Pathways to community transmission of COVID-19 due to rapid evaporation of respiratory virulets.

HYPOTHESIS: The formation of virus-laden colloidal respiratory microdroplets - the sneeze or cough virulets and their evaporation driven miniaturization in the open air are found to have a significant impact on the community transmission of COVID-19 pandemic. SIMULATION DETAILS: We simulate the motions and trajectories of virulets by employing laminar fluid flow coupled with droplet tracing physics. A force field analysis has been included considering the gravity, drag, and inertial forces to unleash some of the finer features of virulet trajectories leading to the droplet and airborne transmissions of the virus. Furthermore, an analytical model corroborates temperature (T) and relative humidity (RH) controlled droplet miniaturization. RESULTS: The study elucidates that the tiny (1-50 µm) and intermediate (60-100 µm) size ranged virulets tend to form bioaerosol and facilitate an airborne transmission while the virulets of larger dimensions (300 to 500 µm) are more prone to gravity dominated droplet transmission. Subsequently, the mapping between the T and RH guided miniaturization of virulets with the COVID-19 cases for six different cities across the globe justifies the significant contribution of miniaturization-based bioaerosol formation for community transmission of the pandemic.

Multiscale landscaping of droplet wettability on fibrous layers of facial masks.

Liquid mobility is ubiquitous in nature, with droplets emerging at all size scales, and artificial surfaces have been designed to mimic such mobility over the past few decades. Meanwhile, millimeter-sized droplets are frequently used for wettability characterization, even with facial mask applications, although these applications have a droplet-size target range that spans from millimeters to aerosols measuring less than a few micrometers. Unlike large droplets, microdroplets can interact sensitively with the fibers they contact with and are prone to evaporation. However, wetting behaviors at the single-microfiber level remain poorly understood. Herein, we characterized the wettability of fibrous layers, which revealed that a multiscale landscape of droplets ranged from the millimeter to the micrometer scale. The contact angle (CA) values of small droplets on pristine fibrous media showed sudden decrements, especially on a single microfiber, owing to the lack of air cushions for the tiny droplets. Moreover, droplets easily adhered to the pristine layer during droplet impact tests and then yielding widespread areas of contamination on the microfibers. To resolve this, we carved nanowalls on the pristine fibers by plasma etching, which effectively suppressed such wetting phenomena. Significantly, the resulting topographies of the microfibers managed the dynamic wettability of droplets at the multiscale, which reduced the probability of contamination with impact droplets and suppressed the wetting transition upon evaporation. These findings for the dynamic wettability of fibrous media will be useful in the fight against infectious droplets.

An Improved STL-LSTM Model for Daily Bus Passenger Flow Prediction during the COVID-19 Pandemic.

The COVID-19 pandemic is a significant public health problem globally, which causes difficulty and trouble for both people's travel and public transport companies' management. Improving the accuracy of bus passenger flow prediction during COVID-19 can help these companies make better decisions on operation scheduling and is of great significance to epidemic prevention and early warnings. This research proposes an improved STL-LSTM model (ISTL-LSTM), which combines seasonal-trend decomposition procedure based on locally weighted regression (STL), multiple features, and three long short-term memory (LSTM) neural networks. Specifically, the proposed ISTL-LSTM method consists of four procedures. Firstly, the original time series is decomposed into trend series, seasonality series, and residual series through implementing STL. Then, each sub-series is concatenated with new features. In addition, each fused sub-series is predicted by different LSTM models separately. Lastly, predicting values generated from LSTM models are combined in a final prediction value. In the case study, the prediction of daily bus passenger flow in Beijing during the pandemic is selected as the research object. The results show that the ISTL-LSTM model could perform well and predict at least 15% more accurately compared with single models and a hybrid model. This research fills the gap of bus passenger flow prediction under the influence of the COVID-19 pandemic and provides helpful references for studies on passenger flow prediction.

Discovery of nanoscale sanal flow choking in cardiovascular system: exact prediction of the 3D boundary-layer-blockage factor in nanotubes.

Evidences are escalating on the diverse neurological-disorders and asymptomatic cardiovascular-diseases associated with COVID-19 pandemic due to the Sanal-flow-choking. Herein, we established the proof of the concept of nanoscale Sanal-flow-choking in real-world fluid-flow systems using a closed-form-analytical-model. This mathematical-model is capable of predicting exactly the 3D-boundary-layer-blockage factor of nanoscale diabatic-fluid-flow systems (flow involves the transfer of heat) at the Sanal-flow-choking condition. As the pressure of the diabatic nanofluid and/or non-continuum-flows rises, average-mean-free-path diminishes and thus, the Knudsen-number lowers heading to a zero-slip wall-boundary condition with the compressible-viscous-flow regime in the nanoscale-tubes leading to Sanal-flow-choking due to the sonic-fluid-throat effect. At the Sanal-flow-choking condition the total-to-static pressure ratio (ie., systolic-to-diastolic pressure ratio) is a unique function of the heat-capacity-ratio of the real-world flows. The innovation of the nanoscale Sanal-flow-choking model is established herein through the entropy relation, as it satisfies all the conservation-laws of nature. The physical insight of the boundary-layer-blockage persuaded nanoscale Sanal-flow-choking in diabatic flows presented in this article sheds light on finding solutions to numerous unresolved scientific problems in physical, chemical and biological sciences carried forward over the centuries because the mathematical-model describing the phenomenon of Sanal-flow-choking is a unique scientific-language of the real-world-fluid flows. The 3D-boundary-layer-blockage factors presented herein for various gases are universal-benchmark-data for performing high-fidelity in silico, in vitro and in vivo experiments in nanotubes.

Simulating Absorption Spectra of Flavonoids in Aqueous Solution: A Polarizable QM/MM Study.

We present a detailed computational study of the UV/Vis spectra of four relevant flavonoids in aqueous solution, namely luteolin, kaempferol, quercetin, and myricetin. The absorption spectra are simulated by exploiting a fully polarizable quantum mechanical (QM)/molecular mechanics (MM) model, based on the fluctuating charge (FQ) force field. Such a model is coupled with configurational sampling obtained by performing classical molecular dynamics (MD) simulations. The calculated QM/FQ spectra are compared with the experiments. We show that an accurate reproduction of the UV/Vis spectra of the selected flavonoids can be obtained by appropriately taking into account the role of configurational sampling, polarization, and hydrogen bonding interactions.