The ‘de-territorialisation of closeness’ - a typology of international successful R&D projects involving cultural and geographic proximity

Although there is a considerable amount of empirical evidence on inter-firm collaborations within technology-based industries, there are only a few works concerned with R&D cooperation by low-tech firms, especially SMEs. Providing further and new evidence based on a recently built database of CRAFT projects, this study analyzes the relationship between technology and proximity in international R&D networks using Homogeneity Analysis by Means of Alternating Least Squares (HOMALS) and statistical cluster techniques. The resulting typology of international cooperative R&D projects highlights that successful international cooperative R&D projects are both culturally/geographically closer and distant. Moreover, and quite interestingly, geographically distant projects are technologically more advanced whereas those located near each other are essentially low tech. Such evidence is likely to reflect the tacit-codified knowledge debate boosted recently by the ICT “revolution” emphasized by the prophets of the “Death of Distance” and the “End of Geography”.Research and Development (R&D); proximity; SMEs

Exchange Rate Mean Reversion within a Target Zone: Evidence from a Country on the Periphery of the ERM

The aim of this study is to assess to what extent the Portuguese participation in the European Monetary System (EMS) has been characterized by mean reverting behaviour, as predicted by the exchange rate target zone model developed by Krugman (1991). For this purpose, a new class of mean reversion tests is introduced. The empirical analysis of mean reversion in the Portuguese exchange rate shows that most of the traditional unit root and stationarity tests point to the nonstationarity of the exchange rate within the band. However, using a set of variance-ratio tests, it was possible to detect the presence of a martingale difference sequence. This suggests that the Portuguese foreign exchange market has functioned efficiently, allowing us to conclude that the adoption of an exchange rate target zone regime has contributed decisively to the creation of the macroeconomic stability conditions necessary for the participation of Portugal in the euro area.difference sequence, mean reversion, stationarity, target zones and unit roots

Twenty years into the new millennium: How integrated is Mathematics, Physics and Computer Science at secondary school level?

Twenty years into the millennium, the world has been confronted with a pandemic that has had an immeasurable impact on the workplace, learning environment and related technologies. Technology and technological advancements are founded on three disciplines, namely Physics, Mathematics and Computer Science. Internationally, an integration of the curricula of these disciplines are promoted in the education space, as an effective way to achieve 21st century capabilities that lately includes computational thinking. This study explores the changes in the content and alignment of the three subjects in the South African secondary school system from an interdisciplinary framework perspective. Textbooks, curriculum documents and planning calendars provided the information for the content analysis. The content in Physics and Mathematics have remained basically the same, with a few topics removed from Physics and some added to Mathematics. Information Technology has replaced Computer Science, with significant changes in content in alignment with developments in computing technology. No clear indication of an alignment between the disciplines could be found, which, to a certain extent, puts South Africa outside the international frame. The basic education system appears to run an assessment-driven curriculum in Mathematics, Physical Sciences and Information Technology. This system produces poor results and seemingly does not allow for interdisciplinary skills development

Compressive sensing adaptation for polynomial chaos expansions

Basis adaptation in Homogeneous Chaos spaces rely on a suitable rotation of the underlying Gaussian germ. Several rotations have been proposed in the literature resulting in adaptations with different convergence properties. In this paper we present a new adaptation mechanism that builds on compressive sensing algorithms, resulting in a reduced polynomial chaos approximation with optimal sparsity. The developed adaptation algorithm consists of a two-step optimization procedure that computes the optimal coefficients and the input projection matrix of a low dimensional chaos expansion with respect to an optimally rotated basis. We demonstrate the attractive features of our algorithm through several numerical examples including the application on Large-Eddy Simulation (LES) calculations of turbulent combustion in a HIFiRE scramjet engine.Comment: Submitted to Journal of Computational Physic

Public-Private Partnerships and the Promotion of Collective Entrepreneurship

Public-private partnerships (PPP) are a recent instrument for social and economic development policies. Within the framework of competitiveness policy, PPP are an adequate instrument to promote collective entrepreneurship. Through this instrument, some market failures can be overcome and a better provision of strategic services can be afforded to firms. Also, PPP can be able to promote co-ordination between public and private partners and lead to specific innovative networks. PPP correspond to a more decentralised policy and they are supposed to increase focus and effectiveness and to involve agencies that are closer to firms and that have a more narrow range of objectives. In this contribution, we analyse the pattern of the so-called partnerships projects, approved between 2000 and the 30th june of 2003 in the framework of the Portuguese Operational Program for the Economy. By using HOMALS and K-means cluster analysis, we were able to characterise PPP and to identify typical clusters for the PPP projects. On one hand, the results show that policy decentralization brought by partnerships has promoted or reinforced a more specialized institutional framework (mainly national, sectoral or regional entrepreneurial associations). But, on the other hand, PPP had a small impact in the promotion of specific networks and/or in innovation. Collective entrepreneurship induced by PPP instrument has presented a clear bias toward the provision of services that have a public or semi-public nature, by the fact that firms that can use these services are in a large number (all the firms of a sub sector or even larger universes). But technological projects and/or projects addressed to specific networks of firms were very few. In particular, the impact of PPP on structural change seems to have been short.Public-private partnerships; Competitiveness policy; Entrepreneurship; Collective entrepreneurship

Mining climate data for shire level wheat yield predictions in Western Australia

Climate change and the reduction of available agricultural land are two of the most important factors that affect global food production especially in terms of wheat stores. An ever increasing world population places a huge demand on these resources. Consequently, there is a dire need to optimise food production. Estimations of crop yield for the South West agricultural region of Western Australia have usually been based on statistical analyses by the Department of Agriculture and Food in Western Australia. Their estimations involve a system of crop planting recommendations and yield prediction tools based on crop variety trials. However, many crop failures arise from adherence to these crop recommendations by farmers that were contrary to the reported estimations. Consequently, the Department has sought to investigate new avenues for analyses that improve their estimations and recommendations. This thesis explores a new approach in the way analyses are carried out. This is done through the introduction of new methods of analyses such as data mining and online analytical processing in the strategy. Additionally, this research attempts to provide a better understanding of the effects of both gradual variation parameters such as soil type, and continuous variation parameters such as rainfall and temperature, on the wheat yields. The ultimate aim of the research is to enhance the prediction efficiency of wheat yields. The task was formidable due to the complex and dichotomous mixture of gradual and continuous variability data that required successive information transformations. It necessitated the progressive moulding of the data into useful information, practical knowledge and effective industry practices. Ultimately, this new direction is to improve the crop predictions and to thereby reduce crop failures. The research journey involved data exploration, grappling with the complexity of Geographic Information System (GIS), discovering and learning data compatible software tools, and forging an effective processing method through an iterative cycle of action research experimentation. A series of trials was conducted to determine the combined effects of rainfall and temperature variations on wheat crop yields. These experiments specifically related to the South Western Agricultural region of Western Australia. The study focused on wheat producing shires within the study area. The investigations involved a combination of macro and micro analyses techniques for visual data mining and data mining classification techniques, respectively. The research activities revealed that wheat yield was most dependent upon rainfall and temperature. In addition, it showed that rainfall cyclically affected the temperature and soil type due to the moisture retention of crop growing locations. Results from the regression analyses, showed that the statistical prediction of wheat yields from historical data, may be enhanced by data mining techniques including classification. The main contribution to knowledge as a consequence of this research was the provision of an alternate and supplementary method of wheat crop prediction within the study area. Another contribution was the division of the study area into a GIS surface grid of 100 hectare cells upon which the interpolated data was projected. Furthermore, the proposed framework within this thesis offers other researchers, with similarly structured complex data, the benefits of a general processing pathway to enable them to navigate their own investigations through variegated analytical exploration spaces. In addition, it offers insights and suggestions for future directions in other contextual research explorations

Mice in a labyrinth: Rapid learning, sudden insight, and efficient exploration

Animals learn certain complex tasks remarkably fast, sometimes after a single experience. What behavioral algorithms support this efficiency? Many contemporary studies based on two-alternative-forced-choice (2AFC) tasks observe only slow or incomplete learning. As an alternative, we study the unconstrained behavior of mice in a complex labyrinth and measure the dynamics of learning and the behaviors that enable it. A mouse in the labyrinth makes ~2000 navigation decisions per hour. The animal quickly discovers the location of a reward in the maze and executes correct 10-bit choices after only 10 reward experiences – a learning rate 1000-fold higher than in 2AFC experiments. Many mice improve discontinuously from one minute to the next, suggesting moments of sudden insight about the structure of the labyrinth. The underlying search algorithm does not require a global memory of places visited and is largely explained by purely local turning rules