Abstract
Several algorithms based on PageRank algorithm have been proposed to rank the document sentences in the multi-document summarization field and LexRank and T-LexRank algorithms are well known examples. In literature different concepts such as weighted inter-cluster edge, cluster-sensitive graph model and document-sensitive graph model have been proposed to improve LexRank and T-LexRank algorithms (e.g. DsR-G, DsR-Q) for multi-document summarization. In this paper, a density-based graph model for multi-document summarization is proposed by adding the concept of density to LexRank and T-LexRank algorithms. The resulting generic multi-document summarization systems, DensGS and DensGSD were evaluated on DUC 2004 while the query-based variants, DensQS, DensQSD were evaluated on DUC 2006, DUC 2007 and TAC 2010 task A. ROUGE measure was used in the evaluation. Experimental results show that density concept improves LexRank and T-LexRank algorithms and outperforms previous graph-based models (DsR-G and DsR-Q) in generic and query-based multi-document summarization tasks. Furthermore, the comparison of the number of iterations indicates that the density-based algorithm is faster than the other algorithms based on PageRank.

Abstract

Abstract
In previous work regarding public-private partnership (PPP) arrangements the theoretical rationales and empirical results have mainly focused on analyzing the importance of quantitative features related to budget constraints deriving from public deficits, the existence of an infrastructure gap and the efficiency hypothesis. Thus, this study aims to identify the underlying determinants behind the proliferation and execution of PPPs, emphasizing the importance that non-financial (such as political, legal and macroeconomic) determinants have in establishing a PPP, as well as the factors that enhance the attractiveness of a country to encourage the private sector through PPPs in the European context. The results of this study show that the macroeconomic environment represented by economic freedom, competitiveness and the unemployment rate is essential for PPPs, as well as the legal system, where regulatory quality and effective rule of law are associated with the effective execution of a PPP. The political environment and previous experience of PPPs are also key factors in making a country more attractive for establishing PPPs.

Abstract
This paper presents a biased random-key genetic algorithm (BRKGA) for the unequal area facility layout problem (UA-FLP) where a set of rectangular facilities with given area requirements has to be placed, without overlapping, on a rectangular floor space. The objective is to find the location and the dimensions of the facilities such that the sum of the weighted distances between the centroids of the facilities is minimized. A hybrid approach combining a BRKGA, to determine the order of placement and the dimensions of each facility, a novel placement strategy, to position each facility, and a linear programming model, to fine-tune the solutions, is developed. The proposed approach is tested on 100 random datasets and 28 of benchmark datasets taken from the literature and compared with 21 other benchmark approaches. The quality of the approach was validated by the improvement of the best known solutions for 19 of the 28 extensively studied benchmark datasets.

Abstract
Airborne pollen emission model was used to determine pollen metrics and to examine their relationship with vineyard phenology in two wine regions of Northern Portugal: Vinhos Verdes (1993-2007) and Douro (1992-2011). A number of airborne pollen metrics were obtained through the rate of changes of logistic model adjusted to the time series of airborne pollen. In both regions, the mean absolute differences between observed phenology and model-predicted values for start, peak and final of flowering phenophases were always lower than 5 days and the slope of the regression through the origin is close to one. These metrics can be used to accurately and precisely predict the dynamic of Vitis flowering observed at field level. The model's simplicity and flexibility are of great advantage for its practical use in aerobiology.

Abstract
In this work, kriging with covariates is used to model and map the spatial distribution of salinity measurements gathered by an autonomous underwater vehicle in a sea outfall monitoring campaign aiming to distinguish the effluent plume from the receiving waters and characterize its spatial variability in the vicinity of the discharge. Four different geostatistical linear models for salinity were assumed, where the distance to diffuser, the west-east positioning, and the south-north positioning were used as covariates. Sample variograms were fitted by the MatSrn models using weighted least squares and maximum likelihood estimation methods as a way to detect eventual discrepancies. Typically, the maximum likelihood method estimated very low ranges which have limited the kriging process. So, at least for these data sets, weighted least squares showed to be the most appropriate estimation method for variogram fitting. The kriged maps show clearly the spatial variation of salinity, and it is possible to identify the effluent plume in the area studied. The results obtained show some guidelines for sewage monitoring if a geostatistical analysis of the data is in mind. It is important to treat properly the existence of anomalous values and to adopt a sampling strategy that includes transects parallel and perpendicular to the effluent dispersion.