Abstract
Background: Growth trends have never been studied in adolescents of the Autonomous Region of Madeira, Portugal. Aims: To analyse growth trends in weight, height, body mass index (BMI), waist circumference (WC), mid-upper arm circumference (MUAC) and triceps skin-fold thickness (TST) of adolescents (10-17 years old) of the Autonomous Region of Madeira between 1996-1998 and 2007-2009. Subjects and methods: A cross-sectional study was carried out between 2007-2009, including 4314 adolescents, 2237 girls and 2077 boys (10-17 years old). To study secular growth trends, data were compared with a sample from 1996-1998, comparing the means for each anthropometric variable by age and sex using the independent-sample t-test. Results: An average increase was found in weight of 5.8 kg in boys and 6.3 kg in girls; in height of 3.0 cm in boys and 3.7 cm in girls; in BMI of 1.5 kg/m(2) in boys and 1.7 kg/m(2) in girls; in WC a difference of 5.6 cm and 4.9 cm for boys and girls, respectively, and for MUAC a difference of 2.7 cm in boys and 2.0 cm in girls. No differences were found in TST in boys, but in girls an increase of 1.2mm was observed. Conclusions: A general increase in anthropometric measurements, more marked in weight, BMI, WC and MUAC and at younger ages, was observed.

Abstract
Temporal Web Image Retrieval can be defined as the process that retrieves sets of Web images with their temporal dimension from explicit or implicit temporal text queries. Supposing that (a) the temporal dimension is included in image indexing and (b) the query is explicitly expressed with a time tag (e. g. "Fukushima 2011"), the retrieval task can be straightforward as image retrieval has been studied for several years with success. However, text queries are usually implicit in time (e. g. "Second World War") and automatically capturing the time dimension included in Web images is a challenge that has not been studied so far to the best of our knowledge. In this paper, we will discuss different research issues about Temporal Web Image Retrieval and the current progresses of our research in temporal ephemeral clustering and temporal image filtering.

Abstract
In this paper, we consider the single machine scheduling problem with weighted quadratic tardiness costs. Several efficient dispatching rules are proposed. These include existing heuristics for the linear problem, as well as procedures suitably adapted to the quadratic objective function. Also, both forward and backward scheduling procedures are considered. The computational results show that the heuristics that specifically take into account the quadratic objective significantly outperform their linear counterparts. Also, the backward scheduling approach proves to be superior, and the difference in performance is even more noticeable for the harder instances. The best of the backward scheduling heuristics is both quite efficient and effective. Indeed, this procedure can quickly generate a schedule even for large instances. Also, its relative deviation from the optimum is usually rather low, and it performs adequately even for the more difficult instances.

Abstract
This paper considers a problem in which there is a set of jobs to be sequenced on a single machine. Each job has a weight and the objective is to sequence the jobs to minimize total weighted squared tardiness. A branch-and-bound algorithm is developed for optimally solving the problem. Several dominance conditions are presented for possible inclusion in the branch-and-bound algorithm. The dominance conditions are included in the branch-and-bound algorithm, which is tested on randomly generated problems of various numbers of jobs, due date tightness and due date ranges. The results show that the dominance conditions dramatically improve the efficiency of the branch-and-bound algorithm.

Abstract
In this paper we present three hybrid heuristics for the single machine scheduling problem with quadratic earliness and tardiness costs, and no machine idle time. Our heuristic is a combination of a steady-state genetic algorithm and three improvement procedures. The two computationally less expensive of these three improvement procedures are used inside the genetic algorithm to improve the schedule obtained after the application of genetic operators, whereas the more expensive one is used to improve the best solution returned by the genetic algorithm. We have compared our hybrid approaches against existing recovering beam search and genetic algorithms. The computational results show the effectiveness of our hybrid approaches. Indeed, our hybrid approaches outperformed the existing heuristics in terms of solution quality as well as running time.

Abstract
By combining features from distinct theoretical approaches, namely the evolutionary and the job search, matching and bargaining literatures, we propose a model that captures the main dynamics of a world where heterogeneous firms and workers interact and co-evolve. Within a micro-meso framework, the model focuses on the influence of firms' labour choices ("institutional settings") on industry dynamics, taking into account the existence of employment adjustment costs. The consideration of endogenous matching and bargaining processes in the labour market results in significant frictions, such as the simultaneous coexistence of unfilled job vacancies and unemployment. In a setting where technological progress is not biased a stylized fact of industrialized world economies in the last few decades emerges, the increasing wage inequality. Additionally, turbulence in the industry increases after a negative demand shock. As expected, the negative demand shock causes a decrease in the number of vacancies and, consequently, unemployment rates increase considerably. Interestingly, and mimicking the recent experiences of countries such as US, Spain, Greece and Portugal, the rise in unemployment is matched by a rise in contractual wages. This outcome is explained by the lower ability of the firms to fill their posted vacancies, which results from friction in the interactions among agents.