Vector-borne pathogens are known to alter the phenotypes of their primary hosts and vectors, with implications for disease transmission as well as ecology. Here we show that a plant virus, barley yellow dwarf virus, increases the surface temperature of infected host plants (by an average of 2°C), while also significantly enhancing the thermal tolerance of its aphid vector Rhopalosiphum padi (by 8°C). This enhanced thermal tolerance, which was associated with differential upregulation of three heat-shock protein genes, allowed aphids to occupy higher and warmer regions of infected host plants when displaced from cooler regions by competition with a larger aphid species, R. maidis. Infection thereby led to an expansion of the fundamental niche of the vector. These findings show that virus effects on the thermal biology of hosts and vectors can influence their interactions with one another and with other, non-vector organisms.

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a b s t r a c tWe present a parallel implementation of a histogram-based particle filter for object tracking on smart cameras based on SIMD processors. We specifically focus on parallel computation of the particle weights and parallel construction of the feature histograms since these are the major bottlenecks in standard implementations of histogram-based particle filters. The proposed algorithm can be applied with any histogram-based feature sets-we show in detail how the parallel particle filter can employ simple color histograms as well as more complex histograms of oriented gradients (HOG). The algorithm was successfully implemented on an SIMD processor and performs robust object tracking at up to 30 frames per second-a performance difficult to achieve even on a modern desktop computer.

Comprehensive Automation for Specialty Crops is a project focused on the needs of the specialty crops sector, with a focus on apples and nursery trees. The project's main thrusts are the integration of robotics technology and plant science; understanding and overcoming socio-economic barriers to technology adoption; and making the results available to growers and stakeholders through a nationwide outreach program. In this article, we present the results obtained and lessons learned in the first year of the project with a reconfigurable mobility infrastructure for autonomous farm driving. We then present sensor systems developed to enable three real-world agricultural applications-insect monitoring, crop load scouting, and caliper measurement-and discuss how they can be deployed autonomously to yield increased production efficiency and reduced labor costs.