Carlos Pais Montes

La adecuación entre las competencias adquiridas por los graduados y las requeridas por los empresarios

During the last few years Spanish university has been forced to undergo a restructuring in order to harmonize with European higher education. This process has given rise to what is known as the European Area of Higher Education (EEES). Under this framework, students’ education main objective not only consists of the acquisition of knowledge, but also on the development of a range of competences based on academic and professional profiles. This research attempts to analyse in depth the understanding of professional competences by graduates of the University of A Coruna (henceforth UDC), and .how their competence knowledge relates with the competences sought for by the entrepreneurs of the same province. The methodology applied is quantitative, and built up in three phases: sample design, data collection and results analysis and subsequent processing. This methodology provides information about the items required by employers when hiring graduates, underscoring the most sought for. The conclusion of this article is dual: on the one hand it provides with an indicator to gauge the competence taken on by UDC graduates, and those applied in the business world; and on the other it provides very relevant information about the competences most sought for by employers. Broadly speaking, the adequacy between these indicators is average; however for some items there exists significant differences. Finally, the analysis confirms the importance that most employers give to practical training, precisely the key educational lack observed in the graduates.

Foreland determination for containership and general cargo ports in Europe (2007–2011)

A simple and accurate relationship is demonstrated that links the average shortest path, nodes, and edges in a complex network. This relationship takes advantage of the concept of link density and shows a large improvement in fitting networks of all scales over the typical random graph model. The relationships herein can allow researchers to better predict the shortest path of networks of almost any size. PACS numbers: 89.75.Hc, 89.75.Da, 89.75.Fb, 89.75.-k, 89.65.Ef Average Path Length in Complex Networks: Patterns and Predictions 2 The research of complex networks has exploded over the past decade with literally thousands of papers describing and theorizing about such networks in all details. This explosion of research followed the widespread availability of large network databases aided by the advance of computer technology and widespread online applications used by millions of users. Among the most prominent and wellknown studies have been those of the Internet [1], metabolic pathways[2], and scientific collaborations[3, 4]. Other networks have also included sexual contacts[5], instant messaging[6], Congressional committees[7], jazz musicians[8], blogs[9], airports[10], and rappers [11]. Several review articles have highlighted the main features and characteristics of complex networks [12, 13, 14]. One of the most studied and important features of a complex network as been found to be the average path length (or characteristic path), l that characterizes a network. It describes the average number of links that form the shortest path between any two nodes in the network. This property, more than any other, gives rise to what is known as ”small world” behavior. 1. Brief Properties of l In their seminal work that helped ignite research into small world phenomena, Watts and Strogatz [15] describe small world networks as those which are connected, where the number of nodes is much larger than the average degree per node, and the average path length scales with log n. Though random graphs can exhibit small world behavior, most graphs in the real world are not random and are often distinguished from random graphs by a relative high degree of clustering among nodes as measured by the clustering coefficients. Watts and Strogatz also described an estimate from random graph theory for the average path length of a random graph, which has become very useful for comparison with real networks,

Short Sea Shipping in the Atlantic Arc: A Spatial Shift-share Approach

This article presents a proposal for determine, given a port region, new SSS candidates between a node and its neighbours, considering the nautical distance between ports as a distance metric. For accomplishing that, classic, homothetic and spatial shift-share decompositions are applied to the 2006-2014 throughput dataset of the 57 European Atlantic Arc main ports. The conclusions show that along the Atlantic facade of the Iberian Peninsula (Portuguese and Galician region - Spanish-ports), and for some Irish sea positions, there are growing nodes with great potential for keep their throughput increasing, in terms of inner competitiveness or by establishing new SSS services between neighbour positions. Another Atlantic Arc ports, affected by the crisis, also appear with good recovering chances based in the setting up of new SSS services.