Abstract
The bivalve dredge fleet is by far the most extensively studied fleet among the Portuguese artisanal segment. It is considered one of the most important artisanal fisheries, essentially due to the number of fishermen and vessels involved and to the high volume and value of the catches. The present study aimed to explore the efficiency of the dredge fleets that operated in the west coast of Portugal between 2006 and 2012. The methodology was based on the use of data envelopment analysis to assess vessels' efficiency. The inputs considered included the number of days at sea, a biomass stock indicator, and the characteristics of the vessels (power, length and tonnage). The annual fishing quota per vessel was also included in the model as a contextual factor. In the technical efficiency analysis, the outputs were defined by the weight of captures for three different bivalve species. Using data on the prices of each species in the wholesale market, revenue efficiency was also estimated to complement the technical efficiency analysis. The results allowed to gain insights concerning the performance of both Northwest and Southwest fleets, considering both technical and economic aspects of the fishery. It was also possible to identify the benchmark vessels, whose practices should be followed by the other vessels of the fleet.

Abstract
The bivalve dredge fleet, considered as one of the most important artisanal fleets due to the high value of the catches, is by far the most extensively studied among the Portuguese artisanal segment. Acknowledging the growing presence of marine phycotoxins in the waters, the present study explores their impact on the revenue of the fleet that operates along the coast of mainland Portugal. The results obtained using stochastic frontier analysis models enlighten the harmful impact of algae blooms on the activity of the artisanal dredge fleets. In particular, it was observed that in the Algarve region, where the frequency and the intensity of these episodes is higher, the sustainability of the dredge fishing activity is seriously compromised by the phycotoxins.

Abstract
This paper proposes two new measures to assess performance of surgical practice based on observed mortality: reliability, measured as the area under the ROC curve and a living score, the sum of individual risk among surviving patients, divided by the total number of patients. A Monte Carlo simulation of surgeons' practice was used for conceptual validation and an analysis of a real-world hospital department was used for managerial validation. We modelled surgical practice as a bivariate distribution function of risk and final state. We sampled 250 distributions, varying the maximum risk each surgeon faced, the distribution of risk among dead patients, the mortality rate and the number of surgeries performed yearly. We applied the measures developed to a Portuguese cardiothoracic department. We found that the joint use of the reliability and living score measures overcomes the limitations of risk adjustedmortality rates, as it enables a different valuation of deaths, according to their risk levels. Reliability favours surgeons with casualties, predominantly, in high values of risk and penalizes surgeons with deaths in relatively low levels of risk. The living score is positively influenced by the maximum risk for which a surgeon yields surviving patients. These measures enable a deeper understanding of surgical practice and, as risk adjusted mortality rates, they rely only on mortality and risk scores data. The case study revealed that the performance of the department analysed could be improved with enhanced policies of risk management, involving the assignment of surgeries based on surgeon's reliability and living score.

Abstract
This paper is about long-term travel time prediction in public transportation. However, it can be useful for a wider area of applications. It follows a heterogeneous ensemble approach with dynamic selection. A vast set of experiments with a pool of 128 tuples of algorithms and parameter sets (a&ps) has been conducted for each of the six studied routes. Three different algorithms, namely, random forest, projection pursuit regression and support vector machines, were used. Then, ensembles of different sizes were obtained after a pruning step. The best approach to combine the outputs is also addressed. Finally, the best ensemble approach for each of the six routes is compared with the best individual a&ps. The results confirm that heterogeneous ensembles are adequate for long-term travel time prediction. Namely, they achieve both higher accuracy and robustness along time than state-of-the-art learners.

Abstract
In this paper we briefly present our feelings about urban logistic and its role in urban mobility. In some way, we can say that this is a position paper based on an extensive review of all known related published material. We support the development of new approaches for the management of passenger and freight transport together as a single logistics system; based on the access to more and more sophisticated flows of data and better communication means, we envisage the dissemination of sufficient information for the correct decision of every citizens between several mobility options in real time (especially with the support of mobile technology); and we sustain that new tools are needed to help the design of innovative business models and policies, and the change of habits and behaviors. We visualize urban logistics as a multi-stakeholder, multi-criteria and multimodal mobility dynamic system.

Abstract
Intelligent transportation systems based on automated data collection frameworks are widely used by the major transit companies around the globe. This paper describes the current state of the art on improving both planning and control on public road transportation companies using automatic vehicle location (AVL) data. By surveying this topic, the expectation is to help develop a better understanding of the nature, approaches, challenges, and opportunities with regard to these problems. This paper starts by presenting a brief review on improving the network definition based on historical location-based data. Second, it presents a comprehensive review on AVL-based evaluation techniques of the schedule plan (SP) reliability, discussing the existing metrics. Then, the different dimensions on improving the SP reliability are presented in detail, as well as the works addressing such problem. Finally, the automatic control strategies are also revised, along with the research employed over the location-based data. A comprehensive discussion on the techniques employed is provided to encourage those who are starting research on this topic. It is important to highlight that there are still gaps in AVL-based literature, such as the following: 1) long-term travel time prediction; 2) finding optimal slack time; or 3) choosing the best control strategy to apply in each situation in the event of schedule instability. Hence, this paper includes introductory model formulations, reference surveys, formal definitions, and an overview of a promising area, which is of interest to any researcher, regardless of the level of expertise.