Multilayer regulatory landscape and new regulators identification for bud dormancy release and bud break in Populus.

For trees originating from boreal and temperate regions, the dormancy-to-active transition, also known as bud dormancy release and bud break, are crucial processes that allow trees to reactive growth in the spring. The molecular mechanisms underlying these two processes remain poorly understood. Here, through integrative multiomics analysis of the transcriptome, DNA methylome, and proteome, we gained insights into the reprogrammed cellular processes associated with bud dormancy release and bud break. Our findings revealed multilayer regulatory landscapes governing bud dormancy release and bud break regulation, providing a valuable reference framework for future functional studies. Based on the multiomics analysis, we have determined a novel long intergenic noncoding RNA named Phenology Responsive Intergenic lncRNA 1 (PRIR1) plays a role in the activation of bud break. that the molecular mechanism of PRIR1 has been preliminary explored, and it may partially promote bud break by activating its neighbouring gene, EXORDIUM LIKE 5 (PtEXL5), which has also been genetically confirmed as an activator for bud break. This study has revealed a lncRNA-mediated regulatory mechanism for the control of bud break in Populus, operating independently of known regulatory pathways.

Advanced application of tea residue extracts rich in polyphenols for enhancing sludge dewaterability: Unraveling the role of pH regulation.

Tea polyphenols (TPs), as a kind of derivatives from tea waste, were employed as a novel environmentally friendly bio-based sludge conditioner in this study. The findings showed that when TPs were applied at a dosage of 300 mg g-1 DS, the sludge CST0/CST ratio significantly increased to 1.90. pH regulation was found to markedly affect the dewatering efficiency of sludge. At pH 4, the CST0/CST rose to 2.86, coupled with a reduction in the specific resistance to filtration (SRF) from 6.69 × 1013 m kg-1 to 1.43 × 1013 m kg-1 and a decrease in the moisture content (MC) from 90.57% to 68.75%. TPs formed complexes and precipitated sludge proteins, as demonstrated by changes in the extracellular polymeric substances (EPS), viscosity, zeta potential, and particles size distribution. The optimization significance of acidification treatment on sludge structure disintegration, the interaction of TPs with EPS, and the removal of sludge proteins were elucidated. The research provided an ideal approach for the integrated utilization of biomass resources from tea waste and highlighted the potential application of TPs as an environmentally friendly conditioner in sludge dewatering.

A novel fault diagnosis method for second-order bandpass filter circuit based on TQWT-CNN.

To accurately locate faulty components in analog circuits, an analog circuit fault diagnosis method based on Tunable Q-factor Wavelet Transform(TQWT) and Convolutional Neural Network (CNN) is proposed in this paper. Firstly, the Grey Wolf algorithm (GWO) is used to improve the TQWT. The improved TQWT can adaptively determine the parameters Q-factor and decomposition level. Secondly, The signal is decomposed, and single-branch reconstruction is conducted with TQWT to facilitate adequate feature extraction. Thirdly, to capture the time-frequency features in the signal, a CNN-LSTM network is built by combining CNN and LSTM for feature extraction. Finally, CNN, which introduces Fully Convolutional Network (FCN) layers and a Batch Normalization layer, is used to fault diagnosis. The method was comprehensively evaluated with a second-order bandpass filter circuit. The experimental results illustrate that the proposed fault diagnosis method can achieve excellent fault diagnosis accuracy, and the average accuracy is 98.96%.

Genomic evidence for evolutionary history and local adaptation of two endemic apricots: Prunus hongpingensis and P. zhengheensis.

Apricot, belonging to the Armeniaca section of Rosaceae, is one of the economically important crop fruits that has been extensively cultivated. The natural wild apricots offer valuable genetic resources for crop improvement. However, some of them are endemic, with small populations, and are even at risk of extinction. In this study we unveil chromosome-level genome assemblies for two southern China endemic apricots, Prunus hongpingensis (PHP) and P. zhengheensis (PZH). We also characterize their evolutionary history and the genomic basis of their local adaptation using whole-genome resequencing data. Our findings reveal that PHP and PZH are closely related to Prunus armeniaca and form a distinct lineage. Both species experienced a decline in effective population size following the Last Glacial Maximum (LGM), which likely contributed to their current small population sizes. Despite the observed decrease in genetic diversity and heterozygosity, we do not observe an increased accumulation of deleterious mutations in these two endemic apricots. This is likely due to the combined effects of a low inbreeding coefficient and strong purifying selection. Furthermore, we identify a set of genes that have undergone positive selection and are associated with local environmental adaptation in PHP and PZH, respectively. These candidate genes can serve as valuable genetic resources for targeted breeding and improvement of cultivated apricots. Overall, our study not only enriches our comprehension of the evolutionary history of apricot species but also offers crucial insights for the conservation and future breeding of other endemic species amidst rapid climate changes.