The influence mechanism of industrial policies on Chinese companies' cross-border M&A decision-making.

This study explored the potential links between Chinese industrial policy and cross-border mergers and acquisitions by Chinese firms from 2009 to 2019. Based on describing China's industrial strategy and evaluating the then-current situation of Chinese enterprises' cross-border mergers and acquisitions, this empirical study constructed a two-way fixed-effect panel model and an intermediate effect model to assess the mechanism of industrial policy's influence on Chinese enterprises' cross-border mergers and acquisitions decisions. The findings were as follows: (1) Industrial policy could promote the implementation of cross-border mergers and acquisitions of Chinese enterprises; (2) By easing financial restrictions, industrial policy could improve firms' access to capital and encourage cross-border mergers and acquisitions. (3) Industrial policies could promote the high political relevance of state-owned enterprises, thus promoting the success of transnational mergers and acquisitions of enterprises. Therefore, it was significant to promote the transformation of industrial policy from subsidy-oriented to performance-oriented and rationally evaluate the risks and benefits of M&A for enterprises to complete cross-border M&A.

Robust quasi-uniform surface meshing of neuronal morphology using line skeleton-based progressive convolution approximation.

Creating high-quality polygonal meshes which represent the membrane surface of neurons for both visualization and numerical simulation purposes is an important yet nontrivial task, due to their irregular and complicated structures. In this paper, we develop a novel approach of constructing a watertight 3D mesh from the abstract point-and-diameter representation of the given neuronal morphology. The membrane shape of the neuron is reconstructed by progressively deforming an initial sphere with the guidance of the neuronal skeleton, which can be regarded as a digital sculpting process. To efficiently deform the surface, a local mapping is adopted to simulate the animation skinning. As a result, only the vertices within the region of influence (ROI) of the current skeletal position need to be updated. The ROI is determined based on the finite-support convolution kernel, which is convolved along the line skeleton of the neuron to generate a potential field that further smooths the overall surface at both unidirectional and bifurcating regions. Meanwhile, the mesh quality during the entire evolution is always guaranteed by a set of quasi-uniform rules, which split excessively long edges, collapse undersized ones, and adjust vertices within the tangent plane to produce regular triangles. Additionally, the local vertices density on the result mesh is decided by the radius and curvature of neurites to achieve adaptiveness.

Rapid detection of acute myocardial infarction-related miRNA based on a Capture-interCalation-electroCatalysis (3C) strategy.

Acute myocardial infarction (AMI) is one of the most urgent and serious diseases that may cause cardiac death in a few hours. Rapid diagnosis of AMI is the pre-requisite for timely interventions. Recently, several specific circulating miRNAs have been proven to have high correlation with AMI. To adopt miRNA as a biomarker may improve the diagnostic accuracy. However, it is a pity that the current available methods for the detection of miRNA usually require a few hours, which is too long for the diagnosis of AMI. In this paper, by adopting a capture DNA, an electrochemical active intercalator and an unimmobilized enzyme, we develop a Capture-interCalation-electroCatalysis (3C) strategy for the rapid detection of AMI-related miRNA. The whole detection process can be completed in 35 min, which is much shorter than most current methods and is acceptable for the diagnosis of AMI. This strategy also shows favorable sensitivity and selectivity, thus provides an alternative for the detection of miRNA. Most importantly, this effort may promote miRNA to work as an effective biomarker in the diagnosis of AMI.

Detection of microRNA SNPs with ultrahigh specificity by using reduced graphene oxide-assisted rolling circle amplification.

Here we report a reduced graphene oxide-assisted rolling circle amplification for the detection of miRNA SNPs. The difference of the signal of a miRNA SNP reaches 100 fold, a value over 10 times larger than some current methodologies, which allows the discrimination of a SNP even with the naked eye.

An ATP-responsive smart gate fabricated with a graphene oxide-aptamer-nanochannel architecture.

Here, we report a graphene oxide-aptamer-nanochannel architecture for the fabrication of a novel stimuli-responsive gate. The gate is switched OFF in the absence of ATP, and is switched ON when ATP is present. The concept we proposed may contribute to a versatile platform for the development of stimuli-responsive gates.