ABSTRACT
This paper presents a development of internet of things (IoT)-based indoor air quality monitoring system. The system is purposed to monitor quality of air in offices. It is to assure the health and safety of the working place which is especially being a big concern during the COVID-19 pandemic. Implementing the IoT concept allows to do monitoring from anywhere at anytime. A prototype of the monitoring system is built using three major components, such as an air quality sensor (BME680), a microcontroller (NodeMCU ESP-12), and an IoT cloud platform (ThingSpeak). The experimental test result shows that system was able to monitor the air temperature, air humidity, air pressure, IAQ (indoor air quality) index, carbon dioxide quantity, and VOC (volatile organic compound). These data is presented real-time in a web application and accessible from anywhere by using computers or smartphones. © 2022 IEEE.
ABSTRACT
Emergencies produce significant changes in people's habits and lifestyles. Further, it also impacts our clothing tastes and preferences because social interaction is reduced, and everyday activities are performed at home. Thus, this paper shows a psychographic analysis to determine the type, style, color, and other clothing characteristics users preferred across the pandemic. In addition, some considerations have been taken into account to understand the clothing characteristics users will look for in post-pandemic presential jobs. In this context, the first version of a smartphone app using augmented reality (AR) has been developed. Three-dimensional objects were designed using Blender, while the smartphone app was set up using Unity, accompanied by modules such as AR Foundation, ARCore XR Plugin, and DOTween. The application allows the overview of the selected three-dimensional garment and relevant information about its components. Statistical analysis shows a vital essential between the monthly income of the participants and their purchasing decision;likewise, between sex and upper garments usage. Experimental tests inside a retail store validate this proposal throughout a new sample of 44 people. Ultimately, they filled out a usability test (SUS) that confirmed the application acceptance with an 82.73%. Finally, they gave the corresponding feedback on their experience using the app. Consequently, relevant information that might be used in future research to understand the consumer needs in a matter of clothing emergencies or confinement is passing through has been exposed. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
Objective: The study aimed to obtain active compounds from Cymbopogon nardus as candidates for protease inhibitor of SARS-CoV-2 virus by assessing the ligand-binding affinity in the binding pocket of SARS-CoV-2 main protease protein. Methods: Molecular docking as a protease inhibitor of SARS-CoV-2 was carried using computational software Molegro Virtual Docker (MVD);computational docking was carried using receptors with Protein Data Bank (PDB) were also used to compare the affinity strength of the test compounds against the protease receptor (code of 5R81). The compounds of Cymbopogon nardus were optimized before docking using ChemDraw and minimized energy using Chem3D. Visualization of the docking result by using Discovery Studio and pkCSM was utilized to perform a pharmacokinetic and toxicological analysis (ADMET). Results: The result showed geranyl acetate, elemol, citronellal, and citronellyl acetate compounds from Cymbopogon nardus has a rerank score more negative than native ligand from 5R81 receptor as a protease inhibitor of SARS-CoV-2. Conclusion: Cymbopogon nardus can be developed as an antivirus with the mechanism of a protease inhibitor of SARS-CoV-2 candidates after further experimental tests.
ABSTRACT
Background: Hearing difficulties in COVID may range from mild to severe and vary based on COVID-19 severity. They range from the self-manageable at home to the ones needing hospitalization. They include dizziness, vertigo, tinnitus, and/or hearing loss. Aims: To assess the long-term impact of COVID-19 on the existence of audiovestibular disorders in subjects hospitalized previously for COVID-19. Materials and Methods: 30 test and 30 control subjects hospitalized in the institution after COVID-19 were assessed for audiovestibular screening Tonal Audiometry was then done to measure bone and air conduction thresholds. Gain threshold was assessed for vestibular loss set at a value less than 0, 6 at 60ms, and vHIT was performed. The collected data were subjected to statistical evaluation and the results were formulated. Results:Dizziness was seen in 10% (n=3) subjects, tinnitus in 3.33% (n=1) subject, spinning vertigo in 3.33% (n=1) subject, Dynamic disequilibrium/ imbalance in 3.33% (n=1) subject, static disequilibrium/ imbalance in 6.66% (n=2) subjects, and hearing loss in 10% (n=3) subjects. PTA values were statistically non-significant at all frequencies except at 0.25, 0.5, 2, and 4 kHz with respective p-values of 0.003, 0.083, 0.04, and 0.03. In gain values only vHIT significant gain was seen in right anterior canal with values of 0.798±0.257 in cases and 0.949±0.121 in controls and the p-value of 0.004 Conclusion:Within its limitations, the present study concludes that audiovestibular symptoms and components are involved in subjects with COVID-19. No definitive conclusion can be drawn on auditory involvement in subjects with a history of COVID-19 with the previous hospitalization.
ABSTRACT
The main goal of this work is to develop and validate a mathematical model of an experimental test bench used for laboratory works on the discipline ''Electrical machines part 2". This model will be presented to the students during their distance learning, imposed by the COVID-19 pandemic. The test bench in mind is used to consider the process of connecting a synchronous generator to the electrical grid. The generator's parameters are measured and applied to a model of the machine in the Matlab/Simulink environment. The simulation results are compared with the experimental ones and show good correspondence, validating the proposed model. © 2021 IEEE.