The Virtual Skeleton Database: An Open Access Repository for Biomedical Research and Collaboration

Background: Statistical shape models are widely used in biomedical research. They are routinely implemented for automatic image segmentation or object identification in medical images. In these fields, however, the acquisition of the large training datasets, required to develop these models, is usually a time-consuming process. Even after this effort, the collections of datasets are often lost or mishandled resulting in replication of work. Objective: To solve these problems, the Virtual Skeleton Database (VSD) is proposed as a centralized storage system where the data necessary to build statistical shape models can be stored and shared. Methods: The VSD provides an online repository system tailored to the needs of the medical research community. The processing of the most common image file types, a statistical shape model framework, and an ontology-based search provide the generic tools to store, exchange, and retrieve digital medical datasets. The hosted data are accessible to the community, and collaborative research catalyzes their productivity. Results: To illustrate the need for an online repository for medical research, three exemplary projects of the VSD are presented: (1) an international collaboration to achieve improvement in cochlear surgery and implant optimization, (2) a population-based analysis of femoral fracture risk between genders, and (3) an online application developed for the evaluation and comparison of the segmentation of brain tumors. Conclusions: The VSD is a novel system for scientific collaboration for the medical image community with a data-centric concept and semantically driven search option for anatomical structures. The repository has been proven to be a useful tool for collaborative model building, as a resource for biomechanical population studies, or to enhance segmentation algorithms.

Building up and sharing knowledge for better decision making on soil and water conservation in a changing mountain environment - the WOCAT experience

For successful implementation of any soil and water conservation (SWC) or sustainable land management practice, it is essential to have a proper understanding of the natural and human environment in which these practices are applied. This understanding should be based on comprehensive information concerning the application of the technologies and not solely on the technological details. The World Overview of Conservation Approaches and Technologies (WOCAT) is documenting and evaluating SWC practices worldwide, following a standardised methodology that facilitates exchange and comparison of experiences. Notwithstanding this standardisation, WOCAT allows flexible use of its outputs, adapted to different users and different environments. WOCAT offers a valuable tool for evaluating the strengths and weaknesses of SWC practices and their potential for application in other areas. Besides collecting a wealth of information, gaps in available information are also exposed, showing the need for more research in those fields. Several key issues for development- oriented research have been identified and are being addressed in collaboration with a research programme for mitigating syndromes of global change.

Firm Building and Entrepreneurship in Second-Tier High-Tech Regions

This paper examines how a second-tier high-technology region leveraged corporate assets—mostly from transnational firms—in building a knowledge-based economy. The paper reviews how firm building and entrepreneurship influence the evolution of a peripheral regional economy. Using a case study of Boise, Idaho (the US), the research highlights several important sources of entrepreneurship. Entrepreneurial firm formation is closely linked with a region's ability to grow incubator organizations, particularly innovative firms. These innovative firms provide the training ground for entrepreneurs. Firms, however, differ and the ways in which firm building activities influence regional entrepreneurship depend on firm strategy and organization. Thus, second-tier high-tech regions in the US are taking a different path than their well-known counterparts such as Silicon Valley or Route 128 around Boston.

Adapting to climate change through sustainable land management: experiences of a pilot project in Tajikistan

Tajikistan is particularly exposed to the risks of climate change. Its widely degraded landscapes are badly prepared to cope with changes in precipitation patterns, increased temperatures, droughts, and the spread of pests and disease. Sustainable land management (SLM) provides a “basket of opportunities” to address these challenges, particularly for increasing land productivity, improving livelihoods, and protecting ecosystems. Within the Pilot Program for Climate Resilience (PPCR) in Tajikistan 70 SLM technologies and approaches on how to implement SLM were documented with the World Overview of Conservation Approaches and Technologies (WOCAT ) tools in 2011. For this purpose a climate change adaptation module was developed and tested in order to enhance the understanding about climate change resilience of SLM practices and community workshops conducted to on adaptation mechanisms by rural communities in Tajikistan. The analysis came up with four guiding principles for applying SLM for adapting to climate change: 1. Diversification of land use technologies and farm incomes; 2. Intensification of use of natural resources; 3. Expansion of highly productive land use technologies; 4. Protection of land and livelihoods from extreme weather events. Furthermore, SLM must be up-scaled from isolated plots to entire zones or landscapes and the project developed the concept of three concentric villages zones, the in-, near- and off-village zones. Land users, advisors, and decision- and policy makers face the task of finding management practices that best suit site-specific conditions. This task is most efficiently addressed in collaborative effort, and building up and managing a respective knowledge platform.

Can the green economy enhance sustainable mountain development? The potential role of awareness building

Mountain socio-ecological systems produce valuable but complex ecosystem services resulting from biomes stratified by altitude and gravity. These systems are often managed and shaped by smallholders whose marginalization is exacerbated by uncertainties and a lack of policy attention. Human–environment interfaces in mountains hence require holistic policies. We analyse the potential of the Global Mountain Green Economy Agenda (GMGEA) in building awareness and thus prompting cross-sectoral policy strategies for sustainable mountain development. Considering the critique of the green economy presented at the Rio + 20 conference, we argue that the GMGEA can nevertheless structure knowledge and inform regional institutions about the complexity of mountain socio-ecological systems, a necessary pre-condition to prompt inter-agency collaboration and cross-sectoral policy formulation. After reviewing the content of the GMGEA, we draw on two empirical cases in the Pakistani and Nepali Himalayas. First, we show that lack of awareness has led to a sequence of fragmented interventions with unanticipated, and unwanted, consequences for communities. Second, using a green economy lens, we show how fragmentation could have been avoided and cross-sectoral policies yielded more beneficial results. Project fragmentation reflects disconnected or layered policies by government agencies, which inherently keep specialized agendas and have no incentive to collaborate. Awareness makes agencies more likely to collaborate and adopt cross-sectoral approaches, allowing them to target more beneficiaries, be more visible, and raise more funds. Nevertheless, we also identify four factors that may currently still limit the effect of the GMGEA: high costs of inter-agency collaboration, lack of legitimacy of the green economy, insufficiently-secured smallholder participation, and limited understanding of the mechanisms through which global agendas influence local policy.

Firm-level strategic orientation and performance: a synthesis and extension of the knowledge base on entrepreneurial, market and learning orientation

Should a firm stay focused or should it rather adopt a broader strategic perspective? This dissertation summarizes and extends the existing knowledge base on entrepreneurial, market, and learning orientation. Building on multiple theoretical perspectives, empirical evidence from prior studies, as well as on survey and archival data collected in two economic contexts, performance effects from individual orientations, their dimensions and combinations are explored. Results reveal that the three strategic orientations are highly interrelated and that their relationship to firm performance is more complex than previously assumed.

Constitutionality: Conditions for Crafting Local Ownership of Institution-Building Processes

This article presents constitutionality as a new approach for analyzing bottom-up institution-building processes emphasizing local perceptions and local agency in common pool resource management. Using four case studies—fisheries in Zambia; pasture and forestry in Mali; fisheries in Indonesia; forestry in Bolivia—this approach analyzes examples of local institution building differing from top-down imposed participation. Our analysis highlights six components of constitutionality: emic perceptions of the need for new institutions, participatory processes of negotiation, preexisting institutions as a basis for institution building, outside catalyzing agents, recognition of local knowledge, and higher level acknowledgment of the new institutions.

Building the View Graph of a Category by Exploiting Image Realism

We propose a weakly supervised method to arrange images of a given category based on the relative pose between the camera and the object in the scene. Relative poses are points on a sphere centered at the object in a given canonical pose, which we call object viewpoints. Our method builds a graph on this sphere by assigning images with similar viewpoint to the same node and by connecting nodes if they are related by a small rotation. The key idea is to exploit a large unlabeled dataset to validate the likelihood of dominant 3D planes of the object geometry. A number of 3D plane hypotheses are evaluated by applying small 3D rotations to each hypothesis and by measuring how well the deformed images match other images in the dataset. Correct hypotheses will result in deformed images that correspond to plausible views of the object, and thus will likely match well other images in the same category. The identified 3D planes are then used to compute affinities between images related by a change of viewpoint. We then use the affinities to build a view graph via a greedy method and the maximum spanning tree.