Shaken not stirred — On internal flow patterns in oscillating sessile drops

We use numerical (volume of fluid) simulations to study the flow in an oscillating sessile drop immersed in an ambient immiscible fluid. The drop is excited by a sinusoidal variation of the contact angle at variable frequency. We identify the eigenfrequencies and eigenmodes of the drops and analyze the internal flow fields by following the trajectories of tracer particles. The flow fields display an oscillatory component as well as a time-averaged mean component. The latter is oriented upward along the surface of the drop from the contact line towards the apex and downward along the symmetry axis. It vanishes at high and low frequencies and displays a broad maximum around f =200–300Hz. We show that the frequency dependence of the mean flow can be described in terms of Stokes drift driven by capillary waves that originate from the contact line, in agreement with recent experiments

Capillarity-driven dynamics of water–alcohol mixtures in nanofluidic channels

We investigated the spontaneous capillarity-driven filling of nanofluidic channels with a thickness of 6 and 16 nm using mixtures of ethanol and water of variable composition. To improve the visibility of the fluid, we embedded metal mirrors into the top and bottom walls of the channels that act as a Fabry–Pérot interferometer. The motion of propagating liquid–air menisci was monitored for various concentrations in transmission with an optical microscope. In spite of the visible effects of surface roughness and different affinity of water and ethanol to the channel walls, the dynamics followed the classical t 1/2—dependence according to Lucas and Washburn. While the prefactor of this algebraic relation falls short of the expectations based on bulk properties by 10–30%, the relative variation between mixtures of different composition follows the expectations based on the bulk surface tension and viscosity, implying that—despite the small width of the channels and the large surface-to-volume ratio—specific adsorption or chemical selectivity effects are not relevant. We briefly discuss the impact of surface roughness on our experimental results

Alleviation of carbon catabolite repression in Enterobacter aerogenes for efficient utilization of sugarcane molasses for 2,3-butanediol production

Table S3. Comparison of fed-batch fermentation with EMY-01, EMY-68, EMY-70S, and EMY-70SP using sugarcane molasses

Numerical Modelling for Effect of Water Curtain in Mitigating Toxic Gas Release

PresentationAs the chemical industry has developed, the use of toxic substances has increased, and leakage accidents have increased. Among various substances, hydrogen fluoride (HF) and ammonia (NH3) are representative materials for the study since both are hazardous and important in the chemical industry. HF is a strong, pervious substance that is a stimulates on the body, respiratory system, and skin. HF is widely used in electronics manufacturing as a polisher and disinfectant. Since an HF release accident occurred in Gumi, S. Korea (2012) the Korea Occupational Safety and Health Agency (KOSHA) has emphasized that special attention and management is needed with respect to this toxic substance. NH3 is widely used in the semiconductor industry and chemical processes. There have been about 20 large accidents regarding NH3 around the world in last 10 years. In this study, ANSYS Fluent, a computational fluid dynamics (CFD) program, was used to identify the effect of a water curtain as a mitigation system for toxic substances that are leaked from industrial facilities. Simulations were conducted to analyze how effectively a water curtain mitigated the dispersion of toxic substances. To verify the accuracy of the simulation, Goldfish experiment and INERIS Ammonia dispersion experiment were simulated and compared. Various water curtains were applied to the simulated field experiment to confirm the mitigation factors of toxic substances. The results show that the simulations and experiments are consistent and that the dispersion of toxic substances can be mitigated by water curtains

Optimizing Parameters of Information-Theoretic Correlation Measurement for Multi-Channel Time-Series Datasets in Gravitational Wave Detectors

Data analysis in modern science using extensive experimental and observational facilities, such as a gravitational wave detector, is essential in the search for novel scientific discoveries. Accordingly, various techniques and mathematical principles have been designed and developed to date. A recently proposed approximate correlation method based on the information theory is widely adopted in science and engineering. Although the maximal information coefficient (MIC) method remains in the phase of improving its algorithm, it is particularly beneficial in identifying the correlations of multiple noise sources in gravitational-wave detectors including non-linear effects. This study investigates various prospects for determining MIC parameters to improve the reliability of handling multi-channel time-series data, reduce high computing costs, and propose a novel method of determining optimized parameter sets for identifying noise correlations in gravitational wave data.Comment: 11 pages, 8 figure

The role of social support and social networks in smoking behavior among middle and older aged people in rural areas of South Korea: A cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Although the number of studies on anti-smoking interventions has increased, studies focused on identifying social contextual factors in rural areas are scarce. The purpose of this study was to explore the role of social support and social networks in smoking behavior among middle and older aged people living in rural areas of South Korea.</p> <p>Methods</p> <p>The study employed a cross-sectional design. Participants included 1,057 adults, with a mean age of 60.7 years, residing in rural areas. Information on participants' tobacco use, stress, social support, and social networks was collected using structured questionnaires. The chi-square test, the t-test, ANOVA, and logistic regression were used for data analysis.</p> <p>Results</p> <p>The overall smoking prevalence in the study was 17.4% (men, 38.8%; women, 5.1%). Overall, stress was high among women, and social support was high among men. Smokers had high levels of social support (t = -2.90, p = .0038) and social networks (t = -2.22, p = .0271), as compared to non- and former smokers. Those in the high social support group were likely to be smokers (AOR = 2.21, 95% CI 1.15-4.26). Women with moderate social ties were less likely to smoke (AOR = 0.18, 95% CI 0.05-0.61).</p> <p>Conclusion</p> <p>There was a protective role of a moderate social network level among women, and a high level of social support was associated with smoking behaviors in rural areas. Findings suggest the need for a comprehensive understanding of the functions and characteristics of social contextual factors including social support and social networks in order to conduct more effective anti-smoking interventions in rural areas.</p

Production of 2,3-butanediol in Saccharomyces cerevisiae by in silico aided metabolic engineering

BACKGROUND: 2,3-Butanediol is a chemical compound of increasing interest due to its wide applications. It can be synthesized via mixed acid fermentation of pathogenic bacteria such as Enterobacter aerogenes and Klebsiella oxytoca. The non-pathogenic Saccharomyces cerevisiae possesses three different 2,3-butanediol biosynthetic pathways, but produces minute amount of 2,3-butanediol. Hence, we attempted to engineer S. cerevisiae strain to enhance 2,3-butanediol production. RESULTS: We first identified gene deletion strategy by performing in silico genome-scale metabolic analysis. Based on the best in silico strategy, in which disruption of alcohol dehydrogenase (ADH) pathway is required, we then constructed gene deletion mutant strains and performed batch cultivation of the strains. Deletion of three ADH genes, ADH1, ADH3 and ADH5, increased 2,3-butanediol production by 55-fold under microaerobic condition. However, overproduction of glycerol was observed in this triple deletion strain. Additional rational design to reduce glycerol production by GPD2 deletion altered the carbon fluxes back to ethanol and significantly reduced 2,3-butanediol production. Deletion of ALD6 reduced acetate production in strains lacking major ADH isozymes, but it did not favor 2,3-butanediol production. Finally, we introduced 2,3-butanediol biosynthetic pathway from Bacillus subtilis and E. aerogenes to the engineered strain and successfully increased titer and yield. Highest 2,3-butanediol titer (2.29 g·l(-1)) and yield (0.113 g·g(-1)) were achieved by Δadh1 Δadh3 Δadh5 strain under anaerobic condition. CONCLUSIONS: With the aid of in silico metabolic engineering, we have successfully designed and constructed S. cerevisiae strains with improved 2,3-butanediol production