Abstract
Biodiversity of cowpea, along with the interesting agricultural and nutritional properties, has encouraged research with local landraces of Portugal. This work deals with the composition of dry beans of cowpea from 28 different Portuguese cultivars concerning dry matter (DM), crude proteins (CP), fat content (FC), ash, and concentration of free essential and non-essential amino acids. Data obtained on these traits showed contents of DM, FC, ash, and CP in the ranges of 95.7-98.9%, 1.0-1.6%, 2.7-4.7%, and 18.6-26.9%, respectively. The content in free amino acids was evaluated as an indicator of germinating potential of the diverse cultivars assessed. The amino acids content was the highest in the varieties 'Vg50' and 'Vg58'. Cluster and principal component analyses of the data allowed the identification of the most promising Portuguese landraces of cowpea to be used for breeding new varieties with improved germination potential and nutritional traits.

Abstract
Modern electric vehicles are most often designed with actuator redundancy and in-wheel propulsion, a combination that appears particularly suitable for the design of motion controllers that can optimally blend multiple objectives, such as dynamic, safety and driver-oriented. This paper considers such a technological setting and concentrates on the design of a path-following algorithm with minimum-time features, with the aim of combining performance and energy-oriented optimization of the vehicle motion. Specifically, an approximate minimum-time trajectory is obtained by appropriate convexification of the resulting optimization problem. The effectiveness of the approach is assessed by means of simulation tests carried out on the CarSim vehicle simulation environment.

Abstract

Abstract
The problem of analyzing massive graph streams in real time is growing along with the size of streams. Sampling techniques have been used to analyze these streams in real time. However, it is difficult to answer questions like, which structures are well preserved by the sampling techniques over the evolution of streams? Which sampling techniques yield proper estimates for directed and weighted graphs? Which techniques have least time complexity etc? In this work, we have answered the above questions by comparing and analyzing the evolutionary samples of such graph streams. We have evaluated sequential sampling techniques by comparing the structural metrics from their samples. We have also presented a biased version of reservoir sampling, which shows better comparative results in our scenario. We have carried out rigorous experiments over a massive stream of 3 hundred million calls made by 11 million anonymous subscribers over 31 days. We evaluated node based and edge based methods of sampling. We have compared the samples generated by using sequential algorithms like, space saving algorithm for finding topK items, reservoir sampling, and a biased version of reservoir sampling. Our overall results and observations show that edge based samples perform well in our scenario. We have also compared the distribution of degrees and biases of evolutionary samples.

Abstract
This paper develops an innovative methodology to assess municipal performance concerning the environmental efficiency of new buildings construction, focusing on the consumption of different types of materials. This study aims to support local governments in the definition of policies for improvements in service provision based on the results of a benchmarking study. The methodology developed includes two stages. The first step concerns the evaluation of municipal environmental efficiency using Data Envelopment Analysis and the identification of factors that may explain different levels of performance. The second step enables the classification of municipalities in terms of the efforts required to achieve environmental efficiency. For this purpose, we used clustering analysis, namely the k-means algorithm. To illustrate the methodology developed, we analyzed the data of the major materials used in the construction of new buildings (metals, non-metallic minerals, fossil fuels, and biomass) in the municipalities of Lisbon metropolitan area between 2003 and 2009. The study revealed that the environmental efficiency of new buildings construction varies considerably among municipalities, suggesting a high potential for performance improvement.

Abstract
Tracking objects in video is a very challenging research topic, particularly when people in groups are tracked, with partial and full occlusions and group dynamics being common difficulties. Hence, its necessary to deal with group tracking, formation and separation, while assuring the overall consistency of the individuals. This paper proposes enhancements to a group management and tracking algorithm that receives information of the persons in the scene, detects the existing groups and keeps track of the persons that belong to it. Since input information for group management algorithms is typically provided by a tracking algorithm and it is affected by noise, mechanisms for handling such noisy input tracking information were also successfully included. Performed experiments demonstrated that the described algorithm outperformed state-of-the-art approaches.