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Alfalfa is a perennial herbaceous forage legume that is significantly and adversely affected by monocropping. Crop rotation is the most effective measure to overcome continuous cropping obstacles. However, the mechanisms of how bacterial communities are affected and the potential links between these effects and cropping systems remain poorly understood. Based on a long-term field experiments with continuous alfalfa and forage crops with alfalfa rotation in the black soil region of the western Songnen Plain in Northeast China, the alterations in soil bacterial community structure using high-throughput sequencing of the 16S rRNA gene and soil chemical properties and enzyme activities were analyzed. The alfalfa–forage oats–silage maize–alfalfa and alfalfa–silage maize–forage oats–alfalfa system significantly increase the levels of total phosphorus and available phosphorus, and promote the activities of acid phosphatase, β-glucosidase, leucine aminopeptidase, and N-acetyl-β-glucosaminidase in comparison to continuous alfalfa. While alfalfa crop rotation did not affect the α-diversity of soil bacteria, it significantly altered the bacterial community composition and structure. Some key taxa are significantly enriched in the crop rotation system soils, including Bacillus, Sphingobium, Paenibacillus, Hydrogenispora, Rubrobacter, Haliangium, and Rubellimicrobium. Additionally, crop rotation with alfalfa increased the stability and complexity of the soil bacterial co-occurrence network. Based on our findings, we recommend promoting the alfalfa–forage oats–silage maize–alfalfa and alfalfa–silage maize–forage oats–alfalfa rotation systems as ideal practices for overcoming the challenges associated with continuous cropping of alfalfa. These systems not only enhance soil nutrient content and enzyme activities but also foster a beneficial microbial community, ultimately improving soil functionality and crop performance. [ABSTRACT FROM AUTHOR]

Particle image velocimetry (PIV) is a widely used experimental technique in ocean engineering, for instance, to study the vortex fields near marine risers and the wake fields behind wind turbines or ship propellers. However, the flow fields measured using PIV in water tanks or wind tunnels always have low resolution; hence, it is difficult to accurately reveal the mechanics behind the complex phenomena sometimes observed. In this paper, physics-informed neural networks (PINNs), which introduce the Navier–Stokes equations or the continuity equation into the loss function during training to reconstruct a flow field with high resolution, are investigated. The accuracy is compared with the cubic spline interpolation method and a classic neural network in a case study of reconstructing a two-dimensional flow field around a cylinder, which is obtained through direct numerical simulation. Finally, the validated PINN method is applied to reconstruct a flow field measured using PIV and shows good performance. [ABSTRACT FROM AUTHOR]

Potato onion has facilitating effect on tomato seedlings; however, the mechanisms underlying the facilitating effect remain unknown. Here, we examined the effects of potato onion leaf volatiles and leachates on tomato seedling growth, and performed a transcriptomic comparison of two potato onion cultivars with different facilitating potentials ('Suihua': higher facilitating potential; 'Qitaihe': lower facilitating potential). Potato onion leaf volatiles and leachates decreased the stem length, but increased the shoot dry matter of tomato seedlings. Transcriptomic analysis showed that 640 genes were differentially expressed (DEGs) between 'Suihua' and 'Qitaihe.' DEGs related to photosynthesis, energy metabolism, and hormone metabolism were higher expressed in 'Suihua' compared to that in 'Qitaihe,' whereas genes related to phenylpropanoid metabolism and disease resistance were lower expressed. Pathway analysis showed the DEGs mainly participated in Metabolism, Biosynthesis of secondary metabolites and Plant hormone signal transduction. [ABSTRACT FROM AUTHOR]