Knowledge gaps that hamper prevention and control of Mycobacterium avium subspecies paratuberculosis infection

In the last decades, many regional and country‐wide control programmes for Johne's disease (JD) were developed due to associated economic losses, or because of a possible association with Crohn's disease. These control programmes were often not successful, partly because management protocols were not followed, including the introduction of infected replacement cattle, because tests to identify infected animals were unreliable, and uptake by farmers was not high enough because of a perceived low return on investment. In the absence of a cure or effective commercial vaccines, control of JD is currently primarily based on herd management strategies to avoid infection of cattle and restrict within‐farm and farm‐to‐farm transmission. Although JD control programmes have been implemented in most developed countries, lessons learned from JD prevention and control programmes are underreported. Also, JD control programmes are typically evaluated in a limited number of herds and the duration of the study is less than 5 year, making it difficult to adequately assess the efficacy of control programmes. In this manuscript, we identify the most important gaps in knowledge hampering JD prevention and control programmes, including vaccination and diagnostics. Secondly, we discuss directions that research should take to address those knowledge gaps.http://wileyonlinelibrary.com/journal/tbed2019-05-01hj2018Veterinary Tropical Disease

Interaction for Immersive Analytics

International audienceIn this chapter, we briefly review the development of natural user interfaces and discuss their role in providing human-computer interaction that is immersive in various ways. Then we examine some opportunities for how these technologies might be used to better support data analysis tasks. Specifically, we review and suggest some interaction design guidelines for immersive analytics. We also review some hardware setups for data visualization that are already archetypal. Finally, we look at some emerging system designs that suggest future directions

Combining Automated and Interactive Visual Analysis of Biomechanical Motion Data

Abstract. We present a framework for combining automated and interactive visual analysis techniques for use on high-resolution biomechanical data. Analyzing the complex 3D motion of, e.g., pigs chewing or bats flying, can be enhanced by providing investigators with a multi-view interface that allows interaction across multiple modalities and representations. In this paper, we employ nonlinear dimensionality reduction to automatically learn a low-dimensional representation of the data and hierarchical clustering to learn patterns inherent within the motion segments. Our multi-view framework allows investigators to simultaneously view a low-dimensional embedding, motion segment clustering, and 3D visual representation of the data side-by-side. We describe an application to a dataset containing thousands of frames of high-speed, 3D motion data collected over multiple experimental trials.