Change in departure time for a train trip to avoid crowding during the COVID-19 pandemic: A latent class study in the Netherlands

The energy-efficient plate heat exchanger (PHE) and refrigerant R1234yf, which has a low global warming potential (GWP), can be used to realize an energy efficient heat pump (HP) system for electric vehicles (EV), extending their driving range. Therefore, the characteristics of R1234yf in an offset-fin strip (OSF) flowstructured PHE are critical for heat-exchanger design. This study investigates the condensation heat transfer coefficient (C-HTC) and two-phase frictional pressure drop (2P-FPD) of R1234yf during condensation in an OSF flow-structured PHE under various operating conditions. First, a modified Wilson plot method was used to determine the multiplier (C) and Reynolds number exponential (n) for the coolant side as -0.426 and 0.494, respectively. When the heat flux (q), average vapor quality (xa), and mass flux (G) increased, the C-HTC increased, whereas it decreased with saturation temperature (Tsat). Despite the force-convective condensation flow regime, the C-HTC increment was minimal with G at lower xa owing to the lesser significance of the shear effect. Additionally, the 2P-FPD was unaffected by q but increased considerably with an increase in xa and G and a decrease in Tsat. Based on the current experimental database, empirical correlations for forecasting friction factor and Nusselt number were developed with a 91% predictability.

A prognostic model for classification of COVID-19 severity based on clinical and laboratory testing data

This study aimed to build an machine learning based model to predict the COVID-19 severity and reveal risk factors related to COVID-19 severity based on laboratory testing and clinical data for 420 participants, using tree-based models such as XGBoost, LightGBM, random forest. We calculated the Odds Ratios (OR) to investigate whether the top-ranked features were statistically significant for severity classification, turning out that high sensitivity C-reactive protein (hs-CRP) was the most important feature for determining of COVID-19 severity and XGBoost model showed the highest performance in classifying COVID-19 severity and healthy controls with F1score (0.84) and AUC (0.87). We expect that our results are of considerable significance for early screening for diagnosing COVID-19 severity, which, in turn, assist in further retrospective research for uncommon infectious diseases. © 2023 IEEE.

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.

Measuring single-cell level gene expression stability and variability in healthy and severe COVID-19 patients using Kullback-Leibler divergence

Recent advances in single-cell RNA sequencing (scRNA-seq) technology have enabled the acquisition of RNA at the single-cell level, which showed that the expression level of genes is highly variable across and within the cell types. Even well-known housekeeping genes showed high expression variance in a single condition and within the same cell types. Previous studies made efforts to identify stably expressed genes and use them as a yardstick for robust gene expression normalization. On the other hand, drugs were shown to be less effective on genes with high expression variance. Thus, identifying both stably and variably expressed genes is an important task, especially at the single-cell level. In this study, using the Kullback-Leibler divergence method, we proposed a metric to measure the expression stability of each gene. Using private scRNA-seq data composed of 25 severe COVID-19 patients and 40 healthy individuals, we identified variably expressed genes specific to COVID-19-infected patients and healthy cohorts. © 2022 IEEE.

Study on droplet dispersion influenced by ventilation and source configuration in classroom settings using low‐cost sensor network

The COVID‐19 virus can transmit through airborne expiratory droplets and thus, the viral transmission can take place between the occupants in the isolated room. With the school re-opening under the current COVID‐19 pandemic, it is urgent to improve the classroom ventilation system to mitigate the risk of virus transmission. The present study developed a particle concentration monitoring network (PCMN) using low‐cost sensors and deployed it to explore the dispersion of the droplet particles under different ventilation settings and aerosol configurations. Our experiment shows the advance of using a low‐cost sensor network on spatiotemporal air monitoring and demonstrates indoor particle concentration level and distribution are strongly impacted by the ventilation setting and source location. Two recommendations on reducing the viral risk in the classroom were derived from the study. The first is the respiratory droplet source, e.g., the instructor, should be in the location such that the particle dispersion opposes the ventilation flow. The second is the air handling unit (AHU) and fan coil unit (FCU) should be both turned on during class hours despite whether there is a need for thermal comfort, as it allows higher and more uniform ventilation flow to resolve the issue of the dead air zone. © The Author(s).

An experimentally validated analytical model for aerosol number concentration reduction in classrooms

To predict the aerosol number concentration decay in modern classrooms, this study derived an analytical model that addresses various indoor factors, viz., the filtration efficiency of air ventilation systems, effects of indoor air cleaners, particle deposition on walls, and particle emission from occupants. We also conducted experimental measurements to determine the wall-loss coefficient and the occupants’ particle generation rate, and the modeling results agreed with the experimental data reasonably well. Additionally, we investigated the behavior of the particle concentration decay in different ventilation scenarios. The model has been incorporated into web-based software that is freely available to the public. © The Author(s).

Alternative face masks made of common materials for general public: Fractional filtration efficiency and breathability perspective

As COVID-19 pandemic has caused more than 24 million confirmed cases globally (as of August 28th, 2020), it is critical to slow down the spreading of SARS-CoV-2 to protect the healthcare system from overload. Wearing a respirator or a mask has been proven as an effective method to protect both the wearer and others, but commercially available respirators and masks should be reserved for healthcare workers under a currently desperate shortage. The use of alternative materials becomes an option for the general public to make the do-it-yourself (DIY) masks, with their efficacy seldom reported. In this study, we tested commercial respirators and masks, furnace filters, vacuum cleaner filters, and common household materials. We evaluated the materials’ fractional filtration efficiency and breathing resistance, which are primary factors affecting respiratory protection. To compare the efficiency-resistance tradeoff, the figure of merit of each tested common material was also calculated. Filter media with electrostatic charges (electret) is recommended due to its high efficiency with low flow resistance;multiple-layer household fabrics and sterilization wraps are acceptable materials;a coffee filter is inadvisable due to its low efficiency. The outcome of this study can not only offer guidance for the general public under the current pandemic but also suggest the appropriate alternative respiratory protection materials under heavy air pollution episodes. © The Author(s).