A MILP Framework to Solve the Sustainable System Optimum with Link MFD Functions

Given the increasing consciousness toward the environmental footprint of mobility, accommodating environmental objectives in existing transport planning strategies is imperative for research and practice. In this paper, we use the link macroscopic fundamental diagram (MFD) model to develop optimal routing strategies that minimize total system emissions (TSE) in multiple origin-destination (OD) networks. Piecewise linear (PWL) functions are used to approximate MFD for individual links, and to define link-level emissions. Dynamic network constraints, non-vehicle holding constraints, and convex formulations of the PWL functions are considered. Thus, the system-optimum dynamic traffic assignment (SO-DTA) problem with environmental objectives is formulated as a mixed integer linear program (MILP). Finally, on a synthetic network, numerical examples demonstrate the performance of the proposed framework

Urban Traffic Eco-driving: A Macroscopic Steady-State Analysis

International audienceThe problem of traveling at maximum energy efficiency (Eco-Driving) is addressed for urban traffic networks at macroscopic level. The scope of this paper is the analysis of the steady-state behavior of the system, given certain boundary flows conditions fixed by traffic lights timings, and in presence of a traffic control policy based on variable speed limits. The formal study is carried out on a two-cells variable length model adapted to the urban setup from previous works on highway traffic. Informative traffic metrics, aimed at assessing traffic and vehicles performance in terms of traveling time, infrastructure utilization and energy consumption, are then defined and adapted to the new macroscopic traffic model. If congestion in a road section does not spill back or vanish, the system is stable and many different equilibrium points can be reached via variable speed limits. Efficient operation points and traffic conditions are identified as a trade-off between optimization of global traffic energy consumption, traveling time and infrastructure utilization

Optimal Ecodriving Control: Energy-Efficient Driving of Road Vehicles as an Optimal Control Problem

International audienceTransportation is responsible for a substantial fraction of worldwide energy consumption and greenhouse gas emissions and is the largest sector after energy production. However, while emissions from other sectors are generally decreasing, those from transportation have increased since 1990. Reducing the impact of transportation is a task that is inherently associated with the improvement of energy efficiency, particularly for passenger cars that contribute to almost half of the whole sector

Arterial Bandwidth Maximization via Signal Offsets and Variable Speed Limits Control

International audienceThe problem of maximizing bandwidth along an arterial is here addressed by use of two combined control actions: traffic lights offsets and variable speed limits. The optimization problem has been enriched in order to account for traffic energy consumption and network travel time, thus avoiding impractical or undesirable solutions. A traffic microscopic simulator has been used to assess the performance of the proposed technique in terms of energy consumption, travel time, idling time, and number of stops. The theoretical bandwidth proves to be well correlated with idling time and number of stops, while the variable speed limits control shows interesting advantages in terms of energy consumption without penalizing the travel time. An analysis of the Pareto optimum has been carried out to help the designer choose a trade-off in the multi-objective optimization

Arterial Bandwidth Maximization via Signal Offsets and Variable Speed Limits Control

International audienceThe problem of maximizing bandwidth along an arterial is here addressed by use of two combined control actions: traffic lights offsets and variable speed limits. The optimization problem has been enriched in order to account for traffic energy consumption and network travel time, thus avoiding impractical or undesirable solutions. A traffic microscopic simulator has been used to assess the performance of the proposed technique in terms of energy consumption, travel time, idling time, and number of stops. The theoretical bandwidth proves to be well correlated with idling time and number of stops, while the variable speed limits control shows interesting advantages in terms of energy consumption without penalizing the travel time. An analysis of the Pareto optimum has been carried out to help the designer choose a trade-off in the multi-objective optimization

Speed Advisory and Signal Offsets Control for Arterial Bandwidth Maximization and Energy Consumption Reduction

International audienceThe problem of maximizing bandwidth along anarterial is addressed here by use of two combined control actions:traffic light offsets and recommended speeds. The optimizationproblem has been enriched in order to account for traffic energyconsumption and network travel time, thus avoiding impracticalor undesirable solutions. A traffic microscopic simulator has beenused to assess the performance of the proposed technique in termsof energy consumption, travel time, idling time, and number ofstops. The correlation of theoretical bandwidth with known trafficperformance metrics is studied, and an analysis of the Paretooptimum has been carried out to help the designer choose atradeoff in the multiobjective optimization. Finally, an evaluationof the traffic performance at different levels of traffic demandaims at showing the best operation conditions of the proposedstrategy. A demand-dependent optimization is proposed

Obesity and kidney stone disease. A systematic review

INTRODUCTION: Currently, abdominal obesity has reached an epidemic stage and obesity represents an important challenge for worldwide health authorities. Epidemiologic studies have demonstrated that the stone risk incidence increases with Body Mass Index, through multiple pathways. Metabolic syndrome and diabetes are associated with an increased renal stones disease incidence. The aim of this systematic review was to investigate the prevalence, morbidity, risk factors involved in the association between obesity and urolithiasis. EVIDENCE ACQUISITION: The search involved finding relevant studies from MEDLINE, EMBASE, Ovid, the Cochrane Central Register of Controlled Trials, CINAHL, Google Scholar, and individual urological journals between January 2001 and May 2017. The inclusion criteria were for studies written in the English language, reporting on the association between obesity and urinary stones. EVIDENCE SYNTHESIS: The underlying pathophysiology of stone formation in obese patients is thought to be related to insulin resistance, dietary factors, and a lithogenic urinary profile. Uric acid stones and calcium oxalate stones are observed frequently in these patients. Insulin resistance is thought to alter the renal acid-base metabolism, resulting in a lower urine pH, and increasing the risk of uric acid stone disease. Obesity is also associated with excess nutritional intake of lithogenic substances and with an increase in urinary tract infection incidence. Recent studies highlighted that renal stone disease increases the risk of myocardial infarction, progression of chronic kidney disease, and diabetes. Contemporary, bariatric surgery has been shown to be associated with hyperoxaluria and oxalate nephropathy. Certainly, the many health risks of obesity, including nephrolithiasis, will add more burden on urologists and nephrologists. CONCLUSIONS: Obesity related nephrolithiasis seems to necessitate weight loss as primary treatment, but the recognition of the associated complications is necessary to prevent induction of new and equally severe medical problems. The optimal approach to obesity control that minimizes stone risk needs to be determined in order to manage obesity-induced renal stones disease

Can daily intake of aspirin and/or statins influence the behavior of non-muscle invasive bladder cancer? A retrospective study on a cohort of patients undergoing transurethral bladder resection

Background: This study aimed to evaluate the behavior of non-muscle-invasive bladder cancer (NMIBC) in patients submitted to transurethral bladder resection (TURB) comparing subjects in chronic therapy with aspirin, statins, or both drugs to untreated ones. Methods: This retrospective study was conducted on 574 patients diagnosed with NMIBC who underwent TURB between March 2008 and April 2013. The study population was divided into two main groups: treated (aspirin and/or statins) and untreated. The treated group was further divided into three therapeutic subgroups: Group A (100 mg of aspirin, daily for at least two years); Group B (20 mg or more of statins, daily for at least two years); and Group C (100 mg of aspirin and 20 mg of statins together). The mean follow-up of patients was 45.06 months. Results: No significant differences were observed among the different groups at baseline. On multivariate analysis, statin treatment, smokers and high stage disease (T1) achieved the level of independent risk factor for the occurrence of a recurrence. When patients were stratified according to the different treatment; patients treated with statins (Group B) presented an higher rate of failure (56/91 patients; 61.5%) when compared to Group A (42/98 patients; 42.9%), Group C (56/98; 57.1%) and (133/287 patients; 46.3%). This difference corresponds to a significant difference in recurrence failure free survival (p = 0.01). Conclusions: Our results suggest that long-term treatment with aspirin in patients with NMIBC might play a role on reducing the risk of tumor recurrence. In contrast, in our investigation data from statins and combination treatment groups showed increased recurrence rates. A long-term randomized prospective study could definitively assess the possible role of this widely used drugs in NMIBC

Artificial Neural Networks (ANN) for automatic detection of dendritic-shaped cancer cells of cutaneous melanoma in Reflectance Confocal Microscopy (RCM) images

Melanoma (MM) is one of the tumors with the highest incidence. In Italy, MM affected about 13,700 patients out of 373,000 new cases of cancer in 2018, with prognosis dependent on the degree of tumor invasion and presence of metastasis at diagnosis: only an early detection can lead to a better prognosis. Recent evidence suggests that MM is a family of different tumors with varying abilities to grow and metastasize: dendritic-shaped tumor cells were typically found in thin MM in situ. Reflectance Confocal Microscopy (RCM) is a non-invasive imaging tool that enables in vivo observation of the skin at a quasi-histological resolution, providing transverse-section grayscale images related to refractive index of different tissues. In this work, a dataset of RCM images, from 13 healthy subjects and 22 patients affected by MM in situ, were used to train a Multi-Layer Perceptron (MLP) artificial neural network. Each image was subdivided into sub-blocks, labeled as positive if containing significant clusters of dendritic-shaped tumour cells. In each block, various standard features were calculated, e.g. Haralick's and features from the run-length matrices. The MLP was trained to recognize the presence of clusters of dendritic-shaped cancer cells. The preliminary results are encouraging, giving AUC=0.81 with about 73% accuracy. Tests are currently underway to improve quality

Eco-Driving in Urban Traffic Networks using Traffic Signal Information

International audienceThis work addresses the problem of finding energy-optimal velocity profiles for a vehicle in an urban traffic network. Assuming communication between infrastructure and vehicles (I2V) and a complete knowledge of the upcoming traffic lights timings, a preliminary velocity pruning algorithm is proposed in order to identify the feasible region a vehicle may travel along in compliance with city speed limits. Then, a graph discretizing approach is utilized for advanced selection, among the feasible ''green windows'', of the optimal ones in terms of energy consumption. Finally, a velocity trajectory is advised, which will be tracked by the driver-in-the-loop in order to pass through the signalized intersections without stopping. The proposed eco-driving assistance algorithm results are compared to the optimal solution provided by the Dynamic Programming, in order to prove not only the effectiveness but also its capability to be employed online due to its low computational load