Transcription factors play crucial roles in patterning posterior neuroectoderm. Previously, zinc finger transcription factor was reported to be expressed in the posterior neuroectoderm of zebrafish embryos. However, its roles remain unknown. Here, we report that there are 13 copies of in the zebrafish genome, and all the paralogues share highly identical protein sequences and cDNA sequences. When are knocked down using a morpholino to inhibit their translation or dCas9-Eve to inhibit their transcription, the zebrafish gastrula displays reduced expression of, the marker gene for the posterior neuroectoderm. Further analyses reveal that diminishing produces the decreased expressions of, whereas overexpression of effectively rescues the reduced expression of in the posterior neuroectoderm. Additionally, knocking down causes the reduced expression of, a direct regulator of , in the posterior neuroectoderm, and overexpression of rescues the expression of in the knockdown embryos. In contrast, knocking down either or does not affect the expressions of Taken together, our results demonstrate that zebrafish control the expression of in the posterior neuroectoderm by acting upstream of and .
Aiming at the application of the geographical conditions monitoring data in the results of the third national land resource survey, this paper proposes a comparison and fusion model of the third national land resource survey and the geographical conditions monitoring based on regression analysis. This study analyses the reasons for the differences between the two groups of data, and formulates the fusion rules, and takes Jieshou city as the study area to carry out experiments. We randomly selected sample areas for fusion experiments to obtain statistical data, consider the relationship between the fused cultivated land area (Y) and the cultivated land overlapping area ( x1 ), and the cultivated land difference area ( x2 ), and established a regression equation. The model can solve the problem of the difference between the data of the third national land resource survey and the geographical conditions monitoring, and realize the effective integration of cultivated land types. Based on the regression analysis method, the regression equation of cultivated land area after the integration of Jieshou city is obtained. The model proposed in this paper can not only effectively connect the third national land resource survey data with the geographical conditions monitoring data, but also scientifically and accurately predict the area of cultivated land in Jieshou city. The research results can provide technical support for the distribution of cultivated land quality monitoring points, land environmental protection, land management, etc.
The particle system is widely used in vector field feature visualization due to its dynamics and simulation. However, there are some defects of the vector field visualization method based on the Euler fields, such as unclear feature expression and discontinuous temporal expression, so the method cannot effectively express the characteristics of wind field on the temporal scale. We propose a Lagrangian visualization method based on spatio-temporal interpolation to solve these problems, which realizes the fusion and expression of the particle system and the time-varying wind data based on the WebGL shader. Firstly, the linear interpolation algorithm is used to interpolate to obtain continuous and dense wind field data according to the wind field data at adjacent moments. Then, we introduce the Lagrangian analysis method to study the structure of the wind field and optimize the visualization effect of the particle system based on Runge–Kutta algorithms. Finally, we adopt the nonlinear color mapping method with double standard deviation (2SD) to improve the expression effect of wind field features. The experimental results indicate that the wind visualization achieves a comprehensive visual effect and the rendering frame rate is greater than 45. The methods can render the particles smoothly with stable and outstanding uniformity when expressing continuous spatio-temporal dynamic visualization characteristics of the wind field.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.