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Preventive measures to reduce infection are needed to combat the COVID-19 pandemic and prepare for a possible endemic phase. Current prophylactic vaccines are highly effective to prevent disease but lose their ability to reduce viral transmission as viral evolution leads to increasing immune escape. Long-term proactive public health policies must therefore complement vaccination with available nonpharmaceutical interventions aiming to reduce the viral transmission risk in public spaces. Here, we revisit the quantitative assessment of airborne transmission risk, considering asymptotic limits that considerably simplify its expression. We show that the aerosol transmission risk is the product of three factors: a biological factor that depends on the viral strain, a hydrodynamical factor defined as the ratio of concentration in viral particles between inhaled and exhaled air, and a face mask filtering factor. The short-range contribution to the risk, present both indoors and outdoors, is related to the turbulent dispersion of exhaled aerosols by air drafts and by convection (indoors), or by the wind (outdoors). We show experimentally that airborne droplets and CO 2 molecules present the same dispersion. As a consequence, the dilution factor, and therefore the risk, can be measured quantitatively using the CO 2 concentration, regardless of the room volume, the flow rate of fresh air, and the occupancy. We show that the dispersion cone leads to a concentration in viral particles, and therefore a short-range transmission risk, inversely proportional to the squared distance to an infected person and to the flow velocity. The aerosolization criterion derived as an intermediate result, which compares the Stokes relaxation time to the Lagrangian time-scale, may find application for a broad class of aerosol-borne pathogens and pollutants., (© The Author(s) 2022. Published by Oxford University Press on behalf of National Academy of Sciences.)

As an answer to alternative non-animal testing, biosensors dedicated to the ex vivo skin explants monitoring are a challenge to study physiological-like behavior and optimize new topical products. Because of the skin viscoelastic behavior, mechanical tests are commonly based on macroscopic measurement and give global descriptors of its state. Other techniques, including photoacoustic ones, are more focused on the molecular scale. There is a gap to fill in the mesoscopic range to get information about the microstructure of the skin. This article presents the proof-of-concept of a biosensor coupling a thickness shear-mode transducer with human skin explants kept in life-like state for a week. Thanks to a multifrequency analysis of the transducer impedance, this biosensor is able to monitor the viscoelastic properties of the skin. To extract the complex shear modulus and the microstructural evolutions, a mechanical model based on fractional calculus is used. As a preliminary results, the sensitivity of the sensor to probe the skin viscoelasticity in lifelike state and the impact of its culture medium are presented. A suitable microstructural coefficient is also extracted in order to identify mechanical breaches in the skin barrier after the application of peeling products., (Copyright © 2021 Elsevier B.V. All rights reserved.)

We have developed a specially designed sensor with its associated instrumentation using a so called acoustical near-field technique based on small resonating horns. Contrary to the conventional measuring devices used in the rheology industry, this sensor enables wide-range and continuous viscosity measurements, including liquid to solid material transition. The sensor is composed of a small piezoelectric element which enables the horn to resonate. Shear waves are generated by means of the thinner part of the sensor (dipped into the material) confining the acoustic field to the tip to ensure local measurements. The frequency is scanned across the resonating frequencies in order to perform these measurements with the maximum of speed and efficiency. The shear moduli G' and G'' of the material is deduced from the electrical impedance measurement at the resonance frequencies. In case of rapidly changing materials, such as quick setting cements or polyesters, we have developed a specific fast instrumentation based on the impulse response of the sensor, which realizes very fast measurements, typically 30 measurements per second. Modelization and experiments are reported.

Gelation is a complex reaction that transforms a liquid medium into a solid one: the gel. In gel state, some gel materials (DMAP) have the singular property to ring in an audible frequency range when a pulse is applied. Before the gelation point, there is no transmission of slow waves observed; after the gelation point, the speed of sound in the gel rapidly increases from 0.1 to 10 m/s. The time evolution of the speed of sound can be measured, in frequency domain, by following the frequency spacing of the resonance peaks from the Synchronous Detection (SD) measurement method. Unfortunately, due to a constant frequency sampling rate, the relative error for low speeds (0.1 m/s) is 100%. In order to maintain a low constant relative error, in the whole speed time evolution range, Chirp-Z Transform (CZT) is used. This operation transforms a time variant signal to a time invariant one using only a time dependant stretching factor (S). In the frequency domain, the CZT enables us to stretch each collected spectrum from time signals. The blind identification of the S factor gives us the complete time evolution law of the speed of sound. Moreover, this method proves that the frequency bandwidth follows the same time law. These results point out that the minimum wavelength stays constant and that it only depends on the gel.