Crown evolution kinematics of a camellia oil droplet impacting on a liquid layer

The phenomenon of droplet impact on the immiscible liquid is encountered in a variety of scenarios in nature and industrial production. Despite the exhaustive researches, it is not fully clear how the immiscibility of the droplet with impact liquid affects the crown evolution. The present work experimentally investigates the evolution kinematics of crown formed by a normal impact of camellia oil droplet on immiscible water layer. Based on discussion of dynamic impact behaviors for three critical Weber numbers (We), the radius of crown and its average spreading velocity are compared with those of previous theoretical models to discuss their applicability to the immiscible liquid. The evolution kinematics (morphology and velocity) are analyzed by considering the effects of We and layer thickness. Furthermore, the ability of crown expansion in radical and vertical directions is characterized by a velocity ratio. The results show that our experimental crown radius still follows a square-root function of evolution time, which agrees with the theoretical predictions. The dimensionless average spreading velocity decreases with We and follows a power-law, while the dimensionless average rising velocity remains constant. The velocity ratio is shown to be linearly increasing with We, demonstrating that the rising movement in crown evolution gradually enhances with We. These results are helpful for further investigation on the droplet impact on immiscible liquid layer.

Disentangling cadherin-mediated cell-cell interactions in collective cancer cell migration

Cell dispersion from a confined area is fundamental in a number of biological processes, including cancer metastasis. To date, a quantitative understanding of the interplay of single cell motility, cell proliferation, and intercellular contacts remains elusive. In particular, the role of E- and N-Cadherin junctions, central components of intercellular contacts, is still controversial. Combining theoretical modeling with in vitro observations, we investigate the collective spreading behavior of colonies of human cancer cells (T24). Inhibition of E- and N-Cadherin junctions decreases colony spreading and average spreading velocities, without affecting the strength of correlations in spreading velocities of neighboring cells. Based on a biophysical simulation model for cell migration, we show that the behavioral changes upon disruption of these junctions can be explained by reduced repulsive excluded volume interactions between cells. This suggests that cadherin-based intercellular contacts sharpen cell boundaries leading to repulsive rather than cohesive interactions between cells, thereby promoting efficient cell spreading during collective migration.

Simulation of Spatial Spread of the COVID-19 Pandemic on the Basis of the Kinetic-Advection Model

A new two-parameter kinetic equation model is proposed to describe the spatial spread of the virus in the current pandemic COVID-19. The migration of infection carriers from certain foci inherent in some countries is considered. The one-dimensional model is applied to three countries: Russia, Italy, and Chile. Both their geographical location and their particular shape stretching in the direction from the centers of infection (Moscow, Lombardy, and Santiago, respectively) make it possible to use such an approximation. The dynamic density of the infected is studied. Two parameters of the model are derived from known data. The first is the value of the average spreading rate associated with the transfer of infected persons in transport vehicles. The second is the frequency of the decrease in numbers of the infected as they move around the country, associated with the arrival of passengers at their destination. An analytical solution is obtained. Simple numerical methods are also used to perform a series of calculations. Calculations us to make some predictions, for example, about the time of recovery in Russia, if the beginning of recovery in Moscow is known.

Prediction of 2019-nCov in Italy based on PSO and inversion analysis

Novel coronavirus (2019-nCov) has swept the world, and all of the world have been harmful. This article makes prediction and suggestions for the Italy. Up to March 11, 2020, 2019-nCov thoroughly broke out in Italy with over 10,000 confirmed cases notwithstanding the gradually block of the country since March 9, 2020. Estimation of possible infection population and prospective suggestion of handling spread based on exist data are of crucial importance. Considering of the biology parameters obtained based on Chinese clinical data in Wuhan, other scholars’ work and real spread feature of 2019-nCov in Italy, we built a more applicable model called SEIJR with log-normal distributed time delay to forecast the trend of spreading. Adopting Particle Swarm Optimization (PSO), we estimated the early period average spreading velocity (α0) and conducted inversion analysis of time point (T0) when the virus first hit the Italy. Based on fixed α0 and T0, we then obtained the average spreading velocity α1 after the lock by PSO. For the aim of offering expeditious advice, we generated the prediction trends with different α which we considered would be helpful in addressing the infection. Not only solved the complex, nondifferentiable equation of epidemic model, our research also performs well in inversion analysis based on PSO which conveys informative outcomes for further discussion on precatious action. To conclude, the first day of spread is around February 1, 2020 with the early period average spreading velocity α0=0.330 which is higher than most cities in China except Wuhan. After locking the country and attaching great attention to public precaution, the α1 sharply descended to 0.278, indicting the effectiveness of these measures. Furthermore, in order to cope the disease before mid-April, take actions to control the under 0.25 is necessary. Code can be freely downloaded from https://github.com/Summerwork/2019-nCov-Prediction.

Effects of Organic Acids on Wettability of Sn-0.3Ag0.7Cu Lead-Free Solder

In the assembly of electronic products, developing good organic acid fluxes plays an important role in improving the solderability of lead-free solders. In this paper, a variety of fluxes containing 5% (mass fraction) organic acid activators were prepared. Effects of different activators on the spreading rates of Sn-0.3Ag0.7Cu solder were studied. The results show that: activity of monobasic acids are weak except for benzoic acid; dibasic acids and polybasic acids have relatively strong activity but serious corrosion and slightly less activity persistence. Compounding palmitic acid and adipic acid in the mass ratio of 1:2 as the activator, the average spreading rate of Sn-0.3Ag0.7Cu solder is 71.11% in maximum. Compounding succinic acid and adipic acid in the mass ratio of 3:7 as the activator, the average spreading rate is up to 72.49% in maximum. And solder spots are in-erratic, bright and plump, meeting the quality requirements of electronic micro-connection.