reducing vehicular flows on a road system (i.e. cars and trucks), especially in high-density contexts such as urban and metropolitan areas where greenhouse gas emissions need to be abated. In particular, since travellers maximise their own utility, variations in mobility choices can be induced only by significantly improving the level-of-service of public transport. Our specific proposal is to identify the economic and environmental effects of implementing an innovative signalling system (which would reduce passenger waiting times) by performing a cost-benefit analysis based on a feasibility threshold approach. Hence, it is necessary to calculate long-term benefits and compare them with intervention costs. In this context, a key factor to be considered is travel demand estimation in current and future conditions. This approach was tested on a regional rail line in southern Italy to show the feasibility and utility of the proposed methodology

Dysregulation of principal cell miRNAs facilitates epigenetic regulation of AQP2 and results in nephrogenic diabetes insipidus

Background MicroRNAs (miRNAs), formed by cleavage of pre-microRNA by the endoribonuclease Dicer, are critical modulators of cell function by post-transcriptionally regulating gene expression. Methods Selective ablation of Dicer in AQP2-expressing cells (DicerAQP2Cre1 mice) was used to investigate the role of miRNAs in the kidney collecting duct of mice. Results The mice had severe polyuria and nephrogenic diabetes insipidus, potentially due to greatly reduced AQP2 and AQP4 levels. Although epithelial sodium channel levels were decreased in cortex and increased in inner medulla, amiloride-sensitive sodium reabsorption was equivalent in DicerAQP2Cre1 mice and controls. Small-RNA sequencing and proteomic analysis revealed 31 and 178 significantly regulated miRNAs and proteins, respectively. Integrated bioinformatic analysis of the miRNAome and proteome suggested alterations in the epigenetic machinery and various transcription factors regulating AQP2 expression in DicerAQP2Cre1 mice. The expression profile and function of three miRNAs (miR-7688-5p, miR-8114, and miR-409-3p) whose predicted targets were involved in epigenetic control (Phf2, Kdm5c, and Kdm4a) or transcriptional regulation (GATA3, GATA2, and ELF3) of AQP2 were validated. Luciferase assays could not demonstrate direct interaction of AQP2 or the three potential transcription factors with miR-7688-5p, miR-8114, and miR-409-3p. However, transfection of respective miRNA mimics reduced AQP2 expression. Chromatin immunoprecipitation assays demonstrated decreased Phf2 and significantly increased Kdm5c interactions at the Aqp2 gene promoter in DicerAQP2Cre1 mice, resulting in decreased RNA Pol II association. Conclusions Novel evidence indicates miRNA-mediated epigenetic regulation of AQP2 expression

Optimization models for the urban park pricing problem

Park pricing strategies are an important tool for rebalancing the modal split between personal car and transit systems in urban area. In fact, the high levels of congestion are mainly due to the preference of users for the private car system. In order to obtain a more equilibrate modal split it is possible, jointly with the improvement of transit system quality, to impose fares on use of private cars; it can be obtained by road pricing and/or park pricing strategies. Park pricing strategies are the simplest ones, since they can be managed without the adoption of advanced technologies.In this paper some park pricing strategies are proposed and some optimization models are formalized; these optimization models search for the optimal parking fares optimizing the value of some objective functions