The motion, stability and breakup of a stretching liquid bridge with a receding contact line

The complex behavior of drop deposition on a hydrophobic surface is considered by looking at a model problem in which the evolution of a constant-volume liquid bridge is studied as the bridge is stretched. The bridge is pinned with a fixed diameter at the upper contact point, but the contact line at the lower attachment point is free to move on a smooth substrate. Experiments indicate that initially, as the bridge is stretched, the lower contact line slowly retreats inwards. However at a critical radius, the bridge becomes unstable, and the contact line accelerates dramatically, moving inwards very quickly. The bridge subsequently pinches off, and a small droplet is left on the substrate. A quasi-static analysis, using the Young-Laplace equation, is used to accurately predict the shape of the bridge during the initial bridge evolution, including the initial onset of the slow contact line retraction. A stability analysis is used to predict the onset of pinch-off, and a one-dimensional dynamical equation, coupled with a Tanner-law for the dynamic contact angle, is used to model the rapid pinch-off behavior. Excellent agreement between numerical predictions and experiments is found throughout the bridge evolution, and the importance of the dynamic contact line model is demonstrated.Comment: 37 pages, 12 figure

BAC transgene arrays as a model system for studying large-scale chromatin structure

The folding of interphase chromatin into large-scale chromatin structure and its spatial organization within nucleus has been suggested to have important roles in gene regulation. In this study, we created engineered chromatin regions consisting of tandem repeats of BAC transgenes, which contain 150-200 kb of defined genomic regions, and used them as a model system to study the mechanisms and functional significance of large-scale chromatin organization. The BAC transgene arrays recapitulated several important features of endogenous chromatin, including transcription level and intranuclear positioning. Using this system, we showed that tandem arrays of housekeeping gene loci form open large-scale chromatin structure independent of their genomic integration sites, including insertions within centromeric heterochromatin. This BAC-specific large-scale chromatin conformation provided a permissive environment for transcription, as evidenced by the copy-number dependent and position independent expression of embedded reporter mini-genes. This leads to the development of a novel method for reliable transgene expression in mammalian cells, which should prove useful in a number of therapeutic and scientific applications. We also demonstrated that BAC transgene arrays can be employed as an effective system for dissecting sequence determinants for intranuclear positioning of gene loci. We showed that in mouse ES and fibroblast cells a BAC carrying a 200 kb human genomic fragment containing the beta-globin locus autonomously targets to the nuclear periphery. Using BAC recombineering, we dissected this 200kb region and identified two genomic regions sufficient to target the BAC transgenes to nuclear periphery. This study represents a first step towards elucidation of the molecular mechanism for the nuclear peripheral localization of genes in mammalian cells

Type-III two Higgs doublet model plus a pseudoscalar confronted with h→μτh\rightarrow\mu\tau, muon g−2g-2 and dark matter

In this work, we introduce an extra singlet pseudoscalar into the Type-III two Higgs doublet model (2HDM) which is supposed to solve a series of problems in the modern particle-cosmology. With existence of a light pseudoscalar, the $h\rightarrow\mu\tau$ excess measured at CMS and as well as the $(g-2)_{\mu}$ anomaly could be simultaneously explained within certain parameter spaces that can also tolerate the data on the flavor-violating processes $\tau\rightarrow\mu\gamma$ and Higgs decay gained at LHC. Within the same parameter spaces, the DM relic abundance is well accounted. Moreover, the recently observed Galactic Center gamma ray excess(GCE) is proposed to realize through dark matter(DM) pair annihilations, and in this work, the scenario of the annihilation being mediated by the pseudoscalar is also addressed.Comment: 14 pages, 8 figures, version to appear in NP

Analysis of Noisy Evolutionary Optimization When Sampling Fails

In noisy evolutionary optimization, sampling is a common strategy to deal with noise. By the sampling strategy, the fitness of a solution is evaluated multiple times (called \emph{sample size}) independently, and its true fitness is then approximated by the average of these evaluations. Previous studies on sampling are mainly empirical. In this paper, we first investigate the effect of sample size from a theoretical perspective. By analyzing the (1+1)-EA on the noisy LeadingOnes problem, we show that as the sample size increases, the running time can reduce from exponential to polynomial, but then return to exponential. This suggests that a proper sample size is crucial in practice. Then, we investigate what strategies can work when sampling with any fixed sample size fails. By two illustrative examples, we prove that using parent or offspring populations can be better. Finally, we construct an artificial noisy example to show that when using neither sampling nor populations is effective, adaptive sampling (i.e., sampling with an adaptive sample size) can work. This, for the first time, provides a theoretical support for the use of adaptive sampling

Running Time Analysis of the (1+1)-EA for Robust Linear Optimization

Evolutionary algorithms (EAs) have found many successful real-world applications, where the optimization problems are often subject to a wide range of uncertainties. To understand the practical behaviors of EAs theoretically, there are a series of efforts devoted to analyzing the running time of EAs for optimization under uncertainties. Existing studies mainly focus on noisy and dynamic optimization, while another common type of uncertain optimization, i.e., robust optimization, has been rarely touched. In this paper, we analyze the expected running time of the (1+1)-EA solving robust linear optimization problems (i.e., linear problems under robust scenarios) with a cardinality constraint $k$. Two common robust scenarios, i.e., deletion-robust and worst-case, are considered. Particularly, we derive tight ranges of the robust parameter $d$ or budget $k$ allowing the (1+1)-EA to find an optimal solution in polynomial running time, which disclose the potential of EAs for robust optimization.Comment: 17 pages, 1 tabl

On the Robustness of Median Sampling in Noisy Evolutionary Optimization

In real-world optimization tasks, the objective (i.e., fitness) function evaluation is often disturbed by noise due to a wide range of uncertainties. Evolutionary algorithms (EAs) have been widely applied to tackle noisy optimization, where reducing the negative effect of noise is a crucial issue. One popular strategy to cope with noise is sampling, which evaluates the fitness multiple times and uses the sample average to approximate the true fitness. In this paper, we introduce median sampling as a noise handling strategy into EAs, which uses the median of the multiple evaluations to approximate the true fitness instead of the mean. We theoretically show that median sampling can reduce the expected running time of EAs from exponential to polynomial by considering the (1+1)-EA on OneMax under the commonly used one-bit noise. We also compare mean sampling with median sampling by considering two specific noise models, suggesting that when the 2-quantile of the noisy fitness increases with the true fitness, median sampling can be a better choice. The results provide us with some guidance to employ median sampling efficiently in practice.Comment: 19 pages. arXiv admin note: text overlap with arXiv:1810.05045, arXiv:1711.0095