Analysis of Madrid Metro Network: From Structural to HJ-Biplot Perspective

With the growth of cities, urban traffic has increased and traffic congestion has become a serious problem. Due to their characteristics, metro systems are one of the most used public transportation networks in big cities. So, optimization and planning of metro networks are challenges which governments must focus on. The objective of this study was to analyze Madrid metro network using graph theory. Through complex network theory, the main structural and topological properties of the network as well as robustness characteristics were obtained. Furthermore, to inspect these results, multivariate analysis techniques were employed, specifically HJ-Biplot. This analysis tool allowed us to explore relationships between centrality measures and to classify stations according to their centrality. Therefore, it is a multidisciplinary study that includes network analysis and multivariate analysis. The study found that closeness and eccentricity were strongly negatively correlated. In addition, the most central stations were those located in the city center, that is, there is a relationship between centrality and geographic location. In terms of robustness, a highly agglomerated community structure was found

Forecasting using dynamic factor models with cluster structure at Barcelona subway stations

Dynamic factor models are a powerful technique for analysing vast volumes of data, more precisely, time series. However, the large volumes of data that come from public transport networks tend to have heterogeneity and a cluster structure. In this paper, Dynamic Factor Models with Cluster Structure (DFMCS) are used to forecast hourly entrances in the different stations of the Barcelona subway network. The main and most novel contribution lies in the use of clustering techniques to make an initial grouping of the behaviour of the elements belonging to the time series, in order to subsequently be able to predict future patterns

Clustering and Forecasting Urban Bus Passenger Demand with a Combination of Time Series Models

The present paper focuses on the analysis of large data sets from public transport networks, more specifically, on how to predict urban bus passenger demand. A series of steps are proposed to ease the understanding of passenger demand. First, given the large number of stops in the bus network, these are divided into clusters and then different models are fitted for a representative of each of the clusters. The aim is to compare and combine the predictions associated with traditional methods, such as exponential smoothing or ARIMA, with machine learning methods, such as support vector machines or artificial neural networks. Moreover, support vector machine predictions are improved by incorporating explanatory variables with temporal structure and moving averages. Finally, through cointegration techniques, the results obtained for the representative of each group are extrapolated to the rest of the series within the same cluster. A case study in the city of Salamanca (Spain) is presented to illustrate the problem

Morphogenesis of rat experimental pulmonary emphysema induced by intratracheally administered papain: changes in elastic fibres

The ultrastructural changes of elastic fibres in emphysematous lungs have been studied in men, but few works exist on this topic in experimental emphysematous animals. In this paper, the morphogenesis of emphysema and alterations of the elastic fibres produced by the instillation of papain are described by light and electron microscopy. Wistar rats were instilled through the trachea with papain at a rate of 3 mg/100 g animal weight. The animals were sacrificed 12 h, 3 days, 10 days and 60 days after enzyme instillation. The "Mean Linear Intercept" (MLI), the "Number of fenestrations/respiratory units" (NF) the “Number of macrophages per mm of alveolar wall” (NM) and the "Number of respiratory unit/mm2” (RU), both in the control and experimental groups were studied. Two months after treatment, the experimental group showed a strong increase in the MLI (p<0.001) and NF (p<0.001), and a diminished number of RU (p<0.05) compared with the control group. Partial correlation analysis showed a positive correlation only between MLI and NF. Twelve hours after papain instillation an inflammatory response was observed, the elastic fibres were ruptured, while the microfibrilar component remained. New formations of eulanin elastic fibres were observed three days post papain instillation. After ten days the interalveolar oedema had disappeared and the elastic fibres were of normal morphology although irregular groups of strips of elastic fibres were evident. A mixed pattern of panlobular, centrilobular and normal lung zones were observed. Two months after papain instillation abundant accumulations of elastic fibres of irregular outline were observed associated to collagen fibres. In conclusion, the morphometric parameters studied showed a significant progression of the emphysema. The strong correlation between NF and MLI suggested that papain-induced emphysema is principally caused by breaches of the alveolar walls. The results seem to point to a very abnormal remodelling process associated with elastic fibre regeneration, although there were no signs of destruction of these new fibres formed in emphysematous rat lung induced by papain