Multi-step forecasts can be produced recursively by iterating a one-step model, or directly using a specific model for each horizon. Choosing between these two strategies is not an easy task since it involves a trade-off between bias and estimation variance over the forecast horizon. Using a nonlinear machine learning model makes the tradeoff even more difficult. To address this issue, we propo...

During spermiogenesis in Eledone cirrhosa a single protamine substitutes for histones in nuclei of developing spermatids. This protein displays a peculiar primary structure. It contains 22.6 mol% cysteine residues (19 cysteines in 84 residues). This makes it the most cysteine-rich protamine known. The proportion of basic residues is relatively low (arginine 36.9 mol%, lysine 19.0 mol%). The pro...

A bubble merged from two parent bubbles with different size tends to be placed closer to the larger parent. This phenomenon is known as the coalescence preference. Here we demonstrate that the coalescence preference can be blocked inside a densely packed cluster of bubbles. We utilized high-speed high-resolution X-ray microscopy to clearly visualize individual coalescence events inside densely ...

In this work, a mechanistic model of drop coalescence based upon a stochastic film-drainage analysis is developed. The coalescence model accounts for previously considered factors, such as turbulence intensity, drop size, and drop deformability, while additionally describing the dual effects of drop surface potential and system electrolyte concentration. Model results indicate that electrostati...

Molecular dynamics simulations were performed to investigate the wetting and coalescence of liquid Al and Pb drops on four carbon-based substrates. We highlight the importance of the microstructure and surface topography of substrates in the coalescence process. Our results show that the effect of substrate on coalescence is achieved by changing the wettability of the Pb metal. Additionally, we...