Vibrational Spectra and Adsorption of Trisiloxane Superspreading Surfactant at Air/Water Interface Studied with Sum Frequency Generation Vibrational Spectroscopy

The C-H stretch vibrational spectra of the trisiloxane superspreading surfactant Silwet L-77 （（CH3）3Si- O-Si（CH3）（C3H6）（OCH2CH2）7-8OCH3）-O-Si（CH3）3） at the air/water interface are measured with the surface Sum Frequency Generation Vibrational Spectroscopy （SFG-VS）. The spectra are dominated with the features from the -Si-CH3 groups around 2905 cm^-1 （symmetric stretch or SS mode） and 2957 ^-1 （mostly the asymmetric stretch or AS mode）, and with the weak but apparent contribution from the -O-CH2- groups around 2880 ^-1 （symmetric stretch or SS mode）. Comparison of the polarization dependent SFG spectra below and above the critical aggregate or micelle concentration （CAC） indicates that the molecular orientation of the C-H related molecular groups remained unchanged at different surface densities of the Silwet L-77 surfactant. The SFG-VS adsorption isotherm suggested that there was no sign of Silwet L-77 bilayer structure formation at the air/water interface. The Gibbs adsorption free energy of the Silwet surfactant to the air/water interface is -42.2±0.8kcal/mol, indicating the unusually strong adsorption ability of the Silwet L-77 superspreading surfactant.

Disease momentum: Estimating the reproduction number in the presence of superspreading

A primary quantity of interest in the study of infectious diseases is the average number of new infections that an infected person produces.This so-called reproduction number has significant implications for the disease progression.There has been increasing literature suggesting that superspreading,the significant variability in number of new infections caused by individuals,plays an important role in the spread of SARS-CoV-2.In this paper,we consider the effect that such superspreading has on the estimation of the reproduction number and subsequent estimates of future cases.Accordingly,we employ a simple extension to models currently used in the literature to estimate the reproduction number and present a case-study of the progression of COVID-19 in Austria.Our models demonstrate that the estimation uncertainty of the reproduction number increases with superspreading and that this improves the performance of prediction intervals.Of independent interest is the derivation of a transparent formula that connects the extent of superspreading to the width of credible intervals for the reproduction number.This serves as a valuable heuristic for understanding the uncertainty surrounding diseases with superspreading.

Effects of environmental variability on superspreading transmission events in stochastic epidemic models

Superspreaders(individuals with a high propensity for disease spread)have played a pivotal role in recent emerging and re-emerging diseases.In disease outbreak studies,host heterogeneity based on demographic(e.g.age,sex,vaccination status)and environmental(e.g.climate,urban/rural residence,clinics)factors are critical for the spread of infectious diseases,such as Ebola and Middle East Respiratory Syndrome(MERS).Transmission rates can vary as demographic and environmental factors are altered naturally or due to modified behaviors in response to the implementation of public health strategies.In this work,we develop stochastic models to explore the effects of demographic and environmental variability on human-to-human disease transmission rates among superspreaders in the case of Ebola and MERS.We show that the addition of environmental variability results in reduced probability of outbreak occurrence,however the severity of outbreaks that do occur increases.These observations have implications for public health strategies that aim to control environmental variables.

Spreading and Wetting Behaviour of Trisiloxanes

Wetting and spreading processes which involve surfactant solutions are widely used in numerous industrial and practical applications nowadays.The performance of different non-ionic surfactants may vary significantly and so far superspreader solutions show the most promising spreading ability.The addition of trisiloxane surfactants to water was proven to enhance wetting,even on hydrophobic surfaces,on which conventional surfactants seem to have little or no effect.Although these extraordinary surfactants have been extensively studied over recent years,complete understanding of their underlying mechanisms and a suitable mathematical model are still lacking.Here we present a possible explanation for the impressive performance of trisiloxane,which is compared to wetting enhancement of a conventional surfactant.Additionally,we will explain why the hydrophobicity of the surface is a crucial factor for the spreading phenomenon.Light will be also shed on the effect of the pH of the solution to which surfactants are added.Finally,we will investigate long-term effects of the water environment on trisiloxane wetting ability and discuss if ageing may significantly affect their performance.

硅表面活性剂的超铺展现象及本质(续完)

另一个有趣的方面是基底的疏水性如何影响超铺展速度[55]。Nikolov和Wasan对超铺展的理论基础进行了很好的总结[56]。他们提出了一种关于超铺展的理论,指出在液滴体积不变且表面活性剂浓度不变的情况下,超铺展的平均速率取决于从液滴最顶部向三相接触线沿着气液界面的表面张力梯度。

Large-area ultrastrong and stiff aramid nanofiber based layered nanocomposite films

One-dimensional(1D)aramid nanofiber(ANF)based nanocomposite films have drawn increasing attentions in various applications due to their excellent mechanical properties and impressive chemical and thermal stabilities.However,the large-area fabrication of aramid nanocomposite films with ultrastrong mechanical properties under mild conditions remains a great challenge.Here we present a facile superspreading-assisted strategy to produce aramid nanofiber based oriented layered nanocomposites using phase inversion process that occurs at the fully swollen hydrogel surfaces.The nanocomposite films based on ANF,carboxylation carbon tube(CNT–COOH),poly(vinyl alcohol)(PVA),and MXene nanosheet exhibit a tensile strength of up to 870.8±85 MPa,a Young’s modulus of 21.8±2.2 GPa,and outstanding toughness(up to 43.2±4.6 MJ/m^(3)),which are much better than those conventional aramid nanofiber based materials.Electrical conductivity of our nanocomposite films reaches the maximum of about 1100 S/m.The fabulous mechanical properties combination and continuous production capability render our strategy representing a promising direction for the development of high-performance nanocomposites.

Unclear but present danger:An asymptomatic SARS-CoV-2 carrier

Superspreaders are critical infectious resources in multiple infectious diseases.They can be asymptomatic or present mild symptoms but can transmit pathogens to susceptible populations,leading to severe symptoms,and even death.Early identification of this population is extremely important to inhibit the spread of infectious diseases.Right now,the whole global world is suffering from a devastating infectious disease caused by severe acute respiratory syndrome coronavirus 2(SARS-CoV-2).In this article,a superspreader cluster event in coronavirus disease 2019(COVID-19)was identified by tracking contacting histories of infected patients.This cluster was found to be originated from an asymptomatic SARS-CoV-2 carrier,which resulted in 13 secondary cases getting infected.All the secondary patients presented with non-typical symptoms of COVID-19,such as fever,dry cough,and myalgia,one of which died of respiratory failure at the end.From this cluster,we learn that people with older ages,low immunity,multiple underlying diseases,especially pulmonary diseases,can contribute to a poor prognosis.Thus,asymptomatic superspreaders of COVID-19 can be extremely dangerous and must be handled time-efficiently.

WLAN-log-based superspreader detection in the COVID-19 pandemic

Identifying“superspreaders”of disease is a pressing concern for society during pandemics such as COVID-19.Superspreaders represent a group of people who have much more social contacts than others.The widespread deployment of WLAN infrastructure enables non-invasive contact tracing via people’s ubiquitous mobile devices.This technology offers promise for detecting superspreaders.In this paper,we propose a general framework for WLAN-log-based superspreader detection.In our framework,we first use WLAN logs to construct contact graphs by jointly considering human symmetric and asymmetric interactions.Next,we adopt three vertex centrality mea-surements over the contact graphs to generate three groups of superspreader candidates.Finally,we leverage SEIR simulation to determine groups of superspreaders among these candidates,who are the most critical individuals for the spread of disease based on the simulation results.We have implemented our framework and evaluate it over a WLAN dataset with 41 million log entries from a large-scale university.Our evaluation shows superspread-ers exist on university campuses.They change over the first few weeks of a semester,but stabilize throughout the rest of the term.The data also demonstrate that both symmetric and asymmetric contact tracing can dis-cover superspreaders,but the latter performs better with daily contact graphs.Further,the evaluation shows no consistent differences among three vertex centrality measures for long-term(i.e.,weekly)contact graphs,which necessitates the inclusion of SEIR simulation in our framework.We believe our proposed framework and these results can provide timely guidance for public health administrators regarding effective testing,intervention,and vaccination policies.