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The response of microbiomes to salinity has been clarified in different geographic scales or ecosystems. However, how soil microbial community structure and interaction respond to salinity across wide salinity range and climatic region is still unclearly resolved. To address this issue, we examined the microbial community’s composition in saline soils from two climatic regions (coastal wetland and arid desert). Our research confirms that soil salinity had a negative effect on soil nutrient content. Salinity decreased the relative abundance of bacteria, but increased archaea abundance, leading to the shifts from bacteria dominant community to archaea dominant community. Low-water medium-salinity soil (LWMS) had the most complex archaeal community network, whereas for bacteria, the most complex bacterial community network was observed in low-water high-salinity soils (LWHS). Key microbial taxa differed in three salinity gradients. Salinity, soil water content, pH, total nitrogen (TN), and soil organic carbon (SOC) were the main driving factors for the composition of archaeal and bacterial community. Salinity directly affected archaeal community, but indirectly influenced bacteria community through SOC; pH affected archaeal community indirectly through TN, but directly affected bacterial community. Our study suggests that soil salinity dramatically influences diversity, composition, and interactions within the microbial community.

Background Carbon dots (CDs), an emerging class of nanomaterials, have shown great potential to modulate plant growth and development. However, the underlying molecular mechanisms and gene regulatory networks through which CDs influence physiological processes remain largely unexplored, limiting their application in agriculture. Results In this study, citric acid was used to synthesis CDs by microwave-assisted method. Here, we treat cotton leaves with different concentrations of CDs to study their effects on cotton growth and development. The findings demonstrated that, at appropriate doses, CDs could enhance cotton biomass accumulation, with concurrent increases in fresh and dry weights. At 100 mg·L − 1 , cotton exhibited optimal morphological performance: the aboveground biomass showed increases of 67.69% and 42.89% in fresh and dry weight, respectively. In addition, the belowground biomass displayed 34.48% and 46.65% increments, respectively. CDs-mediated increases in chlorophyll content and photosynthetic enzyme activities, together with improvements in photosystem performance, suggest that CDs likely enhance photosynthetic efficiency in cotton and thereby promote growth. Moreover, CDs strengthened the antioxidant defense system primarily by enhancing the activities of key enzymes (SOD and POD), despite a concurrent decrease in CAT activity. To elucidate the molecular basis underlying the observed physiological responses, RNA-sequencing (RNA-seq) was performed to provide deeper insights into the gene expression profiles associated with CD-mediated growth. In summary, transcriptomic analysis revealed that CDs significantly enriched the ‘photosynthesis-antenna proteins’ pathway, where Lhcb1 (light-harvesting complex II chlorophyll a/b binding protein 1), Lhcb2 (light-harvesting complex II chlorophyll a/b binding protein 2) and Lhcb3 (light-harvesting complex II chlorophyll a/b binding protein 3) were significantly up-regulated, and the ‘flavone and flavonol biosynthesis’ pathway, involving the up-regulation of F3′5′H (flavonoid 3’,5’-hydroxylase). These molecular findings are highly consistent with the physiological data, demonstrating that CDs promote cotton growth by enhancing light-harvesting efficiency and antioxidant defense systems. Conclusions By integrating transcriptomic profiling with physiological measurements, this study elucidates the molecular pathways by which citric acid–based CDs enhance photosynthesis and antioxidant capacity in cotton. Our findings provide a mechanistic basis for the use of CDs to optimize crop production.

Exploring the structural characteristics of arid soil microbial communities and their assembly mechanisms is important for understanding the ecological characteristics of arid zone soils and promoting ecological restoration. In this study, we used Illumina high-throughput sequencing technology to study soils in the arid zone of the Lake Ebinur basin, determined the differences among soil microbial community structures in the study area under different water–salt gradients, and investigated the effects of environmental factors on microbial community structure and assembly mechanisms. The results show the following: the microbial community alpha diversity exhibited a significantly higher low water–salt gradient (L) than high water–salt gradient (H) and medium water–salt gradient (M). The pH was most strongly correlated with soil microbial community structure, where the alpha diversity indices of the bacterial community and fungal community were significantly negatively correlated with pH, and the Bray–Curtis distance of bacterial community was significantly positively correlated with pH (p < 0.05). The complexity of bacterial community co-occurrence networks showed a significantly higher L than H and M, and the complexity of fungal community co-occurrence network showed a significantly lower L than H and M. The cooperative relationship of H and M in the co-occurrence networks was stronger than that of the L, and the key species of the microbial co-occurrence network were different under different water–salt gradients. Stochastic processes dominated the assembly mechanism of the microbial community structure of soil, and the explanation rates of deterministic and stochastic processes were different under different water–salt gradients, with the highest explanation rate of stochastic processes on the L accounting for more than 90%. In summary, the soil microbial community structure and assembly mechanisms significantly differed across water–salt gradients, and these findings can help provide a reference for further research on soil microbiology in arid zones.

The formation of secondary cell walls in cell types such as tracheary elements and fibers is a defining characteristic of vascular plants. The Arabidopsis transcription factor KNAT7 is a component of a transcription network that regulates secondary cell wall biosynthesis, but its function has remained unclear. We conducted anatomical, biochemical and molecular phenotypic analyses of Arabidopsis knat7 loss-of-function alleles, KNAT7 over-expression lines and knat7 lines expressing poplar KNAT7. KNAT7 was strongly expressed in concert with secondary wall formation in Arabidopsis and poplar. Arabidopsis knat7 loss-of-function alleles exhibited irregular xylem phenotypes, but also showed increased secondary cell wall thickness in fibers. Increased commitment to secondary cell wall biosynthesis was accompanied by increased lignin content and elevated expression of secondary cell wall biosynthetic genes. KNAT7 over-expression resulted in thinner interfascicular fiber cell walls. Taken together with data demonstrating that KNAT7 is a transcriptional repressor, we hypothesize that KNAT7 is a negative regulator of secondary wall biosynthesis, and functions in a negative feedback loop that represses metabolically inappropriate commitment to secondary wall formation, thereby maintaining metabolic homeostasis. The conservation of the KNAT7 regulatory module in poplar suggests new ways to manipulate secondary cell wall deposition for improvement of bioenergy traits in this tree.

BLADE-ON-PETIOLE ( BOP ) genes are essential regulators of vegetative and reproductive development in land plants. First characterized in Arabidopsis thaliana (Arabidopsis), members of this clade function as transcriptional co-activators by recruiting TGACG-motif binding (TGA) basic leucine zipper (bZIP) transcription factors. Highly expressed at organ boundaries, these genes are also expressed in vascular tissue and contribute to lignin biosynthesis during secondary growth. How these genes function in trees, which undergo extensive secondary growth to produce wood, remains unclear. Here, we investigate the functional conservation of BOP orthologs in Populus trichocarpa (poplar), a widely-used model for tree development. Within the poplar genome, we identified two BOP -like genes, PtrBPL1 and PtrBPL2 , with abundant transcripts in stems. To assess their functions, we used heterologous assays in Arabidopsis plants. The promoters of PtrBPL1 and PtrBPL2 , fused with a β-glucuronidase (GUS) reporter gene showed activity at organ boundaries and in secondary xylem and phloem. When introduced into Arabidopsis plants, PtrBPL1 and PtrBPL2 complemented leaf and flower patterning defects in bop1 bop2 mutants. Notably, Arabidopsis plants overexpressing PtrBPL1 and PtrBPL2 showed defects in stem elongation and the lignification of secondary tissues in the hypocotyl and stem. Finally, PtrBPL1 and PtrBPL2 formed complexes with TGA bZIP proteins in yeast. Collectively, our findings suggest that PtrBPL1 and PtrBPL2 are orthologs of Arabidopsis BOP1 and BOP2, potentially contributing to secondary growth regulation in poplar trees. This work provides a foundation for functional studies in trees.

Throughout their lifetimes, plants must coordinate the regulation of various facets of growth and development. Previous evidence has suggested that the Arabidopsis thaliana R2R3-MYB, AtMYB61, might function as a coordinate regulator of multiple aspects of plant resource allocation. Using a combination of cell biology, transcriptome analysis and biochemistry, in conjunction with gain-of-function and loss-of-function genetics, the role of AtMYB61 in conditioning resource allocation throughout the plant life cycle was explored. In keeping with its role as a regulator of resource allocation, AtMYB61 is expressed in sink tissues, notably xylem, roots and developing seeds. Loss of AtMYB61 function decreases xylem formation, induces qualitative changes in xylem cell structure and decreases lateral root formation; in contrast, gain of AtMYB61 function has the opposite effect on these traits. AtMYB61 coordinates a small network of downstream target genes, which contain a motif in their upstream regulatory regions that is bound by AtMYB61, and AtMYB61 activates transcription from this same motif. Loss-of-function analysis supports the hypothesis that AtMYB61 targets play roles in shaping subsets of AtMYB61-related phenotypes. Taken together, these findings suggest that AtMYB61 links the transcriptional control of multiple aspects of plant resource allocation.

The worsening of environmental pollution has compelled industrial organizations to implement improvements across the board and work to inspire staff to engage in active green behavior. However, the majority of recent studies are restricted to a certain perspective, and there is a dearth of study on the variables influencing employees’ green behavior in general. This research is grounded in a comprehensive viewpoint. Experts evaluate the relevant aspects using fuzzy language, and they combine their individual judgements using the central ordered weighted operator to get a more scientific conclusion. The outcomes of expert judgment are then examined using a variety of analytical techniques, including decision-making trail and evaluation laboratory method, interpretative structural model, and MICMAC Matrix, to identify the critical variables that influence employees’ adoption of environmentally friendly behavior. The findings indicate that the most important variables impacting workers’ green behavior are employee motivation, values, and responsible leadership. The attitudes, practices, and leadership philosophies of leaders regarding green conduct have an impact on employee motivation and values. The enterprise’s sustainable development idea is also shown to be impacted by leaders’ attitudes toward green conduct in a number of other areas, including the organizational environment, organizational and human resource management, and other areas. All of these elements have an impact on employees’ values and drive to adopt green practices, either internally or outside. This research can assist businesses in identifying the critical influencing elements that impact workers’ green behavior and provide focused recommendations to enhance employee green behavior.

In the era of digital economy, the digital innovation of manufacturing enterprises has become the main trend of development. This paper constructs an effective and reliable hierarchical framework for identifying critical factors of digital innovation in manufacturing enterprises based on the three stage hybrid DEMATEL–ISM–MICMAC method. Through literature reading and expert judgment, this paper determines the 19 factors that affect the digital innovation of manufacturing enterprises. The DEMATEL technique is used to establish the causal relationship between the factors, the ISM technique is used to stratify the factors, and the MICMAC technique is used to divide the types of influencing factors according to the driving force and dependence, and analyze the correlation between each level and its influence on the digital innovation of manufacturing enterprises. The results show that social capital, learning organization, digital technology, and knowledge are the most important influencing factors in the process of digital innovation in manufacturing enterprises. In particular, the two key factors of social capital and learning organization should be paid attention to by manufacturing enterprises. This research can help the managers of manufacturing enterprises to find out the key influencing factors of the digital innovation of manufacturing enterprises, and give targeted suggestions to promote the process of enterprise digitalization.

Large cable shovel (LCS) is a complex engineering machine which is widely used in the open pit mine. It is characterized by low efficiency, high maintenance cost, and high energy consumption if manipulated by an inexperienced operator. To address these challenges, intelligentization could be a feasible solution. In this work, an intelligent excavation system is put forward and the corresponding energy-minimum optimization through trajectory planning of the optimal excavation is developed to realize the intelligentization of the LCS. Firstly, the excavating resistance acting on the dipper is modeled and the corresponding forces are analyzed. Then, by establishing the kinetics and dynamic models of the excavating process, the point to point (PTP) trajectory planning method is developed by setting the objective to minimize the energy consumption per unite volume material. Polynomial curves in different degrees are used in the PTP planning method and the optimal one is compared with the conventional S-curve in terms of the excavating performance. To explore the advantage of the proposed intelligent system and the corresponding trajectory planning based energy-minimum optimization method, four types of ore piles with different pile angles are compared with respect to the excavating performance. Results show that the larger the pile angle is, the later the maximum hoist power and crowd power will appear. Further, the effects on the excavating performance from different ore piles with complex terrains, including the flat type, concave type, convex type, and concave-convex type, are also studied in the numerical experiments. It is found that the trajectory based energy-minimum optimization method for the intelligent LCS can significantly save excavation energy as well as keep sufficient fill factor.

Afforestation is a widely used method of controlling desertification globally as it significantly impacts the soil quality, microbial community structure, and function. Investigating the effects of various artificial vegetation restoration models on soil microbial communities is crucial in understanding the mechanisms involved in combating desertification. However, research on this topic in arid, desertified regions is limited. In this study, we collected soil samples from two types of artificial forests (single species and mixed species) and bare desert soils in desertified areas of Northwest China to explore the impact of afforestation on soil nutrients, the microbial community composition, network relationships, and carbohydrate degradation abilities using metagenomic sequencing techniques. Our findings indicate that afforestation significantly enhances the soil moisture, total carbon, available phosphorus, and total nitrogen levels. The soil under mixed-species forests exhibited significantly higher levels of total carbon, total phosphorus, available phosphorus, and total nitrogen than that under single-species forests. Following afforestation, the populations of Pseudomonadota, Acidobacteriota, and Cyanobacteria increased significantly, whereas Actinomycetota decreased markedly. In single-species forests, Pseudomonadota and Bacillota were enriched, whereas Chloroflexota, Planctomycetota, and Acidobacteriota were more prevalent in mixed-species plantations. Afforestation increases the complexity and stability of microbial community networks. Afforestation enhances microbial metabolic activity, particularly increasing the abundance of carbon degradation functional genes in forest soils compared to bare desert soils. Mixed-species plantations outperform single-species forests in enhancing carbohydrate metabolism, amino acid metabolism, and the biodegradation and metabolism of xenobiotics. The abundance of functional genes associated with the degradation of starch, cellulose, hemicellulose, chitin, and pectin in mixed-species forests was significantly greater than in single-species plantations. Our study shows that mixed-species afforestation effectively improves the soil quality, enhances the stability of soil microbial communities, and bolsters the carbon cycle in arid regions prone to desertification. The reciprocal relationship between microorganisms and plants may serve as an intrinsic mechanism by which mixed-species afforestation more effectively controls desertification.