Stochastic flowering phenology in Dactylis glomerata populations described by Markov chain modelling

Understanding the relationship between flowering patterns and pollen dispersal is important in climate change modelling, pollen forecasting, forestry and agriculture. Enhanced understanding of this connection can be gained through detailed spatial and temporal flowering observations on a population level, combined with modelling simulating the dynamics. Species with large distribution ranges, long flowering seasons, high pollen production and naturally large populations can be used to illustrate these dynamics. Revealing and simulating species-specific demographic and stochastic elements in the flowering process will likely be important in determining when pollen release is likely to happen in flowering plants. Spatial and temporal dynamics of eight populations of Dactylis glomerata were collected over the course of two years to determine high-resolution demographic elements. Stochastic elements were accounted for using Markov chain approaches in order to evaluate tiller-specific contribution to overall population dynamics. Tiller-specific developmental dynamics were evaluated using three different RV matrix correlation coefficients. We found that the demographic patterns in population development were the same for all populations with key phenological events differing only by a few days over the course of the seasons. Many tillers transitioned very quickly from non-flowering to full flowering, a process that can be replicated with Markov chain modelling. Our novel approach demonstrates the identification and quantification of stochastic elements in the flowering process of D. glomerata, an element likely to be found in many flowering plants. The stochastic modelling approach can be used to develop detailed pollen release models for Dactylis, other grass species and probably other flowering plants.

Nonlinear Markov Chain Modelling of the Novel Coronavirus (Covid-19) Pandemic

Almost all countries around the world are struggling against the novel coronavirus (Covid-19) pandemic. In this paper, a nonlinear Markov chains model is proposed in order to analyse and to understand the behaviour of the Covid-19 pandemic. The data from China was used to build up the presented model. Thereafter, the nonlinear Markov chain model is employed to estimate the daily new Covid-19 cases in some countries including Italy, Spain, France, UK, the USA, Germany, Turkey, and Kuwait. In addition, the correlation between the daily new Covid-19 cases and the daily number of deaths is examined.

The Hidden Transition Paths During the Unfolding of Individual Peptides with a Confined Nanopore

A fundamental question in peptide folding/unfolding is how the peptide fleets through a set of transition states which dominate the dynamics of biomolecular folding path. Owing to their rapid duration and sub-nm structure difference, however, they have always been oversimplified because of limited instrumental resolution.^1-3 Moreover, the most experiments indicate a single fold pathway while the simulations suggest peptides owns the preference in multiple pathways. <a></a><a></a><a>Using the electrochemical confined effect of a solid-state nanopore, we measured the multiple transit paths of peptide inside nanopores. </a>Combining with Markov chain modelling, this new single-molecule technique is applied to clarify the 5 transition paths of the <a>β-hairpin </a>peptide which shows 4 nonequilibrium fluctuating stages. These results enable experimental access to previously obscured peptide dynamics which are essential to understand the misfolding in peptides. The statistical analysis of each peptide from high throughput shows that 78.5% of the peptide adopts the Pathways I during their folding/unfolding in a nanopore while 21.5% of the peptide undergoes the hidden folding/unfolding of transit Pathways II-IV. The frequency of the ionic fluctuation reveals a harmonic structure difference of the <a>metastable</a> peptide. Our results suggest the folding/unfolding of β-hairpin undergo four major structure vibrations which agree well with the theoretical expectation. These measurements provide a first look at the critical experiment picture of the mechanical folding/unfolding of a peptide, opening exciting avenues for the high <a></a><a>throughput</a> investigation of transition paths.