Technology transfer of renewable energy for rural development: historical evolution and lessons of experience from the model WWP

Technology transfer (TT) in the area of renewable energy (RE) throughout history has been an important tool for rural development (RD). Initially, the TT has been conceptualized as the purchase or donation of machinery from first world countries - without any consideration of staff training and contextual conditions for the adaptation of technology to the needs of the country. Various researches have revealed the existence of different approaches to planning the TT of RE, demonstrating the high complexity of projects from the social and contextual dimension. This paper addresses the conceptual evolution of the TT of RE for RD, examining its different periods considered for three criteria: historical events occurred, the role of stakeholders and changing objectives for the TT of RE for RD. For the conceptual analysis of changes the model Working With People (WWP) is used for planning and project management of high social complexity in RD. The analysis defines the existence of four historical periods in the TT of RE and synthesizes the lessons of experience from the three dimensions (ethical-social, technical-entrepreneurial, and political-contextual) of the WWP model.

Development of mathematical models to elaborate strategies, select alternatives and development of plans for adaptation of communities to climate change in different geographical areas including costs to implement it.

There is evidence that the climate changes and that now, the change is influenced and accelerated by the CO2 augmentation in atmosphere due to combustion by humans. Such ?Climate change? is on the policy agenda at the global level, with the aim of understanding and reducing its causes and to mitigate its consequences. In most countries and international organisms UNO (e.g. Rio de Janeiro 1992), OECD, EC, etc . . . the efforts and debates have been directed to know the possible causes, to predict the future evolution of some variable conditioners, and trying to make studies to fight against the effects or to delay the negative evolution of such. The Protocol of Kyoto 1997 set international efforts about CO2 emissions, but it was partial and not followed e.g. by USA and China . . . , and in Durban 2011 the ineffectiveness of humanity on such global real challenges was set as evident. Among all that, the elaboration of a global model was not boarded that can help to choose the best alternative between the feasible ones, to elaborate the strategies and to evaluate the costs, and the authors propose to enter in that frame for study. As in all natural, technological and social changes, the best-prepared countries will have the best bear and the more rapid recover. In all the geographic areas the alternative will not be the same one, but the model must help us to make the appropriated decision. It is essential to know those areas that are more sensitive to the negative effects of climate change, the parameters to take into account for its evaluation, and comprehensive plans to deal with it. The objective of this paper is to elaborate a mathematical model support of decisions, which will allow to develop and to evaluate alternatives of adaptation to the climatic change of different communities in Europe and Latin-America, mainly in especially vulnerable areas to the climatic change, considering in them all the intervening factors. The models will consider criteria of physical type (meteorological, edaphic, water resources), of use of the ground (agriculturist, forest, mining, industrial, urban, tourist, cattle dealer), economic (income, costs, benefits, infrastructures), social (population), politician (implementation, legislation), educative (Educational programs, diffusion) and environmental, at the present moment and the future. The intention is to obtain tools for aiding to get a realistic position for these challenges, which are an important part of the future problems of humanity in next decades.

Desing and development of a robotic platform for the evaluation of search algorithms

Plant diseases represent a major economic and environmental problem in agriculture and forestry. Upon infection, a plant develops symptoms that affect different parts of the plant causing a significant agronomic impact. As many such diseases spread in time over the whole crop, a system for early disease detection can aid to mitigate the losses produced by the plant diseases and can further prevent their spread [1]. In recent years, several mathematical algorithms of search have been proposed [2,3] that could be used as a non-invasive, fast, reliable and cost-effective methods to localize in space infectious focus by detecting changes in the profile of volatile organic compounds. Tracking scents and locating odor sources is a major challenge in robotics, on one hand because odour plumes consists of non-uniform intermittent odour patches dispersed by the wind and on the other hand because of the lack of precise and reliable odour sensors. Notwithstanding, we have develop a simple robotic platform to study the robustness and effectiveness of different search algorithms [4], with respect to specific problems to be found in their further application in agriculture, namely errors committed in the motion and sensing and to the existence of spatial constraints due to land topology or the presence of obstacles.

Evolution and implementation of CDIO initiatives at ETSII-UPM

The School of Industrial Engineering at Universidad Politécnica de Madrid (ETSII-UPM) has been promoting student-centred teaching-learning activities, according to the aims of the Bologna Declaration, well before the official establishment of the European Area of Higher Education. Such student-centred teaching-learning experiences led us to the conviction that project based learning is rewarding, both for students and academics, and should be additionally promoted in our new engineering programmes, adapted to the Grade-Master structure. The level of commitment of our teachers with these activities is noteworthy, as the teaching innovation experiences carried out in the last ten years have led to the foundation of 17 Teaching Innovation Groups at ETSII-UPM, hence leading the ranking of teaching innovation among all UPM centres. Among interesting CDIO activities our students have taken part in especially complex projects, including the Formula Student, linked to the complete development of a competition car, and the Cybertech competition, aimed at the design, construction and operation of robots for different purposes. Additional project-based learning teamwork activities have been linked to toy design, to the development of medical devices, to the implementation of virtual laboratories, to the design of complete industrial installations and factories, among other activities detailed in present study. The implementation of Bologna process will culminate at ETSII-UPM with the beginning of the Master’s Degree in Industrial Engineering, in academic year 2014-15. The program has been successfully approved by the Spanish Agency for Accreditation (ANECA), with the inclusion of a set of subjects based upon the CDIO methodology denominated generally “INGENIA”, linked to the Spanish “ingeniar” (to provide ingenious solutions), also related etymologically in Spanish with “ingeniero”, engineer. INGENIA students will live through the complete development process of a complex product or system and there will be different kind of projects covering most of the engineering majors at ETSII-UPM.

First 20 years of DNDC: Model evolution and GRAMP.

The DNDC (DeNitrification and DeComposition) model was first developed by Li et al. (1992) as a rain event-driven process-orientated simulation model for nitrous oxide, carbon dioxide and nitrogen gas emissions from the agricultural soils in the U.S. Over the last 20 years, the model has been modified and adapted by various research groups around the world to suit specific purposes and circumstances. The Global Research Alliance Modelling Platform (GRAMP) is a UK-led initiative for the establishment of a purposeful and credible web-based platform initially aimed at users of the DNDC model. With the aim of improving the predictions of soil C and N cycling in the context of climate change the objectives of GRAMP are to: 1) to document the existing versions of the DNDC model; 2) to create a family tree of the individual DNDC versions; 3) to provide information on model use and development; and 4) to identify strengths, weaknesses and potential improvements for the model.