Abstract
Many tasks dealing with temporal data, such as interactive browse through temporal datasets, require intensive retrieval from the database. Depending on the user's task, the data retrieved may be too large to fit in the local memory. Even if it fits, the time taken to retrieve the data may compromise user interaction. This work proposes a method, TravelLight, which improves interactive traveling across very large temporal datasets by exploring the temporal consistency of data items. The proposed method consists of two algorithms: the data retrieval and the memory management algorithm, both contributing to improve memory usage and, most important, to reduce the turnaround time. Results are reported concerning experiments with a temporally linear navigation across two datasets of one million items, which differ in the average time span of items. With the obtained results it is possible to conclude that the proposed method reduces turnaround time thus enhancing the response of interactive tasks over very large temporal datasets.

Abstract
Evolutionary Algorithms (EA) approach differently from nature the genotype - phenotype relationship, and this view is a recurrent issue among researchers. Recently, some researchers have started exploring computationally the new comprehension of the multitude of regulatory mechanisms that are fundamental in both processes of inheritance and of development in natural systems, by trying to include those mechanisms in the EAs. One of the first successful proposals was the Artificial Regulatory Network (ARN) model. Soon after some variants of the ARN, including different improvements over the base model, were tested. In this paper, we combine two of those alternatives, demonstrating experimentally how the resulting model can deal with complex problems, including those that have multiple outputs. The efficacy and efficiency of this variant are tested experimentally using two benchmark problems that show how we can evolve a controller or an artificial artist.

Abstract
A large number of studies have emphasized the spatial proximity of economic activity and its relation to the spatiality of knowledge creation in various types of connections. Far less attention has been paid to the understanding of the determinants of 'cultural' and geographical proximity in international R&D cooperation projects involving SMEs and the role of the quality of the Regional Innovation System (RIS). Using a database of completed European Cooperative Research projects, we conclude that: 1) technologically more complex projects are more likely to involve 'culturally' and geographically distant partners; 2) RIS related variables determine 'cultural' proximity but not geographical proximity; 3) at first sight surprisingly, international cooperation projects involving the 1st promoters of innovation-led regions (high patent propensity and high human capital levels) are culturally more distant. © Universidad Alberto Hurtado, Facultad de Economía y Negocios.

Abstract
Critical monitoring applications can use wireless sensor networks to transport delay sensitive data. This data may demand bounded delays in order to be considered useful by the receiver. In these cases, an accurate and real-time estimation of the end-to-end delay could be used to anticipate the data usefulness prior to sending it. A novel real-time and end-to-end delay estimation mechanism is proposed in this paper, which considers processing times and two new RPL metrics. Results show that our proposal is more accurate than the ETT-based solution for delay estimation, and it does not significantly degrade the network performance.

Abstract
Managing perishability may represent a remarkable problem in supply chain management of a varied set of industries. In fact, perishability can influence, for example, productivity or customer service and it may happen to occur in one or more processes throughout the supply chain. In this paper a review on planning models that handle perishability issues in production and distribution is conducted. The contribution of this paper is three-fold. First, a new framework for classifying perishability models based on multiple process features is presented. Second, it draws the community attention to the importance of managing perishability in many different industries' supply chains by showing its relevance and by reviewing the literature related to production and distribution planning. Finally, it points towards research opportunities so far not addressed by the research community in this challenging field.

Abstract
Traditional approaches to virtual archaeology include dealing with research methods to capture information from heritage sites, creating models out of that information and how to present them to the public; these are intense technical procedures which might be too costly for some types of history or heritage-based projects. Virtual worlds allowed new types of models of/for heritage sites to be produced and disseminated at a fraction of the cost.Second Life®, and its open source counterpart, OpenSimulator, are virtual world platforms with user-generated content. 3D models are created in real time and instantly rendered for all visitors. This allows amateurs and researchers create their own virtual archaeology projects easily and with few costs, and to have the resulting models immediately available to a vast community of users. This article presents an overview of four different approaches to virtual archaeology projects that are present in these platforms and that have been publicly discussed and analyzed; in particular, the last type shows a novel approach to virtual archaeology which is not found in other platforms, and explains how researchers have managed to extend the concept to new areas and develop methodologies to incorporate the validation of historical accuracy to encompass these areas.