The explosive success of graphene opens a new era of ultrathin 2D materials. It has been realized that the van der Waals layered materials with atomic and less atomic thickness can not only exist stably, but also exhibit unique and technically useful properties including small size effect, surface effect, macro quantum tunnel effect, and quantum effect. With the extensive research and revealing of the basic optical properties and new photophysical properties of 2D materials, a series of potential applications in optical devices have been continuously demonstrated and realized, which immediately roused an upsurge of study in the academic circle. Therefore, the application of 2D materials as broadband, efficient, convenient, and versatile saturable absorbers in ultrafast lasers is a potential and promising field. Herein, the main preparation methods of 2D materials are reviewed and technical guidelines for identifying and characterizing layered 2D materials are provided. After investigating the characteristics of 2D materials thoroughly in nonlinear optics, their performances in fiber lasers are comprehensively summarized according to the types of materials. Finally, some developmental challenges, potential prospects, and future research directions are summarized and presented for such promising materials.
Variable‐gain nonlinearity is a piecewise‐linear characteristic to describe the process with different gains in different input regions. This article studies the parameter estimation issue of the input nonlinear controlled autoregressive moving average system with variable‐gain nonlinearity. Through introducing a suitable switching function, we describe the variable‐gain nonlinearity by a linear‐in‐parameter form and derive the identification model of the system. Based on the obtained identification model, a maximum likelihood extended stochastic gradient algorithm is presented to estimate the unknown parameters. To make sufficient use of the observation data and improve the identification accuracy, we deduce a maximum likelihood (multiinnovation) extended gradient‐based iterative algorithm by using the maximum likelihood principle. An extended gradient‐based iterative algorithm is given for comparison. A simulation example is employed to validate that the proposed algorithms can effectively identify the unknown parameters and the maximum likelihood extended gradient‐based iterative algorithm has better estimation accuracy and fitting performance than the maximum likelihood extended stochastic gradient algorithm and the extended gradient‐based iterative algorithm.
Predictable, clean genetic modification (GM) in livestock is important for reliable phenotyping and biosafety. Here we reported the generation of isozygous, functional myostatin (MSTN) knockout cloned pigs free of selectable marker gene (SMG) by CRISPR/Cas9 and Cre/LoxP. CRISPR/Cas9-mediated homologous recombination (HR) was exploited to knock out (KO) one allele of MSTN in pig primary cells. Cre recombinase was then used to excise the SMG with an efficiency of 82.7%. The SMG-free non-EGFP cells were isolated by flow cytometery and immediately used as donor nuclei for nuclear transfer. A total of 685 reconstructed embryos were transferred into three surrogates with one delivering two male live piglets. Molecular testing verified the mono-allelic MSTN KO and SMG deletion in these cloned pigs. Western blots showed approximately 50% decrease in MSTN and concurrent increased expression of myogenic genes in muscle. Histological examination revealed the enhanced myofiber quantity but myofiber size remained unaltered. Ultrasonic detection showed the increased longissimus muscle size and decreased backfat thickness. Precision editing of pig MSTN gene has generated isozygous, SMG-free MSTN KO cloned founders, which guaranteed a reliable route for elite livestock production and a strategy to minimize potential biological risks.
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