Oxygen-enriched combustion mechanism of lignite

In this work, thermogravimetric experiments were carried out in a thermogravi-metric analyzer under O2/N2 atmosphere with an oxygen content ranging from 21 vol.% to 70 vol.%. Malek method combined with iso-conversional method and non-isothermal method was employed to determine the burning dynamical function of lignite in high temperature burning region with different oxygen concentrations. The results indicated that the lignite has different burning dynamical function in different oxygen conditions. The combustion mechanism function of lignite belonged to 3-D model when the oxygen concentration is below 30%. The combustion mechanism of lignite belongs to a random successive nucleation growth model when the oxygen concentration is between 40% and 50%. Kinetic burning model of lignite in high burning temperature region with different oxygen concentrations was established. The kinetic parameters were obtained from the kinetic burning model of lignite using Kissinger-Akah-Sunose method.

A macaque connectome for large-scale network simulations in TheVirtualBrain

Models of large-scale brain networks that are informed by the underlying anatomical connectivity contribute to our understanding of the mapping between the structure of the brain and its dynamical function. Connectome-based modelling is a promising approach to a more comprehensive understanding of brain function across spatial and temporal scales, but it must be constrained by multi-scale empirical data from animal models. Here we describe the construction of a macaque connectome for whole-cortex simulations in TheVirtualBrain, an open-source simulation platform. We take advantage of available axonal tract-tracing datasets and enhance the existing connectome data using diffusion-based tractography in macaques. We illustrate the utility of the connectome as an extension of TheVirtualBrain by simulating resting-state BOLD-fMRI data and fitting it to empirical resting-state data.

Single-cell transcriptomics reveals a new dynamical function of transcription factors during embryonic hematopoiesis

Recent advances in single-cell transcriptomics techniques have opened the door to the study of gene regulatory networks (GRNs) at the single-cell level. Here, we studied the GRNs controlling the emergence of hematopoietic stem and progenitor cells from mouse embryonic endothelium using a combination of single-cell transcriptome assays. We found that a heptad of transcription factors (Runx1, Gata2, Tal1, Fli1, Lyl1, Erg and Lmo2) is specifically co-expressed in an intermediate population expressing both endothelial and hematopoietic markers. Within the heptad, we identified two sets of factors of opposing functions: one (Erg/Fli1) promoting the endothelial cell fate, the other (Runx1/Gata2) promoting the hematopoietic fate. Surprisingly, our data suggest that even though Fli1 initially supports the endothelial cell fate, it acquires a pro-hematopoietic role when co-expressed with Runx1. This work demonstrates the power of single-cell RNA-sequencing for characterizing complex transcription factor dynamics.

Residue Geometry Networks: A Rigidity-Based Approach to the Amino Acid Network and Evolutionary Rate Analysis

Amino acid networks (AANs) abstract the protein structure by recording the amino acid contacts and can provide insight into protein function. Herein, we describe a novel AAN construction technique that employs the rigidity analysis tool, FIRST, to build the AAN, which we refer to as the residue geometry network (RGN). We show that this new construction can be combined with network theory methods to include the effects of allowed conformal motions and local chemical environments. Importantly, this is done without costly molecular dynamics simulations required by other AAN-related methods, which allows us to analyse large proteins and/or data sets. We have calculated the centrality of the residues belonging to 795 proteins. The results display a strong, negative correlation between residue centrality and the evolutionary rate. Furthermore, among residues with high closeness, those with low degree were particularly strongly conserved. Random walk simulations using the RGN were also successful in identifying allosteric residues in proteins involved in GPCR signalling. The dynamic function of these residues largely remain hidden in the traditional distance-cutoff construction technique. Despite being constructed from only the crystal structure, the results in this paper suggests that the RGN can identify residues that fulfil a dynamical function.

Dynamic Stability Analysis of Defective Piles under Vertical Harmonic Load

We established the computational mode for defective piles based on practical engineering problems,and studied the stability of the defective pile in the heterogeneous soil under vertical harmonic loads. We established the dynamical function based on the principle of Energy and Hamilton, and abtained the expressions of critical frequency of defective piles.The results show that, the instability of the defective piles relate to the degree of defect and the location of defect.