Low-cost sensors are effective for measuring the mass concentration of ambient aerosols and secondhand smoke in homes, but their use at concentrations relevant to occupational settings has not been demonstrated. We measured the concentrations of four aerosols (salt, Arizona road dust, welding fume, and diesel exhaust) with three types of low-cost sensors (a DC1700 from Dylos and two commodity sensors from Sharp), an aerosol photometer, and reference instruments at concentrations up to 6500 μg/m3. Raw output was used to assess sensor precision and develop equations to compute mass concentrations. EPA and NIOSH protocols were used to assess the mass concentrations estimated with low-cost sensors compared to reference instruments. The detection efficiency of the DC1700 ranged from 0.04% at 0.1 μm to 108% at 5 μm, as expected, although misclassification of fine and coarse particles was observed. The raw output of the DC1700 had higher precision (lower coefficient of variation, CV = 7.4%) than that of the two sharp devices (CV = 25% and 17%), a finding attributed to differences in manufacturer calibration. Aerosol type strongly influenced sensor response, indicating the need for on-site calibration to convert sensor output to mass concentration. Once calibrated, however, the mass concentration estimated with low-cost sensors was highly correlated with that of reference instruments (R2=0.99). These results suggest that the DC1700 and Sharp sensors are useful in estimating aerosol mass concentration for aerosols at concentrations relevant to the workplace.

The combination of PVS impression method and press fabrication technique produced the most accurate 3D and 2D marginal fits.

Heterogeneity in healthcare worker contact patterns dramatically affects disease diffusion. Our findings should inform future infection control interventions and encourage the application of social network analysis to study disease transmission in healthcare settings.

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[1] The Life in the Atacama project investigated the regional distribution of life and habitats in the Atacama Desert of Chile. We sought to create biogeologic maps through survey traverses across the desert using a rover carrying biologic and geologic instruments. Elements of our science approach were to: Perform ecological transects from the relatively wet coastal range to the arid core of the desert; use converging evidence from science instruments to reach conclusions about microbial abundance; and develop and test exploration strategies adapted to the search of scattered surface and shallow subsurface microbial oases. Understanding the ability of science teams to detect and characterize microbial life signatures remotely using a rover became central to the project. Traverses were accomplished using an autonomous rover in a method that is technologically relevant to Mars exploration. We present an overview of the results of the 2003, 2004, and 2005 field investigations. They include: The confirmed identification of microbial habitats in daylight by detecting fluorescence signals from chlorophyll and dye probes; the characterization of geology by imaging and spectral measurement; the mapping of life along transects; the characterization of environmental conditions; the development of mapping techniques including homogeneous biological scoring and predictive models of habitat location; the development of exploration strategies adapted to the search for life with an autonomous rover capable of up to 10 km of daily traverse; and the autonomous detection of life by the rover as it interprets observations on-the-fly and decides which targets to pursue with further analysis.

While substantial concerns were expressed by all types of HCP, participants' recommendations for effective implementation of electronic oversight technologies for hand hygiene monitoring included addressing accuracy issues before implementation and transparent communication with frontline HCP about the intended use of the data.

Objective Evaluate the effectiveness of augmented reality (AR) cues in improving driving safety in elderly drivers who are at increased crash risk due to cognitive impairments. Background Cognitively challenging driving environments pose a particular crash risk for elderly drivers. AR cueing is a promising technology to mitigate risk by directing driver attention to roadway hazards. This study investigates whether AR cues improve or interfere with hazard perception in elderly drivers with age-related cognitive decline. Methods Twenty elderly (Mean= 73 years, SD= 5 years), licensed drivers with a range of cognitive abilities measured by a speed of processing (SOP) composite participated in a one-hour drive in an interactive, fixed-base driving simulator. Each participant drove through six, straight, six-mile-long rural roadway scenarios following a lead vehicle. AR cues directed attention to potential roadside hazards in three of the scenarios, and the other three were uncued (baseline) drives. Effects of AR cueing were evaluated with respect to: 1) detection of hazardous target objects, 2) interference with detecting nonhazardous secondary objects, and 3) impairment in maintaining safe distance behind a lead vehicle. Results AR cueing improved the detection of hazardous target objects of low visibility. AR cues did not interfere with detection of nonhazardous secondary objects and did not impair ability to maintain safe distance behind a lead vehicle. SOP capacity did not moderate those effects. Conclusion AR cues show promise for improving elderly driver safety by increasing hazard detection likelihood without interfering with other driving tasks such as maintaining safe headway.