Sur la planification de tournées de véhicules scolaires

The purpose of school bus services is to carry children from their homes to school and back. Scheduling and routing such services manually can be a long and tedious task, as it gives rise to complex combinatorial problems. To tackle those, we propose various heuristics in order to build good quality schedules of school bus routes for small and large size problems. The school bus routing and scheduling problem is modeled by introducing a performance measure corresponding to the service level provided to the children. This quality measure focusing on the children differs from previous approaches to the subject, in which the solution evaluation generally depends on the number of buses used or the lengths of the routes of the vehicles. In addition, our schedules allow the vehicles simultaneously to carry children going to different schools, which to our knowledge has only been treated once in the literature. Two problems are considered: one consisting in maximizing the average quality of children service level and another to maximize the quality of the worst service level provided to a child. These problems can be formulated as binary integer programs, but their size is too large to consider an exact resolution with current software and computers. A constructive method is proposed to obtain a feasible schedule which is optimized thereafter with various heuristics: simulated annealing, tabu search and variable neighborhood search. Let us note that, during optimization, the use of schedules violating the vehicle capacity is authorized. The heuristics employed, in their variant exploring infeasible solution set, are more effective than those that are confined to the feasible solution set. These methods also yield much higher quality schedules for real data sets than those actually used by the schools in question. An ideal schedule should allow to simultaneously optimize both objective functions mentioned above. In order to approach such a solution, a two phase method is proposed. The first phase consists in maximizing the minimum service level and the second in maximizing the average service level without reducing the minimum obtained during the first phase. We also developed an extension of our methods based on decomposition adapted to large scale problems. The proposed decomposition approach allows to considerably reduce computing time without giving up quality and is essential in order to solve problems with a large number of children. Let us finally note that a graphical user interface was developed, allowing to visualize, analyze and modify schedules generated by the heuristics. It is thus possible to integrate additional constraints that have not been modeled, or to adapt a solution in case of a small modification to the problem data

Physico-Chemical Features of Undoped and Fe/Cu-Doped Na0.67MnO2-Layered Cathodes for Sodium Batteries

Na0.67MnO2 (NMO) stands out among the layered cathode materials used for sodium batteries due to its high-capacity values, low cost, and environmental friendliness. Unfortunately, many drawbacks arise during cycling, but nanostructure tailoring and doping can help to mitigate them. Our aim was to synthesize undoped and Cu- or Fe-doped NMO samples via the sol-gel route, with a different cooling step to room temperature, i.e., in a natural way or via quenching. The formation of a mixture of polymorphs was observed, as well as differences in the external morphology of the powders' grains. The use of spectroscopic techniques, Mössbauer spectroscopy for the Fe-doped samples and Electron paramagnetic resonance, allowed us to gain insights into the oxidation states of transition metals and to make suggestions about the magnetic ordering, as well as on the possible presence of magnetic impurities. Cyclic voltammetry and galvanostatic cycling results were interpreted on the basis of the spectroscopic data: the introduction of substituents, in general, worsens the capacity values, due to the decrease in the P2 amount and the introduction of structural distortions. The structural stability of the samples in air as a function of time was also analyzed via X-ray diffraction, demonstrating the positive effect of Cu presence

Diversity and ethics in trauma and acute care surgery teams: results from an international survey

Background Investigating the context of trauma and acute care surgery, the article aims at understanding the factors that can enhance some ethical aspects, namely the importance of patient consent, the perceptiveness of the ethical role of the trauma leader, and the perceived importance of ethics as an educational subject. Methods The article employs an international questionnaire promoted by the World Society of Emergency Surgery. Results Through the analysis of 402 fully filled questionnaires by surgeons from 72 different countries, the three main ethical topics are investigated through the lens of gender, membership of an academic or non-academic institution, an official trauma team, and a diverse group. In general terms, results highlight greater attention paid by surgeons belonging to academic institutions, official trauma teams, and diverse groups. Conclusions Our results underline that some organizational factors (e.g., the fact that the team belongs to a university context or is more diverse) might lead to the development of a higher sensibility on ethical matters. Embracing cultural diversity forces trauma teams to deal with different mindsets. Organizations should, therefore, consider those elements in defining their organizational procedures. Level of evidence Trauma and acute care teams work under tremendous pressure and complex circumstances, with their members needing to make ethical decisions quickly. The international survey allowed to shed light on how team assembly decisions might represent an opportunity to coordinate team member actions and increase performance

Association of kidney disease measures with risk of renal function worsening in patients with type 1 diabetes

Background: Albuminuria has been classically considered a marker of kidney damage progression in diabetic patients and it is routinely assessed to monitor kidney function. However, the role of a mild GFR reduction on the development of stage 653 CKD has been less explored in type 1 diabetes mellitus (T1DM) patients. Aim of the present study was to evaluate the prognostic role of kidney disease measures, namely albuminuria and reduced GFR, on the development of stage 653 CKD in a large cohort of patients affected by T1DM. Methods: A total of 4284 patients affected by T1DM followed-up at 76 diabetes centers participating to the Italian Association of Clinical Diabetologists (Associazione Medici Diabetologi, AMD) initiative constitutes the study population. Urinary albumin excretion (ACR) and estimated GFR (eGFR) were retrieved and analyzed. The incidence of stage 653 CKD (eGFR < 60 mL/min/1.73 m2) or eGFR reduction > 30% from baseline was evaluated. Results: The mean estimated GFR was 98 \ub1 17 mL/min/1.73m2 and the proportion of patients with albuminuria was 15.3% (n = 654) at baseline. About 8% (n = 337) of patients developed one of the two renal endpoints during the 4-year follow-up period. Age, albuminuria (micro or macro) and baseline eGFR < 90 ml/min/m2 were independent risk factors for stage 653 CKD and renal function worsening. When compared to patients with eGFR > 90 ml/min/1.73m2 and normoalbuminuria, those with albuminuria at baseline had a 1.69 greater risk of reaching stage 3 CKD, while patients with mild eGFR reduction (i.e. eGFR between 90 and 60 mL/min/1.73 m2) show a 3.81 greater risk that rose to 8.24 for those patients with albuminuria and mild eGFR reduction at baseline. Conclusions: Albuminuria and eGFR reduction represent independent risk factors for incident stage 653 CKD in T1DM patients. The simultaneous occurrence of reduced eGFR and albuminuria have a synergistic effect on renal function worsening

Decision-aid methodology for the school bus routing and scheduling problem

We consider the school bus routing and scheduling problem, where transportation demand is known and bus scheduling can be planned in advance. We present a comprehensive methodology designed to support the decision of practitioners. We first propose a modeling framework where the focus is on optimizing the level of service for a given number of buses, then we describe an automatic procedure generating a solution to the problem. The procedure first builds a feasible solution, which is subsequently improved using a heuristic. We analyze two important issues associated with this methodology. On the one hand, we analyze the performance of three types of heuristics both on real and synthetic data. We recommend the use of a simulated annealing technique exploring infeasible solutions, which performs slightly better than all others. More importantly, we find that the performance of all heuristics is not globally affected by the choice of the parameters. This is important from a practitioner viewpoint, because the fine-tuning of algorithm parameters is not critical for the algorithms performance. We have successfully applied our methods on real problems and on large-scale problems. On the other hand, we propose an interactive tool allowing the practitioner to visualize the proposed solution, to test its robustness, and to dynamically rebuild new solutions if the data of the original problem are modified

Application of photogrammetry and image processing for the study of porous surface courses ::which accuracy for which application?

This article presents an application of photogrammetry and image processing for road sample analysis. The technique makes it possible to measure the void content of a sample and at the same time to analyse this physical characteristic as a function of the depth relative to the pavement surface. In a first part, the device dedicated and data acquired will be presented, then our algorithm (pore extraction and geometry processing) will be described and finally the results will be discussed, both on the quantitative aspect and on the transmission via a dedicated report

Decision-aid Methodology for the School Bus Routing and Scheduling Problem

We consider the school bus routing and scheduling problem, where transportation demand is known and bus scheduling can be planned in advance. We present a comprehensive methodology designed to support the decision of practitioners. We first propose a modeling framework where the focus is on optimizing the level of service for a given number of buses. Then, we describe an automatic procedure generating a solution to the problem. It first builds a feasible solution, which is subsequently improved using a heuristic. We analyze two important issues associated with this methodology. On the one hand, we analyze the performance of three types of heuristics both on real and synthetic data. We recommend the use of a simulated annealing technique exploring infeasible solutions, which performs slightly better than all others. More importantly, we find that the performance of all heuristics is not globally affected by the choice of the parameters. This is important from a practitioner viewpoint, as the fine tuning of algorithm parameters is not critical for its performance. On the other hand, we propose an interactive tool allowing the practitioner to visualize the proposed solution, to test its robustness, and to dynamically rebuild new solutions if the data of the origina