Reshaping Rural Extension: Learning for Sustainability (LforS): An Integrative and Learning-Based Advisory Approach for Rural Extension with Small-Scale Farmers

This publication offers concrete suggestions for implementing an integrative and learning-oriented approach to agricultural extension with the goal of fostering sustainable development. It targets governmental and non-governmental organisations, development agencies, and extension staff working in the field of rural development. The book looks into the conditions and trends that influence extension today, and outlines new challenges and necessary adaptations. It offers a basic reflection on the goals, the criteria for success and the form of a state-of-the-art approach to extension. The core of the book consists of a presentation of Learning for Sustainability (LforS), an example of an integrative, learning-oriented approach that is based on three crucial elements: stakeholder dialogue, knowledge management, and organizational development. Awareness raising and capacity building, social mobilization, and monitoring & evaluation are additional building blocks. The structure and organisation of the LforS approach as well as a selection of appropriate methods and tools are presented. The authors also address key aspects of developing and managing a learning-oriented extension approach. The book illustrates how LforS can be implemented by presenting two case studies, one from Madagascar and one from Mongolia. It addresses conceptual questions and at the same time it is practice-oriented. In contrast to other extension approaches, LforS does not limit its focus to production-related aspects and the development of value chains: it also addresses livelihood issues in a broad sense. With its focus on learning processes LforS seeks to create a better understanding of the links between different spheres and different levels of decision-making; it also seeks to foster integration of the different actors’ perspectives.

Virtual reality ultrasound imaging of the normal and abnormal fetal central nervous system

OBJECTIVES: In fetal ultrasound imaging, teaching and experience are of paramount importance to improve prenatal detection rates of fetal abnormalities. Yet both aspects depend on exposure to normal and, in particular, abnormal 'specimens'. We aimed to generate a number of simple virtual reality (VR) objects of the fetal central nervous system for use as educational tools. METHODS: We applied a recently proposed algorithm for the generation of fetal VR object movies to the normal and abnormal fetal brain and spine. Interactive VR object movies were generated from ultrasound volume data from normal fetuses and fetuses with typical brain or spine anomalies. Pathognomonic still images from all object movies were selected and annotated to enable recognition of these features in the object movies. RESULTS: Forty-six virtual reality object movies from 22 fetuses (two with normal and 20 with abnormal brains) were generated in an interactive display format (QuickTime) and key images were annotated. The resulting .mov files are available for download from the website of this journal. CONCLUSIONS: VR object movies can be generated from educational ultrasound volume datasets, and may prove useful for teaching and learning normal and abnormal fetal anatomy.