PROLONGED FACIAL MASK WEAR IS A CONCERN FOR THE DEVELOPMENT OF DYSBIOTIC MICROBIOME

Facial masks are beauty products which composed of a facial mask paper and beauty solution. Silk contains the amino acid structure closest to the human skin, and has the skin-friendly, cosmetic and antibacterial functions, but the common method for making nonwoven facial mask paper is not suitable for silk. In this paper, the silkworm’s spinning path is intervened manually to obtain a smart silk facial mask paper (SMC) of controllable thickness, so that the sericin on the silk fiber is well preserved. In the experiment where the SMC is compared with the nonwoven 384-cuprammonium rayon facial mask paper (CRMC) which is the most widely used in the market, it is found that the ways of forming the two facial mask paper are completely different, and therefore the morphologies under SEM are obviously different. The thickness of the SMC is 0.183 mm and the areal weight of it is 38.0 g/m2. It is very close to the CRMC (0.187 mm, 38.4 g/m2). The porosity of the SMC is 84.0%, which is slightly lower than that of the CRMC (86.3%), but its pores are well distributed. Compared with the CRMC, the smart SMC has higher dry and wet strength, lower elongation, slightly lower air permeability and liquid entrainment rate, and better antibacterial performance.

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Critical Design Condensation Locations in Facial Masks

ASME 2010 Summer Bioengineering Conference, Parts A and B ◽

10.1115/sbc2010-19101 ◽

2010 ◽

Author(s):

A. M. Al-Jumaily

Keyword(s):

Heat Transfer ◽

Computer Simulation ◽

Dynamic Model ◽

Fluid Dynamic ◽

Condensation Rate ◽

Facial Mask ◽

Critical Design ◽

Life Threatening ◽

Mass And Heat Transfer

Facial masks are the main interface between patients and breathing supportive devices. Condensation in these masks causes serious breath disturbance which could be life threatening. Based on temperature-driven mass and heat transfer formulations, a computer simulation fluid dynamic model is developed to compute the condensation rate and locations of a typical breathing facial mask. Condensation measurements are taken to validate the model. The effects of mask geometry and shape on condensation are elaborated on.

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Use of Artificial Intelligence for Face Detection with Face Mask in Real Time to Control the Entrance to an Entity

International Journal of Emerging Technology and Advanced Engineering ◽

10.46338/ijetae1121_09 ◽

2021 ◽

Vol 11 (11) ◽

pp. 68-75

Author(s):

Enrique Lee Huamaní ◽

◽

Lilian Ocares Cunyarachi

Keyword(s):

Machine Learning ◽

Real Time ◽

Face Detection ◽

Face Mask ◽

Economic Activities ◽

Facial Mask ◽

The Face ◽

The Individual ◽

A Company ◽

Selection Of

Due to the pandemic caused by Covid-19, daily life has changed significantly. For this reason, biosecurity measures have been implemented to prevent the spread of the virus as an effective way to reactivate economic activities. In this sense, the present paper focuses on real-time face detection as a measure of control at the entrance to an entity, thus avoiding the spread of the virus while recognizing the identity of workers despite the use of masks and thus reducing the risk of entry of individuals outside the organization. Therefore, the objective is to contribute to the security of a company through the application of machine learning methodology. The selection of methodology is justified due to the adaptation of the same according to the interests of this project. Consequently, algorithms were used in a progressive manner, obtaining as a result the control system that was intended, since each particularity of the face of the individual was recognized in relation to its corresponding identification. Finally, the results of this article benefit the security of organizations regardless of their field or sector. Keywords— Control, Detection, Facial Recognition, Facial Mask, Face recognition, Machine learning.

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