RESUMEN
Underwater friction stir welding (UFSW) achieves reliable joining between dissimilar materials and meets the welding demand for function and properties in lightweight structures of modern engineering. A defect monitoring method based on Variational Mode Decomposition optimized by Beluga Whale Optimization and Hilbert-Huang Transform (BWO-VMD-HHT) is proposed to solve the unclear feature of AE signal in UFSW due to the aqueous medium. UFSW experiments on Al alloy and carbon fiber reinforced thermoplastic (CFRTP) are carried out with AE signals measured. The time-frequency domain features of AE signals are extracted by BWO-VMD-HHT. The experimental results show that the main frequency of the AE signal is 22.5 kHz, and surface crack defects, shallow hole defects, and deep hole defects are accompanied by the transfer phenomena of different frequency components. Then, the feature vectors are built by frequency components in the BWO-VMD-HHT spectrum and reduced by principal component analysis, including 22.5 kHz, 24 kHz, 20.6 kHz, 18.4 kHz, 17.3 kHz, and 15.6 kHz. The feature vectors are divided into the train and test sets, and the welding defect prediction model (ResNet18-attention) is built by ResNet18 and trained by feature vectors. In the test set, the ResNet18-attention is compared with the BP, SVM, and RBF. Test results show that the precision of models has improved by at least 10%, which are trained by BWO-VMD-HHT features vector. Also, ResNet18-attention has achieved an average precision of 0.906 and recognizes the category of weld defect accurately, and this method can be applied to the defect monitoring of UFSW.
RESUMEN
Bacillus spp. has been widely used as a biocontrol agent to control plant diseases. However, little is known about mechanisms of the protein MAMP secreted by Bacillus spp. Herein, our study reported a glycoside hydrolase family 30 (GH30) protein, BpXynC, produced by the biocontrol bacteria Bacillus paralicheniformis NMSW12, that can induce cell death in several plant species. The results revealed that the recombinant protein triggers cell death in Nicotiana benthamiana in a BAK1-dependent manner and elicits an early defense response, including ROS burst, activation of MAPK cascades, and upregulation of plant immunity marker genes. BpXynC was also found to be a glucuronoxylanase that exhibits hydrolysis activity on xlyan. Two mutants of BpXynC which lost the glucuronoxylanase activity still retained the elicitor activity. The qRT-PCR results of defense-related genes showed that BpXynC induces plant immunity responses via an SA-mediated pathway. BpXynC and its mutants could induce resistance in N. benthamiana against infection by Sclerotinia sclerotiorum and tobacco mosaic virus (TMV). Furthermore, BpXynC-treated tomato fruits exhibited strong resistance to the infection of Phytophthora capsica. Overall, our study revealed that GH30 protein BpXynC can induce plant immunity response as MAMP, which can be further applied as a biopesticide to control plant diseases.
Asunto(s)
Bacillus , Glicósido Hidrolasas , Glicósido Hidrolasas/genética , Glicósido Hidrolasas/metabolismo , Proteínas , Bacillus/metabolismo , Inmunidad de la Planta , Enfermedades de las Plantas/microbiologíaRESUMEN
Considerable evidence suggests that the skin microbiota is not only important and complex in humans and other mammals but also critical for maintaining health and skin homeostasis. To date, studies on the skin microorganisms of donkeys are surprisingly rare. To investigate the dynamic changes in commensal microbial communities on the skins of healthy donkeys throughout the growing period, skin and soil samples were collected from 30 healthy Dezhou donkeys (ranging from 1, 6, 12, 24 to 48 months of age) and their corresponding breeding sheds on the farm. All samples were analysed for high-throughput sequencing of the 16S rRNA and ITS to characterize the skin microbiota of healthy donkeys and compare the differences in skin microbiota among donkeys of different ages. There were notable differences in the proportions of various genera (including bacteria and fungi) between dorsal and abdominal skin with increasing age. The comparison of the skin microbial communities among these groups revealed that Staphylococcus was mainly enriched in the early growing stage (1 and 6 months), while the relative abundance of Streptococcus was higher in both the 1- and 48-month-old age groups. Moreover, some bacteria and commensal fungi, such as Staphylococcus and Trichosporon, were found to be positively correlated between the skin and the environment. This is the first study to investigate the dynamic changes in skin microbiota diversity and composition in donkeys of different ages and at different sites of the body. Furthermore, this study provides insights into the dynamic alterations in skin microbes during a donkey's growth and characterizes the profiles of bacterial and fungal communities across a donkey's body regions (dorsal and abdomen).