Abstract
For efficient planning of waste collection routing, large municipalities may be partitioned into convenient sectors. The real case under consideration is the municipality of Monção, in Portugal. Waste collection involves more than 1600 containers over an area of 220 km2 and a population of around 20,000 inhabitants. This is mostly a rural area where the population is distributed in small villages around the 33 boroughs centres (freguesia) that constitute the municipality. In most freguesias, waste collection is usually conducted 3 times a week. However, there are situations in which the same collection is done every day. The case reveals some general and specific characteristics which are not rare, but are not widely addressed in the literature. Furthermore, new methods and models to deal with sectorization and routing are introduced, which can be extended to other applications. Sectorization and routing are tackled following a three-phase approach. The first phase, which is the main concern of the presentation, introduces a new method for sectorization inspired by Electromagnetism and Coulomb’s Law. The matter is not only about territorial division, but also the frequency of waste collection, which is a critical issue in these types of applications. Special characteristics related to the number and type of deposition points were also a motivation for this work. The second phase addresses the routing problems in each sector: new Mixed Capacitated Arc Routing with Limited Multi-Landfills models will be presented. The last phase integrates Sectoring and Routing. Computational results confirm the effectiveness of the entire novel approach.

Abstract
This paper attempts to propose a fair solution in generation scheduling problem in the presence of inherent uncertainties in short-term power system operation. The proposed methodology incorporates probabilistic methodology in the uncertainties representation section, while harmony search algorithm is adopted as a fast and reliable soft computing algorithm to solve the proposed nonlinear, non-convex, large-scaled and combinatorial problem. As an indispensable step towards a more economical power system operation, the optimal generation scheduling strategy in the presence of mixed hydro-thermal generation mix, deemed to be the most techno-economically efficient scheme, comes to the play and is profoundly taken under concentration in this study. This paper devises a comprehensive hybrid optimisation approach by which all the crucial aspects of great influence in the generation scheduling process can be accounted for. Two-point estimation method is also adopted probabilistically approaching the involved uncertain criteria. In the light of the proposed methodology being implemented on an adopted test system, the anticipated efficiency of the proposed method is well verified. © 2014 Taylor & Francis.

Abstract
Under the scope of a Portuguese regional maize ear competition (the "Sousa Valley Best Ear Competition"), an ear value (EV) formula was developed in 1993 based on published maize trait correlations. This formula had two main purposes, ears evaluation for the ear competition and maize improvement selection. The EV formula included only ear length, kernel weight at 15% moisture, number of rows and number of kernels/ear, with no direct inputs from farmers maize yield. In order to add a more scientific dimension to this popular maize evaluation approach, four main goals were defined: (1) to test alternative interpretable regression methods to provide new ear value formulas that better estimates the yield potential using ear traits; (2) to develop a new instance ranking method, allowing to select the best new ear value formula to be used on the ear competition; (3) to identify a set of traits that will help farmers on selection toward better yield; and (4) to compare the ranking results obtained by the original EV formula and the newly one developed, using data from the "Sousa Valley Best Ear" competition. To achieve these goals we analyzed some of the competition winning maize populations, on a multilocation field trial, collecting not only ear, but also field traits and yield. This data was analyzed using multiple linear regression (MLR) and multiple adaptive regression splines (MARS). A new ranking evaluation measure (PR.NDCG measure) was developed to rank the eleven interpretable regression methods obtained, and our results indicated that the most appropriate formula for yield potendal estimation included the original EV traits, but with different coefficients and was entitled adjusted EV (EVA). Ear weight, kernel depth and rachis 2, followed by cob and ear diameters and number of kernels per row were also considered traits of major importance to define potential EV formulas, i.e., contributing to yield increase. Plant stand was the most important field variable for yield potential estimation. We also observed, from comparing EV and EVA ranking, that four of the top ranks maize ears using EV were included on the EVA top ten ranks. From all the above and due to its simplicity, we conclude that the new EVA formula is a valid starting point for a long term engagement of farmers with maize germplasm development and improvement and an open door to their better understanding of maize quantitative genetics.

Abstract
Stub Wireless Mesh Networks (WMNs) are used to extend Internet access. The use of multiple channels improves the capacity of WMN but significant challenges arise when nodes are limited to a single-radio interface to form the WMN. In particular, the assignment of mesh nodes to channels results on the creation of multiple sub-networks, one per channel, where individual capacity may depend on the sub-network topologies This paper identifies the relevant topological characteristics of the sub-networks resultant from the channel assignment process and studies, through simulation, the impact and relative importance of those characteristics on the maximal throughput enabled by the stub WMN. The number of nodes in the gateways neighborhood and the hidden node problem in the gateways neighborhood were identified as the characteristics having the highest impact on the WMN throughput.

Abstract
Current approaches to game design improvements rely on time-consuming gameplay testing processes, which rely on highly subjective feedback from a target audience. In this paper, we propose a generalizable approach for building predictive models of players' emotional reactions across different games and game genres, as well as other forms of digital stimuli. Our input agnostic approach relies on the following steps: (a) collecting players' physiologically-inferred emotional states during actual gameplay sessions, (b) extrapolating the causal relations between changes in players' emotional states and recorded game events, and (c) building hierarchical cluster models of players' emotional reactions that can later be used to infer individual player models via fuzzy cluster membership vectors. We expect this work to benefit game designers by accelerating the affective playtesting process through the offline simulation of players' reactions to game design adaptations, as well as to contribute towards individually-tailored affective gaming.

Abstract
This paper aims to examine the impacts of fleet composition changes on emission due to the introduction of different road transportation policies in a medium size European country (Portugal) applying an ex-post analysis (e.g. policies based on fuel pricing, car scraping, car taxation). A baseline scenario was compared with a counterfactual scenario in order to understand what would occur in the absence of the introduction of those policies. For each scenario, four approaches were assessed using economic effects and/or human health costs. HC, CO, NOx, PM and CO2 emissions from passenger cars and light duty vehicles were evaluated. The results show high statistical significance (p <= 0.05) between CO emissions and different vehicle features as vehicle age, fuel type and engine classes. The same pattern was observed between the average vehicle age and HC, NOx and PM. After the implementation of road traffic policies, the average emission factors of the fleet decreased 28-62% for HC, CO, NOx, PM and 20-39% for CO2. However, if a counterfactual scenario would be implemented, the reduction would be 20-80% and 26-55% higher, respectively. The results demonstrates that although were recorded some benefits, the fleet characteristics distribution were more environmental friendly in 2001 than in 2011.