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Rational prediction of future CO 2 at the regional level is essential to the carbon emission reduction targets in China. The primary aim of this study is to examine the applicability of an up-to-date forecast algorithm, namely dynamic mode decomposition (DMD), in provincial CO 2 emission prediction. The testing results validate the accuracy and application value of the DMD short-run forecast, which may provide method reference for relevant policy formulation and research areas. Moreover, the 2020 provincial economic situation and CO 2 emissions in China are projected via DMD. On this basis, the unqualified provinces regarding CO 2 emission reduction are identified considering the relative standard and absolute standard, and the corresponding mitigation paths are proposed through decoupling analysis and shadow price calculation. The results indicate that the unqualified provinces include Heilongjiang, Gansu, Shanxi, Hebei, Liaoning, Jilin, Shaanxi, and Inner Mongolia. The open-emission-reduction mechanism should be adopted in the first five provinces; the conservative one should be applied in the other provinces. Graphical abstract

To achieve China’s determined contributions by 2030 and establish nationwide carbon emission trading system (ETS) which main participants are sectors, appropriated carbon emission allowance (CEA) allocation among sectors is crucial. In CEA distribution, fairness is primary; and sectoral efficiency is another significant factor. Nevertheless, considering fairness and efficiency while covering various sectors is a challengeable issue. Hence, combined with a new tow-objective data envelopment analysis (DEA) model and genetic algorithm (GA), a novel allocation framework is proposed, i.e., dual level allocation scheme incorporated with GA (DLA-GA). On the basis of evaluating the CO 2 emission performance of various sectors in China, the corresponding allocation steps are put forward. Through the value convergence and value repetition tests, the stability and feasibility of DLA-GA are justified. Then, the results of the DLA-GA and grandfathering principle are compared. The research shows that: (1) under the same constraint conditions, the emission right of CO 2 is allocated with DLA-GA, which leads to lower cost and higher overall sectoral performance; (2) through utilizing the En-Lorenz and En-Gini coefficients, it has found that higher allocation equity among sectors emerges via DLA-GA;(3) the key reduction sectors have been revealed through emission value estimation. This work may contribute to enrich the methodologies in CEA allocation at different dimensions, and provide some references for policymaker regarding the achievement of 2030 carbon reduction target.

Background Intercropping is often used in the tea producing areas where land resources are not so abundant, and the produced green tea is tasted more delicious through a tea-Chinese chestnut intercropping system according to the experience of indigenous farmers. The length and weight of tea leaf increase under this intercropping system and their root systems are stratified vertically and coordinate symbiosis. However, the delicacy mechanism under the intercropping is not fully understood. Results Green tea from the Chinese chestnut–tea intercropping system established in the 1980s ranked highest compared with a pure tea plantation from the same region. Based on the non-targeted metabolomics, 100 differential metabolites were upregulated in the tea leaves from intercropping system relative to monoculture system. Twenty-one amino acids were upregulated and three downregulated in response to the intercropping based on the targeted metabolomics; half of the upregulated amino acids had positive effects on the tea taste. Levels of allantoic acid, sugars, sugar alcohols, and oleic acid were higher and less bitter flavonoids in the intercropping system than those in monoculture system. The upregulated metabolites could promote the quality of tea and its health-beneficial health effects. Flavone and flavonol biosynthesis and phenylalanine metabolism showed the greatest difference. Numerous pathways associated with amino acid metabolism altered, suggesting that the intercropping of Chinese chestnut–tea could greatly influence amino acid metabolism in tea plants. Conclusions These results enhance our understanding of the metabolic mechanisms by which tea quality is improved in the Chinese chestnut–tea intercropping system and demonstrate that there is great potential to improve tea quality at the metabolomic level by adopting such an intercropping system.

At present, convolutional neural networks (CNN) have been widely used in building extraction from remote sensing imagery (RSI), but there are still some bottlenecks. On the one hand, there are so many parameters in the previous network with complex structure, which will occupy lots of memories and consume much time during training process. On the other hand, low-level features extracted by shallow layers and abstract features extracted by deep layers of artificial neural network cannot be fully fused, which leads to an inaccurate building extraction from RSI. To alleviate these disadvantages, a dense residual neural network (DR-Net) was proposed in this paper. DR-Net uses a deeplabv3+Net encoder/decoder backbone, in combination with densely connected convolution neural network (DCNN) and residual network (ResNet) structure. Compared with deeplabv3+net (containing about 41 million parameters) and BRRNet (containing about 17 million parameters), DR-Net contains about 9 million parameters; So, the number of parameters reduced a lot. The experimental results for both the WHU Building Dataset and Massachusetts Building Dataset, DR-Net show better performance in building extraction than other two state-of-the-art methods. Experiments on WHU building data set showed that Intersection over Union (IoU) increased by 2.4% and F1 score increased by 1.4%; in terms of Massachusetts Building Dataset, IoU increased by 3.8% and F1 score increased by 2.9%.

Plants intimately associate with diverse bacteria. Plant-associated bacteria have ostensibly evolved genes that enable them to adapt to plant environments. However, the identities of such genes are mostly unknown, and their functions are poorly characterized. We sequenced 484 genomes of bacterial isolates from roots of Brassicaceae, poplar, and maize. We then compared 3,837 bacterial genomes to identify thousands of plant-associated gene clusters. Genomes of plant-associated bacteria encode more carbohydrate metabolism functions and fewer mobile elements than related non-plant-associated genomes do. We experimentally validated candidates from two sets of plant-associated genes: one involved in plant colonization, and the other serving in microbe–microbe competition between plant-associated bacteria. We also identified 64 plant-associated protein domains that potentially mimic plant domains; some are shared with plant-associated fungi and oomycetes. This work expands the genome-based understanding of plant–microbe interactions and provides potential leads for efficient and sustainable agriculture through microbiome engineering. Comparative genomic analysis of 3,837 bacterial genomes, including new sequences from 484 root-associated isolates, identifies plant-associated gene clusters and plant-mimicking domains.

This work presents a novel type of soft reconfigurable mobile robot with multimodal locomotion, which is created using a controllable magneto-elastica-reinforced composite elastomer. The rope motor-driven method is employed to modulate magnetics–mechanics coupling effects and enable the magneto-elastica-reinforced elastomer actuator to produce controllable deformations. Furthermore, the 3D-printed magneto-elastica-reinforced elastomer actuators are assembled into several typical robotic patterns: linear configuration, parallel configuration, and triangular configuration. As a proof of concept, a few of the basic locomotive modes are demonstrated including squirming-type crawling at a speed of 1.11 mm/s, crawling with turning functions at a speed of 1.11 mm/s, and omnidirectional crawling at a speed of 1.25 mm/s. Notably, the embedded magnetic balls produce magnetic adhesion on the ferromagnetic surfaces, which enables the soft mobile robot to climb upside-down on ferromagnetic curved surfaces. In the experiment, the inverted ceiling-based inverted crawling speed is 2.17 mm/s, and the inverted freeform surface-based inverted crawling speed is 3.40 mm/s. As indicated by the experimental results, the proposed robot has the advantages of a simple structure, low cost, reconfigurable multimodal motion ability, and so on, and has potential application in the inspection of high-value assets and operations in confined environments.

• The lignin content of feedstock has been proposed as one key agronomic trait impacting biofuel production from lignocellulosic biomass. 4‐Coumarate:coenzyme A ligase (4CL) is one of the key enzymes involved in the monolignol biosynthethic pathway. • Two homologous 4CL genes, Pv4CL1 and Pv4CL2, were identified in switchgrass (Panicum virgatum) through phylogenetic analysis. Gene expression patterns and enzymatic activity assays suggested that Pv4CL1 is involved in monolignol biosynthesis. Stable transgenic plants were obtained with Pv4CL1 down‐regulated. • RNA interference of Pv4CL1 reduced extractable 4CL activity by 80%, leading to a reduction in lignin content with decreased guaiacyl unit composition. Altered lignification patterns in the stems of RNAi transgenic plants were observed with phloroglucinol‐HCl staining. The transgenic plants also had uncompromised biomass yields. After dilute acid pretreatment, the low lignin transgenic biomass had significantly increased cellulose hydrolysis (saccharification) efficiency. • The results demonstrate that Pv4CL1, but not Pv4CL2, is the key 4CL isozyme involved in lignin biosynthesis, and reducing lignin content in switchgrass biomass by silencing Pv4CL1 can remarkably increase the efficiency of fermentable sugar release for biofuel production.

The plastic elongation of mesocotyl (MES) and coleoptile (COL), which can be repressed by light exposure, plays a vital role in maize seedling emergence and establishment under adverse environmental conditions. Understanding the molecular mechanisms of light-mediated repression of MES and COL elongation in maize will allow us to develop new strategies for genetic improvement of these two crucial traits in maize. A maize variety, Zheng58, was used to monitor the transcriptome and physiological changes in MES and COL in response to darkness, as well as red, blue, and white light. The elongation of MES and COL was significantly inhibited by light spectral quality in this order: blue light > red light > white light. Physiological analyses revealed that light-mediated inhibition of maize MES and COL elongation was closely related to the dynamics of phytohormones accumulation and lignin deposition in these tissues. In response to light exposure, the levels of indole-3-acetic acid, trans-zeatin, gibberellin 3, and abscisic acid levels significantly decreased in MES and COL; by contrast, the levels of jasmonic acid, salicylic acid, lignin, phenylalanine ammonia-lyase, and peroxidase enzyme activity significantly increased. Transcriptome analysis revealed multiple differentially expressed genes (DEGs) involved in circadian rhythm, phytohormone biosynthesis and signal transduction, cytoskeleton and cell wall organization, lignin biosynthesis, and starch and sucrose metabolism. These DEGs exhibited synergistic and antagonistic interactions, forming a complex network that regulated the light-mediated inhibition of MES and COL elongation. Additionally, gene co-expression network analysis revealed that 49 hub genes in one and 19 hub genes in two modules were significantly associated with the elongation plasticity of COL and MES, respectively. These findings enhance our knowledge of the light-regulated elongation mechanisms of MES and COL, and provide a theoretical foundation for developing elite maize varieties with improved abiotic stress resistance.

How does the economy of China and Japan interact with each other? Through building vector autoregression (VAR) model, this study examines the transmission mechanism of economic synchronization among the two nations from three perspectives, namely foreign direct investment (FDI), bilateral trade, and political relation. Based on this, relevant stabilizing measures for China’s economy are proposed. The findings of this study are as follows: (a) There exists business cycle co-movement between China and Japan. (b) The transmission mechanism of this co-movement contains bilateral trade and FDI. Therein, import contributes the most to China’s economic fluctuation, which is followed by FDI and export. (c) Bilateral political relation exerts indirect influence on China-Japan economic synchronization. (d) The impact of Japan’s economic fluctuations on the economy of China would be mitigated by expanding international trade markets, reducing financial market access restrictions, strengthening the political mutual trust, and encouraging communications between China and Japan in science, technology, and education, etc.

The digestibility of soybean meal can be severely impacted by trypsin inhibitor (TI), one of the most abundant anti-nutritional factors present in soybean seeds. TI can restrain the function of trypsin, a critical enzyme that breaks down proteins in the digestive tract. Soybean accessions with low TI content have been identified. However, it is challenging to breed the low TI trait into elite cultivars due to a lack of molecular markers associated with low TI traits. We identified Kunitz trypsin inhibitor 1 ( KTI1 , Gm01g095000) and KTI3 (Gm08g341500) as two seed-specific TI genes. Mutant kti1 and kti3 alleles carrying small deletions or insertions within the gene open reading frames were created in the soybean cultivar Glycine max cv. Williams 82 ( WM82 ) using the CRISPR/Cas9-mediated genome editing approach. The KTI content and TI activity both remarkably reduced in kti1/3 mutants compared to the WM82 seeds. There was no significant difference in terms of plant growth or maturity days of kti1 / 3 transgenic and WM82 plants in greenhouse condition. We further identified a T1 line, #5-26, that carried double homozygous kti1/3 mutant alleles, but not the Cas9 transgene. Based on the sequences of kti1 / 3 mutant alleles in #5-26, we developed markers to co-select for these mutant alleles by using a gel-electrophoresis-free method. The kti1 / 3 mutant soybean line and associated selection markers will assist in accelerating the introduction of low TI trait into elite soybean cultivars in the future.