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The SARS-CoV-2 pandemic has highlighted the need for improved technologies to help control the spread of contagious pathogens. While rapid point-of-need testing plays a key role in strategies to rapidly identify and isolate infectious patients, current test approaches have significant shortcomings related to assay limitations and sample type. Direct quantification of viral shedding in exhaled particles may offer a better rapid testing approach, since SARS-CoV-2 is believed to spread mainly by aerosols. It assesses contagiousness directly, the sample is easy and comfortable to obtain, sampling can be standardized, and the limited sample volume lends itself to a fast and sensitive analysis. In view of these benefits, we developed and tested an approach where exhaled particles are efficiently sampled using inertial impaction in a micromachined silicon chip, followed by an RT-qPCR molecular assay to detect SARS-CoV-2 shedding. Our portable, silicon impactor allowed for the efficient capture (>85%) of respiratory particles down to 300 nm without the need for additional equipment. We demonstrate using both conventional off-chip and in-situ PCR directly on the silicon chip that sampling subjects' breath in less than a minute yields sufficient viral RNA to detect infections as early as standard sampling methods. A longitudinal study revealed clear differences in the temporal dynamics of viral load for nasopharyngeal swab, saliva, breath, and antigen tests. Overall, after an infection, the breath-based test remains positive during the first week but is the first to consistently report a negative result, putatively signalling the end of contagiousness and further emphasizing the potential of this tool to help manage the spread of airborne respiratory infections. ispartof: BIOSENSORS & BIOELECTRONICS vol:217 ispartof: location:England status: published

The SARS-CoV-2 pandemic has highlighted the need for improved technologies to help control the spread of contagious pathogens. While rapid point-of-need testing plays a key role in strategies to rapidly identify and isolate infectious patients, a cornerstone for any disease-control strategy, current test approaches have significant shortcomings related to assay limitations and sample type. Direct quantification of viral shedding in exhaled particles may offer a better rapid testing approach, since SARS-CoV-2 is believed to spread mainly by aerosols. It potentially measures contagiousness directly, the sample is easy to obtain, its production can be standardized between patients, and the limited sample volume lends itself to a fast and sensitive analysis. In view of these benefits, we developed and tested an approach where exhaled particles are efficiently sampled using inertial impaction in a micromachined silicon chip, followed by an in-situ RT-qPCR molecular assay to detect SARS-CoV-2 shedding. We demonstrate that sampling subjects using a one-minute breathing protocol, yields sufficient viral RNA to detect infections with a sensitivity comparable to standard sampling methods. A longitudinal study revealed clear differences in the temporal dynamics of viral load for nasopharyngeal swab, saliva, breath, and antigen tests. Overall, after an infection, the breath-based test is the first to consistently report a negative result, putatively signaling the end of contagiousness and further emphasizing the potential of this tool to help manage the spread of airborne respiratory infections.

This paper investigates the opportunities of deploying distributed sensors within the manufacturing environmentof a large scale automobile plant using energy harvesting techniques. Measurements were taken in three domainsat the plant in order to characterize ambient energy. Due to the location of the plant, the RF power density forradio access technologies present varied between -127 dBm/cm 2 and -113 dBm/cm 2 . The maximum temperaturedi erence measured within accessible distance from machine parts on the production lines surveyed was 10 C.Indoor lighting was dominant at the plant via uorescent tubes, with average irradiance of 1 W/m 2 . The resultsobtained from this measurement campaign showed that indoor lighting was the most suitable ambient source forenergy harvesting.Keywords: Energy Harvesting, RF power density, temperature, light, measurement, factory 1. INTRODUCTION In manufacturing plants today, maintenance of critical assets is typically done via condition monitoring. Indus-trial monitoring systems such as the NI CompactRIO, depend on a large number of sensor inputs measuringvarious parameters on the shop oor (for example temperature, vibration, rotation, and resource usage). Inorder to operate a robust maintenance network, it is essential that these sensors are self-sustainable during theirlifetime. Conventional sensors networks (such as controller area networks) which have been used in industry areeither directly wired or battery powered, causing signi cant installation or retro t cost or in extreme cases areresponsible for failure