Early Weight Gain During Pregnancy: Which Women Are the Most Affected?

Maternal weight gain during pregnancy is a good prediction tool in short and long term health of pregnant women and their children. To study the effect of early weight gain of pregnant women until the end of the 2nd trimester of pregnancy, depending on their pre-pregnancy body mass index. 116 healthy pregnant women were followed until the 2nd trimester of pregnancy, their weight and height before pregnancy, as well as the current weight at the end of the 1st and 2nd trimesters were collected. Data included age, parity, eating habits and physical activity level. Statistics were performed using the Statview software. The mean pre-pregnancy BMI was 27 ± 5.27 kg/m². Weight gain in the 2nd trimester is 6.33 ± 4.84 kg. It decreases with the increasing age of the mother (25% of women between 20 and 24.9 years vs 12.5% of more than 35). Also, it decreases with the increasing number of children (62.5% in nulliparous vs 25% in multiparous). Breakfast is skipped by 64.5 % of overweight pregnant women in the 1st trimester and 90 % in the 2nd one. 80.17% and 69.83% of pregnant women do not practice any physical activity. Overweight and obese pregnant women before pregnancy do not take enough weight during pregnancy. Prospects will to analyze behaviors related to health and social status

Electric Vehicle Scheduling and Optimal Charging Problem: Complexity, Exact and Heuristic Approaches

This paper deals with the Electric Vehicle Scheduling and Optimal Charging Problem.More precisely, given a eet of Electric Vehicles - EVs and Combustion Engine Vehicles - CVs, aset of tours to be processed by vehicles and a charging infrastructure, the problem aims to optimizethe assignment of vehicles to tours and minimize the charging cost of EVs, while considering severaloperational constraints mainly related to chargers, electricity grid, and EVs driving range. We provethat the Electric Vehicle Scheduling and Charging Problem (EVSCP) is NP-hard in the ordinary sense.We provide a mixed-integer linear programming formulation to model the EVSCP and use CPLEX tosolve small and medium instances. To solve large instances, we propose two heuristics: a SequentialHeuristic - SH and a Global Heuristic - GH. The SH considers the EVs sequentially. To each EV, itassigns a set of tours and guarantees the feasibility of a charging schedule using the Maximum WeightClique Problem. Then, it generates an optimal charging schedule for this EV using a Minimum CostFlow formulation. However, the GH computes, in the rst step, a feasible assignment of tours to allEVs. In the second step, it applies a global Min-Cost-Flow-based charging algorithm to minimize thecharging cost of the EVs eet. To evaluate the eciency of our solving approaches, computationalresults on a large set of real and randomly generated test instances are reported and compared. Testedinstances include large random instances with up to 200 EVs and 320 tours

Aroma characterization of ripe date fruits (Phoemix dactylifera L.) from Algeria

The headspace of eight Algerian date varieties with low market value were analyzed for their aroma compounds using solid phase micro extraction and gas chromatography combined with mass spectrometry. In this study, 61 identified compounds were categorized in various chemical classes on the basis of their functional groups, alcohols, esters, aldehydes, terpenoids, ketones, hydrocarbons, and ethers. Twenty specific volatiles were found to be representative of a single variety and four shared molecules were exclusively observed in all the studied dates. Some dates such as Bent Qbala, Litima, and Timjouhart were statistically different from the other varieties which presented on the contrary a significant similarity between them. In the present study, forty eight new volatile compounds were identified which could be useful for the characterization of the Algerian date

A priori approach of real-time ridesharing problem with intermediate meeting locations

Ridesharing is a mobility concept in which a trip is shared by a vehicle’s driver and one or more passengers called riders. Ridesharing is considered as a more environmentally friendly alternative to single driver commutes in pollution-creating vehicles on overcrowded streets. In this paper, we present the core of a new strategy of the ridesharing system, making it more flexible and competitive than the recurring system. More precisely, we allow the driver and the rider to meet each other at an intermediate starting location and to separate at another intermediate ending location not necessarily their origins and destinations, respectively. This allows to reduce both the driver’s detour and the total travel cost. The term “A priori approach” means that the driver sets the sharing cost rate on the common path with rider in advance. An exact and heuristic approaches to identify meeting locations, while minimizing the total travel cost of both driver and rider are proposed. Finally, we analyze their empirical performance on a set of real road networks consisting of up to 3,5 million nodes and 8,7 million edges. Our experimental results show that our heuristics provide efficient performances within short CPU times and improves the recurring ridesharing approach in terms of cost-savings

Flowshop Scheduling Problem with Batching Machines and Task Compatibilities

International audienc

Complexity of flow shop scheduling problems with Transportation Constraints

In most manufacturing and distribution systems, semi-finished jobs are transferred from one processing facility to another by transporters such as Automated Guided Vehicles, robots and conveyors, and finished jobs are delivered to warehouses or customers by vehicles such as trucks. This paper investigates two-machine flow shop scheduling problems taking transportation into account. The finished jobs are transferred from the processing facility and delivered to customers by truck. Both transportation capacity and transportation times are explicitly taken into account in these models. We study the class of flow shop problems by analysing their complexity. For the makespan objective function, we prove that this problem is strongly NP-hard when the capacity of a truck is limited to two or three parts with an unlimited buffer at the output of the each machine. This problem with additional constraints, such as blocking, is also proven to be strongly NP-hard

Ordonnancement conjoint de la production et de la maintenance

National audienc

Scheduling a no-wait flow shop with unbounded batching machines

International audienc

Permutation flowshop scheduling problems with time lags to minimize the weighted sum of machine completion times

In this article, we consider flowshop scheduling problems with minimal and maximal time lag constraints. Such constraints extend precedence constraints between operations in the jobs and may be used to model various industrial applications. The objective is to minimize a non-classical criterion based on the weighted sum of machine completion times. We show that it generalizes makespan and we derive several complexity results for two- and three-machine problems. An exact algorithm based on a branch-and-bound procedure is developed to solve the permutation flowshop problem with m machines.