In virtual environments, spatial discrepancies between visual and haptic scenes negatively impact user performance and experience. This paper shows how spatial discrepancies due to pose differences can occur in a haptic augmented virtuality system with an encountered-type haptic display. To mitigate this problem, we propose visual guidance, an algorithm that dynamically manipulates the visual scene to compensate for discrepancies. The effectiveness of this algorithm was verified in a pair of studies involving a button pressing task and spatial discrepancies between +/- 150 mm and +/- 40 degrees. Experimental results show that discrepant trials using the technique yield error rates and a number of speed peaks (representing the number of targeting movements) that are comparable to those attained in trials with zero spatial discrepancy. This result was also achieved without requiring a dedicated adaptation or training process, ensuring the algorithm can be used immediately by users. A pair of follow-up studies also indicates the algorithm has little impact on subjective ratings of simulator sickness, suggesting that sporadic use of the algorithm will not negatively affect user's experience of a virtual environment. We believe that the visual guidance algorithm presented in this paper can be used to create more useful and compelling experiences in various haptic training applications incorporating encountered-type haptic displays.

Field-grown strawberries, the environment of strawberry farms and fresh strawberries from marketplaces were examined for bacterial, viral, and protozoan pathogens. The presence of bacteria was determined using culture and real-time PCR (qPCR), presence of protozoa and viruses using qPCR and reverse transcription qPCR, respectively. The highest proportion of positivity was observed for Escherichia coli both in field and purchased strawberries (up to 48.6%). Finding of Cronobacter ranged from 0.6% to 9% both for field and market strawberries. The prevalence of other pathogens (Listeria monocytogenes, Giardia intestinalis, Cryptosporidium sp., and Norovirus) in strawberries was below 4.5%; HAV was not detected at all. Positivity of the environment was determined to be lower than 2.1% for all microorganisms, except for E. coli. The concentration of pathogens in most samples did not exceed 100 CFU/g using culture and 1.8 x 10(2) GE/g of strawberries or swabbing area 6.1 x 10(2) GE/mL or swabbing area of environmental samples using qPCR. All studied farms applied preventive measures such as drip irrigation, avoidance of organic fertilizers, and use of mulch foils or gloves for workers to decrease contamination of strawberries. Despite this, certain pathogens were found in fresh strawberries. Even at low concentrations, these pathogens can be a source of infection for consumers. Thus, their presence in strawberries is of particular significance as these are mostly consumed fresh and without any thermal processing. Practical Application Nonlegislatively monitored pathogens of bacterial, viral and parasitic origin were found in strawberries. Monitoring the presence of these pathogens in ready-to-eat food is therefore meaningful and important in terms of food safety, especially in relation to pathogens with low infectious dose (for example, viruses, parasites).