Strong Seedlings of Improved Varieties and High-efficiency Cultivation of Artificial Forests Promotes the Early Realization of"Carbon Neutrality"

China is striving to achieve"carbon dioxide peaking"in 2030 and"carbon neutrality"in 2060.In addition to optimizing and upgrading the industrial structure and increasing industrial emission reduction,afforestation is an important way to increase forest carbon sinks and achieve carbon dioxide peaking and carbon neutrality.Improved seedlings are significantly better than general seedlings in terms of afforestation adaptability,growth and stress resistance.The use of improved varieties for afforestation can improve the quality of afforestation from the source.Although the growth cycle of economical tree species is short,and the carbon storage does not increase after directional cultivation,they significantly improve the quality and yield,and indirectly reduce carbon emissions compared with ordinary seedlings.Therefore,in agricultural and forestry production,the transformation and utilization efficiency of improved varieties should be improved and the planting structure should be optimized to improve the quality and efficiency and significantly improve the yield and carbon storage,and the management of plantations should be strengthened to help achieve the goal of"carbon neutrality"as soon as possible.This paper analyzed the current situation of improved varieties and plantation management in China,and put forward corresponding countermeasures.

Current advances of transition metal dichalcogenides in electromagnetic wave absorption:A brief review

Transition metal dichalcogenides(TMDs)show great advantages in electromagnetic wave(EMW)absorption due to their unique structure and electrical properties.Tremendous research works on TMD-based EMW absorbers have been conducted in the last three years,and the comprehensive and systematical summary is still a rarity.Therefore,it is of great significance to elaborate on the interaction among the morphologies,structures,phases,components,and EMW absorption performances of TMD-based absorbers.This review is devoted to analyzing TMD-based absorbers from the following perspectives:the EMW absorption regulation strategies of TMDs and the latest progress of TMD-based hybrids as EMW absorbers.The absorption mechanisms and component-performance dependency of these achievements are also summarized.Finally,a straightforward insight into industrial revolution upgrading in this promising field is proposed.

Water Model Study of Level Flunction in Continuous Casting Mold

Using 0.6-scale warer modelling based on Fr-We number similitude criteria, the influences of the submerged entry nozzle configuration and operating practices on the level fluctuation in the mold which caused surface defects and mold power catching, were studied. It was found that the level flunction was resulted from gas injection, impacting of the stream and standing wave. The level turblence raises with the incresing of the gas injection, however the casting rate, immersion depth and jet angel of SEN have a dual influenc on the level fluctuation.

Morphological and molecular identification of Xylocoris flavipes(Hemiptera:Anthocoridae)in southern China

During the investigation of natural enemy insects in grain depots,we've found an Anthocoridae insect accounted for a high proportion of natural enemy insects.We identify the enemy insects from morphology and molecular biology,so as to realize more accurate and effective control of storage pests by using the enemy insect.The images of the insects under the ultra-depth microscope(VHX-5000)showed that the insect adults were black brown in colour;the antennas of both the female and male had four segments,which increase in length sequentially from the base to the end,and had a length of 756.2μm for the female and 741.1μm for the male.The rostrums of both the female and the male insects were composed of three segments,the male's rostrum(596.8μm)were shorter than the female's(734.6μm),and the former two segments of the female's rostrum were significantly longer than the male's.The abdomen of the insect was bilaterally symmetrical,the female's abdomen was wider than the male,and the male insect had a dent between its eighth and ninth segments of the left abdomen,in which its male genitalia was located.In addition,the nymphs as a whole were tangerine in colour,and the eggs were elliptic with creamy white gloss and gridding patterns on the surface.The cytochrome C oxidase I(COI)gene sequences of the insects were identified by DNA barcoding technique,and the determined COI sequences were then submitted to the Genbank database for Blast alignment,and the results showed that the COI gene sequences had a high degree of similarity(99%)with X.flavipes records in the Genbank database.Therefore,we could determine that the insect was X.flavipes.In addition,the neighbor joining(NJ)was used to construct the evolutionary tree,and 1,000 repeated tests were conducted on the confidence levels of each branch.Based on the phylogenetic tree,we've found that X.flavipes belongs to Xylocoris genus.Based on morphology and COI sequence identification,we confidentiy determined that the collected natural enemy insect was X.flavipes.This is the first time that the identification of X.flavipes is being investigated from morphology and molecular biology.The research results are helpful to identify and distinguish the species of flower bugs,and beneficial for the better application of X.flavipes in biological control.

DeepCBA:A deep learning framework for gene expression prediction in maize based on DNA sequences and chromatin interactions

Chromatin interactions create spatial proximity between distal regulatory elements and target genes in the genome,which has an important impact on gene expression,transcriptional regulation,and phenotypic traits.To date,several methods have been developed for predicting gene expression.However,existing methods do not take into consideration the effect of chromatin interactions on target gene expression,thus potentially reducing the accuracy of gene expression prediction and mining of important regulatory elements.In this study,we developed a highly accurate deep learning-based gene expression prediction model(DeepCBA)based on maize chromatin interaction data.Compared with existing models,DeepCBA exhibits higher accuracy in expression classification and expression value prediction.The average Pearson correlation coefficients(PCCs)for predicting gene expression using gene promoter proximal interactions,proximaldistal interactions,and both proximal and distal interactions were 0.818,0.625,and 0.929,respectively,representing an increase of 0.357,0.16,and 0.469 over the PCCs obtained with traditional methods that use only gene proximal sequences.Some important motifs were identified through DeepCBA;they were enriched in open chromatin regions and expression quantitative trait loci and showed clear tissue specificity.Importantly,experimental results for the maize flowering-related gene ZmRap2.7 and the tillering-related gene ZmTb1 demonstrated the feasibility of DeepCBA for exploration of regulatory elements that affect gene expression.Moreover,promoter editing and verification of two reported genes(ZmCLE7 and ZmVTE4)demonstrated the utility of DeepCBA for the precise design of gene expression and even for future intelligent breeding.DeepCBA is available at http://www.deepcba.com/or http://124.220.197.196/.

Application of deep learning in genomics

In recent years, deep learning has been widely used in diverse fields of research, such as speech recognition, image classification,autonomous driving and natural language processing. Deep learning has showcased dramatically improved performance in complex classification and regression problems, where the intricate structure in the high-dimensional data is difficult to discover using conventional machine learning algorithms. In biology, applications of deep learning are gaining increasing popularity in predicting the structure and function of genomic elements, such as promoters, enhancers, or gene expression levels. In this review paper, we described the basic concepts in machine learning and artificial neural network, followed by elaboration on the workflow of using convolutional neural network in genomics. Then we provided a concise introduction of deep learning applications in genomics and synthetic biology at the levels of DNA, RNA and protein. Finally, we discussed the current challenges and future perspectives of deep learning in genomics.