Abstract
A traffic incident is defined by an event which provokes a disruption on the normal (free) flow condition of any highway. Such incidents must be caused by a recurrent excessive demand or, in alternative, by a series of possible stochastic occurrences which may suddenly reduce the road capacity (e.g. car accidents, extreme weather changes). This paper proposes a novel binary supervised learning method to classify congestion predictions regarding their causes - CJAMmer. It leverages on heterogeneous and ubiquitous data sources - such as weather, flow counts and traffic incident event logs -To generalize decision models able to understand the road congestion nature. CJAMmer settles on boosted decision trees using the well-known C4.5, as well as a straightforward feature generation process. A real world experiment was used to compare this method against other state-of-The-Art classifiers. The results uncovered the high potential impact of this methodology on industrial scale traffic control systems. © 2016 IEEE.

Abstract
Background/Aims: Intradialytic hypotension (IDH) is a serious and frequent complication of hemodialysis (HD). Thus far, data are scarcely available to assess the impact of first versus subsequent HD sessions of the week in IDH. Therefore, the purpose of this work was to evaluate IDH risk in patients on thrice-weekly HD. Methods: We conducted an analysis of all blood pressure (BP) measurements obtained during 492 HD treatments given to 41 prevalent adult patients over a one month period. A logistic regression model for repeated binary observations was used to determine the association between hypotension and patient and dialysis factors. Results: The incidence of IDH was 32.5%. First dialysis session of the week was associated with a 9% higher risk of hypotension relatively to the second one. The risk was even higher from the first to the third session of the week (60%) and from the second to the third (50%). A higher hypotension odds ratio was also associated with age (1.03, 90% CI: 1.01-1.06), higher predialysis BP (1.04, 90% CI: 1.03-1.05) and higher phosphorus level (1.38, 90% CI: 1.07-1.76). The risk decreased 24.4% for each additional antihypertensive drug taken by the patient. Conclusions: The odds of hypotension occurrence decrease throughout dialysis sessions of the week. Minimizing modifiable risk factors may decrease IDH episodes. (C) 2016 The Author(s) Published by S. Karger AG, Basel

Abstract

Abstract
Wind power is the source of electrical energy that has grown more over the last years, with annual rate in installed capacity around 20%. Therefore, it is important to optimize the production efficiency of wind farms. In a wind farm, the electrical energy is collected at a central substation from different wind turbines placed nearby. This paper addresses the optimal design of the cable network interconnecting the turbines to the substation aiming to minimize not only the infrastructure cost but also the cost of the energy losses in the cables. Although this problem is non-linear, different integer linear programming models are proposed considering the wind farm technical constraints. The models are applied to three real cases Portuguese wind farms. The computational results show that the proposed models are able to compute the optimal solutions for all cases.

Abstract
In the past few decades, ecological and environmental issues have dominated the forest industry worldwide, but economic aspects have been much less studied in this dynamic period. However, a sustainable and efficient forest biomass supply is critical for socio-economic development in many regions, particularly in rural areas. Nature protection efforts have contributed to reduced harvesting quotas, which have resulted in an imbalance of the environmental functions of the forests and forest management, particularly wood supply. Considering the size and distribution of forest production management units and the forest stands that compose those units, there is a clear need for improved decision-making tools that help forest managers in planning harvest sequences. The optimization of harvest scheduling should consider economic and spatial factors, which may reduce production costs by increasing the logistic efficiency. Moreover, incorporating maximum harvesting opening size constraints into planning can help preserve biodiversity. This article presents a new spatial harvest scheduling model based on the integer programming method; it was developed using real data from a forest production unit located in the northern part of the southeast region of Brazil. The goal of the proposed scheduling approach is to maximize the net present value and concentrate the harvesting locations in each period. In spite of the fact that the object of the study is plantation forest under management different to common conditions in Europe or North America, the model is flexible and can be used in management of forest in Central Europe. © 2016 Jan Kašpar et al.

Abstract
This paper considers a multi-item inventory distribution problem motivated by a practical case occurring in the logistic operations of an hospital. There, a single warehouse supplies several nursing wards. The goal is to define a weekly distribution plan of medical products that minimizes the visits to wards, while respecting inventory capacities and safety stock levels. A mathematical formulation is introduced and several improvements such as tightening constraints, valid inequalities and an extended reformulation are discussed. In order to deal with real size instances, an hybrid heuristic based on mathematical models is introduced and the improvements are discussed. A branch-and-cut algorithm using all the discussed improvements is proposed. Finally, a computational experimentation is reported to show the relevance of the model improvements and the quality of the heuristic scheme. © Springer International Publishing AG 2016.