Abstract
MOOCs are a recent phenomenon, although given their impact, they have been subject to a large debate. Several questions have been raised by researchers and educators alike regarding their sustainability, both economically and as an efficient mode of education provision. In this paper we contribute to this discussion by presenting a case study of the MOOC on Lived Experiences of Climate Change, which piloted the iMOOC pedagogical model developed at Universidade Aberta (UAb), the Portugese Distance Learning University. The iMOOC is a hybrid model which incorporates elements from existing MOOCs but adds other features drawn from UAb's experience with online learning and aims at better integrating in the larger context of the institutional pedagogical culture. The iMOOC implied also an integration of platforms - Moodle and Elgg. The pilot course had more than one thousand registrations, and it was the largest MOOC course on Portuguese language delivered so far. We discuss the effort required to design and deliver the course, the technological solution developed, and the results obtained. We registered a moderate effort to create and run the course, ensured by internal staff from the University. The technological solution was a success: an integrated architecture combining well-established, well-tested open software. The completion rate was 3.3%, but the high success of this innovative learning experience was demonstrated by the active involvement of about 50% of the registered participants, that followed the course until the end. Lessons learned from this experience and future research on the field are also discussed.

Abstract
In a bankruptcy situation individuals are not equally affected since each one has its own specific characteristics. These aspects cannot be ignored and may justify an allocation bias in favor of or against some individuals. This paper develops a theory of differentiation in claims problems that considers not only the vector of claims, but also some justified differentiating criteria based on other characteristics (wealth, net-income, GDP, etc.). Accordingly, we propose some progressive transfers from richer to poorer claimants with the purpose of distributing the damage as evenly as possible. Finally, we characterize our solution by means of the Lorenz criterion. Endogenous convex combinations between solutions are also considered.

Abstract
We consider the problem of scheduling a number of jobs on a number of unrelated parallel machines in order to minimize the makespan. We develop three heuristic approaches, i.e., a genetic algorithm, a tabu search algorithm and a hybridization of these heuristics with a truncated branch-and-bound procedure. This hybridization is made in order to accelerate the search process to near-optimal solutions. The branch-and-bound procedure will check whether the solutions obtained by the meta-heuristics can be scheduled within a tight upper bound. We compare the performances of these heuristics on a standard dataset available in the literature. Moreover, the influence of the different heuristic parameters is examined as well. The computational experiments reveal that the hybrid heuristics are able to compete with the best known results from the literature.

Abstract
Real-time monitoring applications may be used in a wireless sensor network (WSN) and may generate packet flows with strict quality of service requirements in terms of delay, jitter, or packet loss. When strict delays are imposed from source to destination, the packets must be delivered at the destination within an end-to-end delay (EED) hard limit in order to be considered useful. Since the WSN nodes are scarce both in processing and energy resources, it is desirable that they only transport useful data, as this contributes to enhance the overall network performance and to improve energy efficiency. In this paper, we propose a novel cross-layer admission control (CLAC) mechanism to enhance the network performance and increase energy efficiency of a WSN, by avoiding the transmission of potentially useless packets. The CLAC mechanism uses an estimation technique to preview packets EED, and decides to forward a packet only if it is expected to meet the EED deadline defined by the application, dropping it otherwise. The results obtained show that CLAC enhances the network performance by increasing the useful packet delivery ratio in high network loads and improves the energy efficiency in every network load.

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
In those positioning systems based on the detection of acoustic signals, an accurate detection of the arrival times is crucial for a correct estimation of the distance between nodes, and therefore, for the precise estimation of the node that wants to be located. In order to obtain this arrival time more accurately, acoustic signals can be coded using pseudorandom noise, but these coded signals are still affected by underwater channel phenomena. In this work, the detection of spread-spectrum modulated signals is analyzed in underwater environments that are highly affected by multipath and reverberation. A spread-spectrum signal, which consist of a modulated Kasami code, has been emitted through two different pools, reaching a receiver where it has been captured after following several line-of-sight and non-line-of-sight paths. Then, a correlation process has been performed offline to provide information about the arrival times (times-of-flight) that form the multipath structure. These times-of-flight are compared with those provided by an underwater acoustic propagation model, in order to test the performance of this model and its capacity to predict the outcome of signal detection in underwater environments with a strong multipath and reverberation component. That way, the validated propagation model could be later used in future studies to predict the detection of spread-spectrum signals and the performance of systems that use them in these adverse environments.