Effect of Elevator Design on the Risk Associated with COVID Transmission – A Comparative Study between a Sliding Door and a Collapsible Gate Elevator

The ominous spread of the COVID-19 pandemic is attributed to the droplets respired during coughing, sneezing or speaking. These droplets undergo evaporation to become aerosols, which, along with the larger droplets, are believed to ultimately spread the virus. In this current work, a small, enclosed region like an elevator (containing a COVID infected passenger) is considered where the risk of infection is high as the commonly practiced norm of social distancing is not possible. Numerical simulations are performed using OpenFOAM. Two different types of elevators – one equipped with a sliding door and the other with a collapsible gate, are considered and the change in droplet behavior is examined. Certain parameters pertaining to the risk of virus transmission have been quantified and assessed thoroughly, such as the percentage of droplets floating in the height range from a person's waist height to his mouth height, the radial span of the floating droplets from the infected passenger's mouth. From these parameters, the safety measures to be adopted by other copassengers can be determined. After an extensive study, it has been found that the collapsible gate elevator is safer than the sliding door elevator along with added advantages in the context of disease transmission. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Template for Extended Abstract contributions to INDOOR AIR 2022

This investigation presents results of Computational Fluid Dynamics (CFD) modelling of aerosol behaviour within an arbitrary 'realistic' 100m2 office environment, with dynamic and variable respiratory droplet release profile applied based on published findings (Morawska et al., 2009). A multitude of ventilation strategies and configurations have been applied to the base model to compare the effectiveness of reducing the concentration of suspended aerosols over time. A key finding of the investigation indicates a relatively low sensitivity to increasing outside air percentage, and that the benefit from this strategy is heavily dependent on the in-duct droplet decay factor. The application of local recirculating air filtration systems with MERV-13 filters mounted on occupant desks proved significantly more effectiveness than increasing outside air concentration from 25% to 100% in reducing the quantity of suspended aerosols. This highlights that the ventilation industry should perhaps focus on opportunities to integrate filtration systems into furniture, partitions, cabinetry etc., and that an appliance-based solution may be more beneficial for reducing COVID-19 transmission in buildings (and likely more straightforward) than modifications to central ventilation systems, particularly in the application of refurbishments and retrofits. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.

Predicting the infection probability distribution due to airborne and droplet transmission

In this study, a method was proposed to predict the infection probability distribution rather than the room-averaged value. The infection probability by airborne transmission was predicted based on the CO2 concentration. The infection probability by droplet transmission was predicted based on occupant position information. Applying the proposed method to an actual office confirmed that it could be used for quantitatively predicting the infection probability by integrating the ventilation efficiency and distance between occupants. The infection probability by airborne transmission was relatively high in a zone where the amount of outdoor air supply was relatively small. The infection probability by droplet transmission varied with the position of the occupants. The ability of the proposed method to analyze the relative effectiveness of countermeasures for airborne transmission and droplet transmission was verified in this study. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.

Estimation of infection fields and pathways for SARS-CoV-2 and its variant based on the relationship among dose-response function parameter, quantum emission rate, and basic reproductive number

The theoretical model of the relationship among dose-response function parameters, quantum emission rate, and basic reproductive number for SARS-CoV-2 was constructed. Then, using this model, infection fields and pathways for SARS-CoV-2 and its variant were estimated. The parameters of the time activity, the number of contacts by the microenvironments and groups, and the COVID-19 risk from multiple pathways in near and far fields were used. Consequently, in lower transmissibility, droplet spray transmission in the near field was dominant, whereas in higher transmissibility, transmission from inhalation of smaller aerosols in the far field was dominant. Moreover, it was suggested that transmission from droplet spray, indirect contacts, and inhalation of smaller aerosols in the near field and inhalation of smaller aerosols in the far field was dominant for the wild-type strain, while transmission from inhalation of smaller aerosols in the far field were dominant for the Delta variant. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.

Polyethylene glycol sensitization in patients with recurrent urticaria: Something to consider before the administration of the mRNA COVID-19 vaccine

Background: Polyethylene glycol (PEG) and polysorbate are two commonly used excipients in cosmetics, therapeutics, and processed foods. They are used not just to stabilize and preserve but also to influence the pharmacokinetics and bioavailability of the active ingredients of these products. Numerous reports have described patients with recurrent urticaria self-reporting multiple unrelated products hypersensitivities. We aim to describe a case series of sensitization to PEG in patients with recurrent urticaria and its implications to the currently available COVID-19 vaccines in Malaysia. Method(s): Data of all patients during the peak vaccination period (March 2021 -May 2021) who had positive intradermal test to surrogate PEG and polysorbate 80 were retrieved and analyzed. They were tested with PEG 4000 (macrogol), PEG 400 (Systane Ultra eye drop) and polysorbate 80 (Tween 80). Result(s): A total of eight patients were skin test positive to PEG and/ or polysorbate 80. The mean age was 35.1 +/- 10.5 years. Only one patient was male. Everyone reported history of multiple product reactions with recurrent urticaria as the major symptom. Majority (75%) had multiple unrelated products hypersensitivities. Four of them had urticarial reactions after the first dose of mRNA vaccine. Two patients were skin test negative to the lower molecular weight PEG 400. Cross sensitization between PEG 4000 and polysorbate 80 was 100%. All patients were subsequently inoculated with two doses of inactivated virus COVID-19 vaccine without any serious sequalae. Conclusion(s): The validity of skin testing towards PEG is not yet clear. Nonetheless it is a promising tool in diagnosing PEG sensitization in selected patients reporting recurrent urticaria with multiple unrelated products. Pretesting of this select group may be considered before the inoculation of PEG-containing COVID-19 vaccine.

A nanofiber Murray membrane with antibacterial properties for high efficiency oily particulate filtration

Particulate air pollution represented by PM2.5 is one of the biggest environmental challenges in the 21st century. Especially in 2020, the global outbreak of COVID-19 has brought new challenges to melt-blown filter materials, such as the attenuation of filtration efficiency with breathing, even no filtration effect for viruses as their smaller diameter, the sharp decline of filter efficiency after oily filtration cycle, and its limit in some explosive occasions. Here, using the diameter difference of polystyrene (PS), polyvinylidene fluoride (PVDF) and nylon 6(PA6) fibers, we report a multistage structure nanofiber membrane (PS/PVDF/PA6&Ag MSNMs) with high efficiency, low resistance and antibacterial effect by constructing gradient pore structure and introducing silver nanoparticles (Ag NPs), overcoming the above defects. The average filtration efficiency of PS/PVDF/PA6&Ag MSNMs for diisooctyl sebacate (DEHS) monodisperse particles from 0.2 μm to 4.9 μm was 99.88%, and the pressure drop was only 128 Pa. After repeated circulation for 100 times, the filtration efficiency and pressure drop remained stable. Above all, the antibacterial nanofiber membrane with high efficiency and low resistance has been preliminarily constructed, the future research will further focus on the performance after circulation. © 2023 Elsevier Ltd

A Prospective Approach on Covid-19 Forecasting Using LSTM

The novel Corona virus has been proclaimed as a worldwide pandemic through World Health Organization in the March 2020 has immensely affected the world with its ferocity. By observation, the scientists got to know that it transmits from one human to other by droplets which range from larger respiratory droplets to smaller aerosols or direct contact with an infected person. Its impurity has been assessed to have an incubation time of 6.4 days than a simple reproduction amount of 2.24-3.58.[19] The transmission rate and spread of infection is quite rapid as compared to other fatal viral infections encountered till date. A massive loss of human life was faced even by the developed countries which had the best health-care facilities. According to WHO, COVID-19 has been confirmed in 238,521,855 people over the world, with 4,863,818 deaths as of October 9th, 2021. After experiencing the second covid wave, the number of cases had got dropped drastically but the increase in their number in the recent days is a major cause of concern. This stresses us to build some prediction models which could help in providing relief to the virus-prone areas. In this study, we are using time series for predicting forthcoming cases of corona virus. © 2022 IEEE.

A Parallel Adaptive Finite Element Method for Modeling a Deformable Droplet Travelling in Air

Violent respiratory events such as coughing and sneezing can contribute to the transmission of infectious diseases from host to host. The dynamics of droplet transfer between individuals and the range of contamination are extremely complex and remain unclear [3]. Studying the fluid dynamics of pathogen-laden droplets is critically important to controlling the covid19 pandemic. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Saliva Droplet Evaporation Experiment and Simple Correlation of Evaporation-falling Curve under Different Temperatures and RH

In the present study, water and saliva droplet evaporation rates are experimentally evaluated in various environmental conditions: temperature and relative humidity. We found that the ratio of saliva residue size to saliva initial droplet size is 0.216. We also found that the saliva correction factor which is defined as a ratio of water evaporation coefficient to saliva evaporation coefficient was not affected by environmental conditions and was determined as 0.857. By considering the evaporation and gravitational settling effects, the saliva airborne lifetime, i.e., the evaporation-falling curve is numerically calculated and characterized. In addition to this numerical calculation results, we present the simple correlation equation for obtaining the evaporation-falling curve under different temperatures and relative humidity. © 2023, AAGR Aerosol and Air Quality Research. All rights reserved.

Guillain-Barre syndrome: An autoimmune disorder post-COVID-19 vaccination?

SARS-CoV-2 causes Coronavirus Disease 2019 (COVID-19), an infectious condition that can present none or one or more of these symptoms: fever, cough, headache, sore throat, loss of taste and smell, aches, fatigue and musculoskeletal pain. For the prevention of COVID-19, there are vaccines available including those developed by Pfizer, Moderna, Sinovac, Janssen, and AstraZeneca. Recent evidence has shown that some COVID-19-vaccinated individuals can occasionally develop as a potential side effect Guillain-Barre syndrome (GBS), a severe neurological autoimmune condition in which the immune response against the peripheral nerve system (PNS) can result in significant morbidity. GBS had been linked previously to several viral or bacterial infections, and the finding of GBS after vaccination with certain COVID-19, while rare, should alert medical practitioners for an early diagnosis and targeted treatment. Here we review five cases of GBS that developed in different countries after COVID-19 vaccination.Copyright © 2021

A Review Study on Associated Factors Ofmyopia Amongschool Goingchildren

Myopia is a prevalent yet confusingocular disorder. Myopia,formerlyconsidered abenignrefractivecondition, is nowassociatedwithanincreasedriskofdevelopingseveraloculardisorders,evenatmodestlevels.Myopiaisaglobalproblemthatexpe rts have documented. Despite the fact that the specific cause of myopia remains a mystery, it appears to be a combinationof genetic and environmental factors, making the prevention and treatment of the condition difficult and highly personalised.Myopia can have a positive impact on both the quality of life and the health of the eyes if it is prevented. Progressive additionlenses (PAL), topical atropine, ortho-k (orthokeratology) lenses and multifocal contact lenses are some of the most commoncontrol options currently available. Myopia has gained prominence in optometry studies as a result of its high prevalence. It ismore common for children to suffer from problems, such as extreme myopia and myopic macular degeneration, if they begindevelopingmyopiaatanearlyage.Thepurposeofthisstudywillbetoconductaninquiryintotheepidemiologyandriskfactorsfor myopiainschool-agedchildren(aged 6-19years)aroundtheworld.Copyright © 2022, Anka Publishers. All rights reserved.

Intelligent Ventilation System for COVID-19 Prevention using the IoT and Decision Tree

COVID-19 can be spread through the air, caused by inhaling smaller droplets1 containing SARS-CoV-2 in an indoor environment. In particular, both people with symptoms and people without symptoms make many small droplets and respiratory droplets when they breathe, sneeze, cough, or speak. When these tiny droplets are exposed to the air around them, they can react with the particles (PM) and stay in the air for a long time. The survival period depends on various conditions, including the type of surface, temperature, and relative humidity. The ventilation system is one way to solve this problem. This research makes a significant contribution to the development of intelligent ventilation systems utilizing the Internet of Things (IoT) and decision tree algorithms. The function of this system is to get a clean room environment from viruses by spraying disinfectant automatically and controlling the temperature and humidity of the air. Based on the results of this study, the system is able to control and categorize room conditions based on temperature and humidity factors. The classification value using the C4.5 decision tree algorithm is 92.33% with an average temperature and humidity value of 25oC and 49%. © 2022 IEEE.

HateNet: A Graph Convolutional Network Approach to Hate Speech Detection

The COVID-19 pandemic has caused hate speech on online social networks to become a growing issue in recent years, affecting millions. Our work aims to improve automatic hate speech detection to prevent escalation to hate crimes. The first c hallenge i n h ate s peech r esearch i s t hat e xisting datasets suffer from quite severe class imbalances. The second challenge is the sparsity of information in textual data. The third challenge is the difficulty i n b alancing t he t radeoff b etween utilizing semantic similarity and noisy network language. To combat these challenges, we establish a framework for automatic short text data augmentation by using a semi-supervised hybrid of Substitution Based Augmentation and Dynamic Query Expansion (DQE), which we refer to as SubDQE, to extract more data points from a specific c lass f rom T witter. W e a lso p ropose the HateNet model, which has two main components, a Graph Convolutional Network and a Weighted Drop-Edge. First, we propose a Graph Convolutional Network (GCN) classifier, using a graph constructed from the thresholded cosine similarities between tweet embeddings to provide new insights into how ideas are connected. Second, we propose a weighted Drop-Edge based stochastic regularization technique, which removes edges randomly based on weighted probabilities assigned by the semantic similarities between Tweets. Using 3 different SubDQE-augmented datasets, we compare our HateNet model using eight different tweet embedding methods, six other baseline classification models, and seven other baseline data augmentation techniques previously used in the realm of hate speech detection. Our results show that our proposed HateNet model matches or exceeds the performance of the baseline models, as indicated by the accuracy and F1 score. © 2022 IEEE.

A Real Time Face Mask Detection and Health Status Monitoring using Deep Learning after Pandemic

Over the past two years, COVID-19 has spread over 200 countries, leading to pandemic proportions. Still, the virus is rapidly changing, the variants spreading through direct and indirect contact in places irrespective of the vaccine distribution. Many infectious diseases spread through droplets, and micro-droplets require face masks and other social distancing measures. This article proposed for pandemic circumstances called real-time face mask with health screening (RTFMHS) with two screening methods: (i) Internet of Things (IoT) node monitors a real-time intelligent face mask detection using multi-level high-speed augmented convolution neural network (MLHS-CNN), (ii) Individuals health indicators such as non-contact body temper-ature sensor and blood oxygen saturation are sending to fog cloud to manipulate and display the user health status. A face mask detection technique based on MLHS-CNN is proposed to determine whether a person is wearing a mask properly. User health is computed in real-time by an RNN running on the fog server to estimate the risk of infection spreading. The proposed method uses a lightweight IoT node and fog-based Deep Learning (DL) tools for data analysis and diagnosis. The experimental results outperformed previous research in terms of detection accuracy, precision, recall, and time complexity. © 2022 IEEE.

Effectiveness of RANS in predicting indoor airborne viral transmission: A critical evaluation against LES

We investigate the dispersal of droplet nuclei inside a canonical room of size 10×10×3.2m3 with a four-way cassette air-conditioning unit placed at the center of the ceiling. We use Reynolds averaged Navier–Stokes (RANS) simulations with three flow rates corresponding to air changes per hour (ACH) values of 2.5, 5, and 10. The room setup as well as the operating conditions are chosen to match those of a recent high-fidelity large eddy simulation (LES) study. We use statistical overloading with a total of one million droplet nuclei being initially distributed randomly with uniform probability within the room. Six nuclei sizes are considered ranging in radius from 0.1 to 10μm (166,667 nuclei per size). The simulations are one-way coupled and employ the Langevin equations to model sub-grid motion. The flow and particle statistics are compared against the reference LES simulations, and we find that the RANS k−ɛ realizable model may be used as a computationally cheaper alternative to LES for predicting pathogen concentration in confined spaces albeit, with potentially increased statistical discrepancy. © 2023 Elsevier Ltd

Filtration Performance and Fiber Shedding Behavior in Common Respirator and Face Mask Materials

Wearing respirators and face masks is effective for protecting the public from COVID-19 infection. Thus, there is a need to evaluate the performance of the commonly used respirators and face masks. Two experimental systems were developed to investigate seven different mask materials, which have a fiber size range from 0.1 µm (100 nm) to 20 µm (20,000 nm). One of the systems is a computer-controlled setup for measuring the filtration performance, including size-dependent filtration efficiency and pressure drop, while the other system is for testing the fiber shedding behavior of the materials. The technique of scanning electron microscope (SEM) was applied to observe the dimensions and structures of those materials, which are made of nonwoven-fabrics electret-treated media, cotton woven fabrics, or nanofiber media. The study indicated that the 3M N95 respirator has the best overall filtration performance with over 95% efficiency and low pressure drop of 74.1 Pa. The two commercial cotton face masks have the worst filtration performance in general, with a filtration efficiency of around 25%. No broken fibers from by the seven tested respirator and face mask materials were discovered;however, dendrite structures likely shed by the SHEMA97 face mask with a size comparable to its nanoscale fibers were identified. The reason for this phenomena is presented. © 2023, AAGR Aerosol and Air Quality Research. All rights reserved.

iConDet2: An Improved Conjunctivitis Detection Portable Healthcare App Powered by Artificial Intelligence

Conjunctivitis is one of the common and contagious ocular diseases which affects the conjunctiva of the human eye. Both the bacterial and viral types of it can be treated with eye drops and other medicines. It is important to diagnose the disease at its early stage to realise the connection between it and other diseases, especially COVID-19. Mobile applications like iConDet is such a solution that performs well for the initial screening of Conjunctivitis. In this work, we present with iConDet2 which provides an advanced solution than the earlier version of it. It is faster with a higher accuracy level (95%) than the previously released iConDet. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Betaine- and L-Carnitine-Based Ionic Liquids as Solubilising and Stabilising Agents for the Formulation of Antimicrobial Eye Drops Containing Diacerein.

The therapeutic efficacy of topically administered drugs, however powerful, is largely affected by their bioavailability and, thus, ultimately, on their aqueous solubility and stability. The aim of this study was to evaluate the use of ionic liquids (ILs) as functional excipients to solubilise, stabilise, and prolong the ocular residence time of diacerein (DIA) in eye drop formulations. DIA is a poorly soluble and unstable anthraquinone prodrug, rapidly hydrolysed to rhein (Rhe), for the treatment of osteoarthritis. DIA has recently been evaluated as an antimicrobial agent for bacterial keratitis. Two ILs based on natural zwitterionic compounds were investigated: L-carnitine C6 alkyl ester bromide (Carn6), and betaine C6 alkyl ester bromide (Bet6). The stabilising, solubilising, and mucoadhesive properties of ILs were investigated, as well as their cytotoxicity to the murine fibroblast BALB/3T3 clone A31 cell line. Two IL-DIA-based eye drop formulations were prepared, and their efficacy against both Staphylococcus aureus and Pseudomonas aeruginosa was determined. Finally, the eye drops were administered in vivo on New Zealand albino rabbits, testing their tolerability as well as their elimination and degradation kinetics. Both Bet6 and Carn6 have good potential as functional excipients, showing solubilising, stabilising, mucoadhesive, and antimicrobial properties; their in vitro cytotoxicity and in vivo ocular tolerability pave the way for their future use in ophthalmic applications.

Effects of occupant behavior and ventilation on exposure to respiratory droplets in the indoor environment

To quantify the risk of the transmission of respiratory infections in indoor environments, we systematically assessed exposure to talking- and breathing-generated respiratory droplets in a generic indoor environment using computational fluid dynamic (CFD) simulations. The flow field in the indoor environment was obtained with SST k-ω model and Lagrangian method was used to predict droplet trajectories, where droplet evaporation was considered. Droplets can be categorized into small droplets (initial size ≤30 μm or ≤10 μm as droplet nuclei), medium droplets (30–80 μm) and large droplets (>100 μm) according to the exposure characteristics. Droplets up to 100 μm, particular the small ones, can contribute to both short-range and long-range airborne routes. For the face-to-face talking scenario, the intake fraction and deposition fractions of droplets on the face and facial mucosa of the susceptible were up to 4.96%, 2.14%, and 0.12%, respectively, indicating inhalation is the dominant route. The exposure risk from a talking infector decreases monotonically with the interpersonal distance, while that of nasal-breathing generated droplets maintains a relatively stable level within 1.0 m. Keeping an angle of 15° or above with the expiratory flow is efficient to reduce intake fractions to <0.37% for small droplets. Adjusting the orientation from face-to-face to face-to-back can reduce exposure to small droplets by approximately 88.0% during talking and 66.2% during breathing. A higher ventilation rate can reduce the risk of exposure to small droplets but may increase the risk of transmission via medium droplets by enhancing their evaporation rate. This study would serve as a fundamental research for epidemiologist, healthcare workers and the public in the purpose of infection control. © 2023 Elsevier Ltd

Face Masks and Prevention of Respiratory Viral Infections: An Overview

Airborne transmission of respiratory viruses consists of three sequential steps: (1) release of respiratory fluids in the form of droplets from the nose and mouth of an infected person, (2) transport of the droplets through air, and (3) entry of the droplets into the nose and mouth of an uninfected individual. Talking, coughing, and sneezing emit droplets across a spectrum of sizes. The water in exhaled droplets begins to evaporate in air and, as a result, the droplets are reduced in size shortly after being emitted. Face masks are effective for capturing droplets just released from the nose and mouth. Studies indicate that more than 50% of community transmission of SARS-CoV-2 is from asymptomatic and pre-symptomatic cases. Use of face masks by the public can effectively reduce the chance of infected individuals unknowingly spreading the virus. In addition to being an effective device for source control, face masks can protect the wearers from inhaling virus-laden droplets. Cloth masks and disposable masks provide reasonable protection for the public, while surgical masks and N95 respirators give higher levels of protection as needed in healthcare settings. Made with varied materials, these masks have different structural characteristics. The collection efficiency of a face mask depends on droplet size, face velocity, and the structural characteristics of the mask. For a given mask, capturing droplets is more effective during exhalation than during inhalation. Pressure drop across the mask should be taken into consideration when selecting a face mask. The best face mask is the one that gives the highest collection efficiency with the least pressure drop. For an effective protection, a mask should fit the face properly. While face masks have proven adequate in reducing airborne transmission of SARS-CoV-2 infections, continuous improvement is needed to better prepare for future respiratory viral threats. © The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.