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The MYB transcription factor is one of the largest gene families in plants, playing an important role in regulating plant growth, development, response to stress, senescence, and especially the anthocyanin biosynthesis. In this study, A total of 217 MYB genes, including 90 1R-MYBs, 124 R2R3-MYBs, and 3 R1R2R3-MYBs have been identified from the potato genome. The 1R-MYB and R2R3-MYB family members could be divided into 20 and 35 subgroups respectively. Analysis of gene structure and protein motifs revealed that members within the same subgroup presented similar exon/intron and motif organization, further supporting the results of phylogenetic analysis. Potato is an ideal plant to reveal the tissue-specific anthocyanins biosynthesis regulated by MYB, as the anthocyanins could be accumulated in different tissues, showing colorful phenotypes. Five pairs of colored and colorless tissues, stigma, petal, stem, leaf, and tuber flesh, were applied to the transcriptomic analysis. A total of 70 MYB genes were found to be differentially expressed between colored and colorless tissues, and these differentially expressed genes were suspected to regulate the biosynthesis of anthocyanin of different tissues. Co-expression analysis identified numerous potential interactive regulators of anthocyanins biosynthesis, involving 39 MYBs, 24 bHLHs, 2 WD-repeats, and 29 biosynthesis genes. Genome-wide association study (GWAS) of tuber flesh color revealed a major signal at the end of Chromosome 10, which was co-localized with reported I gene (StMYB88), controlling tuber peel color. Analyses of DEGs (Differentially Expression Genes) revealed that both StMYB88 and StMYB89 were closely related to regulating anthocyanin biosynthesis of tuber flesh. This work offers a comprehensive overview of the MYB family in potato and will lay a foundation for the functional validation of these genes in the tissue-specific regulation of anthocyanin biosynthesis.

Non-destructive testing (NDT) of magnetic materials such as aviation parts is an indispensable part of the civil aviation maintenance industry. The NDT of such metal materials often uses magnetic particle inspection (MPI) technology. This paper proposes an improved DeepLabv3+ semantic segmentation algorithm for automatic defect detection of aviation ferromagnetic parts after MPI. In the network structure, lightweight MobileNetV2 is the backbone feature extraction network. The dense atrous spatial pyramid pooling (DenseASPP) structure is used to strengthen feature extraction. The influence of three different DenseASPP structures on the recognition effect is compared in the experiment. At the same time, the decoder is further optimized. The experimental results show that the Ours-DeepLabv3+ network model can effectively for automatic defect detection of aviation ferromagnetic parts after MPI. The Precision, Recall, F1-score, and intersection over union are 81.64%, 83.12%, 82.37%, and 71.23%, respectively, which are 7.48%, 5.45%, 6.50%, and 10.1% higher than the original DeepLabv3+, and defect detail segmentation is more accurate. Compared with other semantic segmentation algorithms, this method can effectively improve the accuracy of defect detection of aviation ferromagnetic parts and meet the requirements of defect detection.

Porcine transmissible gastroenteritis virus (TGEV) is an enteric coronavirus that has caused high morbidity and mortality of piglets worldwide. Previous studies have shown that the TGEV can lead to severe diarrhoea, vomiting and dehydration in 2-week-old piglets and weaned piglets, resulting in a large number of piglet deaths. Antimicrobial peptides have broad-spectrum antimicrobial activity and a strong killing effect on bacteria, especially on the drug-resistant pathogenic bacteria, and it has attracted broad concern. However, there are very few reports on the effect of APB-13 (an antimicrobial peptide) on the intestinal microbes of piglets infected with TGEV. In this study, 16S rRNA gene sequencing was used to compare the microbial phylum and the genus of piglet's enteric microorganism in different experimental groups, and to predict the metabolic function of the microbial flora. At the same time, the apparent digestibility of nutrients, digestive enzyme activity, daily weight gain and survival rate were also measured. TGEV infection could cause the imbalance of intestinal microbes in piglets, and increase of the relative abundance of Proteobacteria, and decrease of the relative abundance of Firmicutes, Bacteroidetes and Actinobacteri. With the addition of APB-13, this problem can be alleviated, which can reduce the relative abundance of Proteobacteria and improve the balance of intestinal microorganisms. At the microbial genus level, after adding APB-13, the relative abundance of Catenibacterium, Enterobacter and Streptococcus in the intestinal tract of piglets infected with TGEV showed significant decrease, while the relative abundance of Lactobacillus and Ruminococcus increased. Finally, we found that APB-13 can significantly increase the activity of digestive enzyme in the intestinal tract of piglet, thereby improving the apparent digestibility of nutrients and the growth performance of piglets. This study demonstrates that APB-13 can alleviate the adverse outcomes caused by TGEV infection by correcting the intestinal microbial disorders.

The traditional pupil positioning method is carried out under the assumption that the pupil boundary is a regular circle, and thus the rich texture features around the pupil boundary are eliminated, which directly affects the iris recognition accuracy. To solve this problem, this paper proposes an irregular pupil positioning method, finds the pupil boundary by preprocessing, then uses the least-squares method to accurately fit the pupil boundary. Finally, the algorithm is verified and analyzed by the CASIA database, and the traditional Hough transform method is used as a comparative experiment. The experimental results show that the proposed algorithm is not only suitable for irregular pupil boundaries (including noncircular and concave and convex areas), but also better in positioning time and positioning accuracy.

This paper introduces a novel Hall-effect-based whisker sensor and proposes a contour recognition algorithm for distinguishing and recognizing objects. The mechanical arm drives the sensor to move according to the contour recognition algorithm in the experiments, and the object contour is distinguished and recognized by processing the detected spatial magnetic field data. The results of identifying the measured object with harder carbon fiber and softer ABS whiskers were compared and analyzed, and a new design was proposed based on the advantages of soft and hard materials. The newly designed whisker with glass fiber and stainless steel rod nested reduced the contour recognition error to 4.1%. The experimental results showed that the sensor could distinguish the contour of the straight line and circular objects, and the glass fiber and stainless steel rod nested sensor had a better recognition effect.

The design of a whisker sensor, inspired by mammalian whisker characteristics, is presented in this paper. It uses a novel spring structure to transfer the deformation generated by the whisker tip when it touches an object at the base, which drives the permanent magnet installed at the base to change its position. It achieves precise positioning of the object by using the magnetic induction intensity data output from the Hall sensor MLX90393. Based on the results of the finite element model analysis, the detection range of the whisker sensor can be expanded by replacing the artificial whisker material and selecting a permanent magnet of a suitable size. Calibration experiments and positioning tests were conducted on the sensor. The experimental results showed that the detection radius of the sensor was 24, 30, 33, and 39 mm for the carbon fiber, acrylic, acrylonitrile butadiene styrene plastic (ABS), and nylon whiskers, respectively, when they were matched with a NdFeB annular permanent magnet with an aperture of 3 mm and a thickness of 3 mm. The sensor is small and simple to manufacture with good sensitivity, linearity, hysteresis, and repeatability. The maximum positioning errors of the X and Y positions in the detection plane of the sensor were within ±1.3 mm, and the positioning was accurate. The sensor can be used to identify the shape of an object.

Streptococcus suis (SS), an important pathogen for pigs, is not only considered as a zoonotic agent for humans, but is also recognized as a major reservoir of antimicrobial resistance contributing to the spread of resistance genes to other pathogenic Streptococcus species. In addition to serotype 2 (SS2), serotype 9 (SS9) is another prevalent serotype isolated from diseased pigs. Although many SS strains have been sequenced, the complete genome of a non-SS2 virulent strain has been unavailable to date. Here, we report the complete genome of GZ0565, a virulent strain of SS9, isolated from a pig with meningitis. Comparative genomic analysis revealed five new putative virulence or antimicrobial resistance-associated genes in strain GZ0565 but not in SS2 virulent strains. These five genes encode a putative triacylglycerol lipase, a TipAS antibiotic-recognition domain protein, a putative TetR family transcriptional repressor, a protein containing a LPXTG domain and a G5 domain, and a type VII secretion system (T7SS) putative substrate (EsxA), respectively. Western blot analysis showed that strain GZ0565 can secrete EsxA. We generated an esxA deletion mutant and showed that EsxA contributes to SS virulence in a mouse infection model. Additionally, the antibiotic resistance gene vanZSS was identified and expression of vanZSS conferred resistance to teicoplanin and dalbavancin in Streptococcus agalactiae. We believe this is the first experimental demonstration of the existence of the T7SS putative substrate EsxA and its contribution to bacterial virulence in SS. Together, our results contribute to further understanding of the virulence and antimicrobial resistance characteristics of SS.

Streptococcus suis (SS) is an important pathogen for pigs, and it is also considered as a zoonotic agent for humans. Meningitis is one of the most common features of the infection caused by SS, but little is known about the mechanisms of SS meningitis. Recent studies have revealed that small RNAs (sRNAs) have emerged as key regulators of the virulence in several bacteria. In the previous study, we reported that SS sRNA rss04 was up-regulated in pig cerebrospinal fluid and contributes to SS virulence in a zebrafish infection model. Here, we show that rss04 facilitates SS invasion of mouse brain and lung in vivo. Label-free quantitation mass spectrometry analysis revealed that rss04 regulates transcriptional regulator CcpA and several virulence factors including LuxS. Transmission electron microscope and Dot-blot analyses indicated that rss04 represses capsular polysaccharide (CPS) production, which in turn facilitates SS adherence and invasion of mouse brain microvascular endothelial cells bEnd.3 in vitro and activates the mRNA expression of TLR2, CCL2, IL-6 and TNF-α in mouse brain in vivo at 12h post-infection. In addition, rss04 positively regulates SS biofilm formation. Survival analysis of infected mice showed that biofilm state in brain contributes to SS virulence by intracranial subarachnoidal route of infection. Together, our data reveal that SS sRNA rss04 contributes to the induction of meningitis by regulating the CPS synthesis and by inducing biofilm formation, thereby increasing the virulence in a mouse infection model. To our knowledge, rss04 represents the first bacterial sRNA that plays definitive roles in bacterial meningitis.

Streptococcus suis is a major pathogen of pigs and also an important zoonotic agent for humans. A S. suis protein containing Mac-1 domain (designated Mac) is a protective antigen, exclusively cleaves porcine IgM, and contributes to complement evasion with the presence of high titers of specific porcine anti-S. suis IgM, but its role in S. suis virulence has not been investigated in natural healthy host without specific IgM. In this study, a mac deletion mutant was constructed by homologous recombination in S. suis serotype 2 virulent reference strain P1/7. Deletion of mac did not significantly influence phagocytosis or intracellular survival within murine macrophages RAW264.7, or the oxidative-burst induction of RAW264.7 and murine neutrophils. Furthermore, the mutant is as virulent as the wild-type strain in pig, mouse, and zebrafish infection models. Our data suggest that Mac is not essential for S. suis virulence in strain P1/7 in natural healthy host without specific IgM, and the immunogenicity of Mac does not appear to correlate with its significance for virulence.

Streptococcus suis is not only a major bacterial pathogen of pigs worldwide but also an emerging zoonotic agent. In humans and pigs, meningitis is a major manifestation of S. suis infections. A suitable infection model is an essential tool to understand the mechanisms of diseases caused by pathogens. Several routes of infection in mice have been developed to study the pathogenesis of S. suis infection. However, the intraperitoneal, intranasal, and intravenous routes of infection are not suitable for studying the roles of S. suis surface components in meningitis directly in the brain, such as the extracellular matrix from biofilms. Although intracisternal inoculation has been used for S. suis infection, the precise injection site has not been described. Here, the intracranial subarachnoidal route of infection was described in a mouse model to investigate the roles of biofilms in S. suis meningitis. S. suis planktonic cells or biofilm state cells were directly injected into the subarachnoid space of mice through the injection site located 3.5 mm rostral from the bregma. Histopathological analysis and increased mRNA expression of TLR2 and cytokines of the brain tissue from mice injected with biofilm state cells clearly indicated that S. suis biofilm plays definitive roles in S. suis meningitis. This route of infection has obvious advantages over other routes of infection, allowing the study of the host-bacterium interaction. Furthermore, it permits the effect of bacterial components on host immune responses directly in the brain to be assessed, and mimics bacterial entrance into the central nervous system. This route of infection can be extended for investigating the mechanisms of meningitis caused by other bacteria. In addition, it can also be used to test the efficacy of drugs against bacterial meningitis.

Instrument is an important component of industrial production. How to read instrument automatically is of great value to improve production efficiency. The automatic recognition of instrument has the problems of complicated composition of instrument panel and blurred image. This paper puts forward automatic recognition of instrument dial readings with multiple reference points. According to the position relation of reference points and pointer center, we select the optimal reference point. The number of instrument can be obtained by the vector relation of center point of instrument, pointer point and optimal reference point. The effectiveness of the proposed method is experimentally validated in complex environments.

An attractive way to prepare carbon fiber-reinforced ZrC matrix composites was proposed and confirmed experimentally. The experimental results showed that the resulting composites were fabricated by immersing carbon/carbon preforms in molten Zr 2 Cu at 1200 °C for 3 h. ZrC was the main phase, with a content of 42.2 ± 1.3 vol.%. The composites exhibited excellent ablation resistance when undergoing ablation with an oxyacetylene torch, the mass loss rate and linear recession rate being 0.0006 ± 0.0001 g s −1 and 0.0003 ± 0.0001 mm s −1 , respectively.

Zirconium diboride–zirconium carbide based composites were fabricated by reactive melt infiltration with boron carbide and Zr 2 Cu at 1200 °C. Mechanical properties of the composites before and after high temperature treatments were investigated. The presence of elongated ZrB 2 grains and amorphous residual alloy provided the composites with an excellent fracture toughness of 12.1 MPa m 1/2 . High temperature treatments could improve the density of sintered composite and increase the bonding strength between ZrB 2 and ZrC grains. This resulted in a flexural strength of 469.7 MPa and an excellent fracture toughness of 13.6 MPa m 1/2 was obtained after a treatment at 1600 °C in argon. The evaporation of copper at 1600 °C in vacuum during heat treatment caused degradation in the mechanical properties. However, at a higher temperature of 1800 °C, the composite showed the highest flexural strength of 484.1 MPa and the highest flexural modulus of 282.2 GPa, apparently counterbalanced the Cu-loss effect.

Tungsten–zirconium carbide composites were fabricated at different temperatures by the displacive compensation of porosity (DCP) method, the microstructure, mechanical properties, and ablation resistance were investigated. It was found that no WC phase was left in the composites prepared at 1400 °C, and a few residual W 2 C particles were surrounded in W product. Microstructure analyses revealed that zirconium atoms diffused into tungsten carbide to form ZrC and W 2 Zr besides carbon diffused into the Zr 2 Cu melt. Composites fabricated at 1400 °C had a flexural strength of 356.7 ± 15.2 MPa, an elastic modulus of 193.7 ± 9.8 GPa, a fracture toughness of 7.0 ± 0.7 MPa m 1/2 , and a hardness of 13.6 ± 0.7 GPa. After ablated by an oxyacetylene flame for 30 s, the higher temperature prepared composites had a better ablation resistance, the linear ablation rate was 0.0033 ± 0.0004 mm/s, and the mass ablation rate was 0.0012 ± 0.0001 g/s.

An attractive way to prepare ZrB2–ZrC-based composites at relative low temperature was proposed and confirmed experimentally. The thermodynamics calculations indicated the reaction between B4C and Zr2Cu was feasible at as low a temperature as 1100 °C. The experimental results showed that ZrB2–ZrC-based composites could be fabricated by heating Zr2Cu-covered B4C preforms to 1200 °C for 6 h in vacuum. Further, the microstructure features and mechanical properties were discussed.

Nanostructure tin dioxide (SnO 2 ) powders prepared by sol-gel dialytic processes using tin (IV) chloride and anhydrous alcohol as start materials, ammonia gas as catalyst of the formation of colloid solution and agent of removing Cl − , and by introducing dialytic processes to improve and accelerate the formation of gels. From the result of TG–DTA analyses, the dried samples were calcined at 673 K in air for 3 h. Tin dioxide nanoparticles were characterized by thermogravimetry and differential thermal analyses (TG–DTA), X-ray diffraction (XRD), nitrogen adsorption–desorption, X-ray photoelectron spectroscopy (XPS). The average particle size of the as-prepared tin dioxide was about 5 nm. The as-prepared SnO 2 possessed mesoporous structure and large surface area. The Au/SnO 2 catalysts for low-temperature CO oxidation were prepared by the deposition–precipitation method using as-prepared SnO 2 powders as the support. The Au/SnO 2 catalysts exhibited high catalytic activity for low-temperature CO oxidation. The nanostructure SnO 2 has promising applications in sensor, catalyst, catalytic support, mesoporous membranes, etc.

The Au/SnO2 catalysts were prepared by a co-precipitation method. The structure of the sample treated at different temperatures was investigated by means of HRTEM and XPS. The structure of the samples after various treatments and their activity in the CO oxidation were compared. The results showed that the catalytic behavior was related to the particle size of gold and surface oxygen species on the support. Highly dispersed gold particles and adsorbed surface oxygens and hydroxyl groups on the support were responsible for the high catalytic activity of the Au/SnO2 catalyst.

ZrB 2 based composites were prepared by a novel reactive melt infiltration process. The porous boron bars were used as preforms and infiltrated by the low melting Zr 2 Cu intermetallic compound. Thermodynamics calculations revealed that B could react with liquid Zr 2 Cu to form ZrB 2 as low as 1100 °C. Composites were prepared by heating the two materials to 1200 °C for 3 h in vacuum. The resultant composites were studied with XRD and SEM. ZrB 2 was identified to be the main constituent. The composites had a flexural strength of 414.3 MPa, a flexural modulus of 183.6 GPa, and a fracture toughness of 5.5 MPa m 1/2 .

Flotation level control is a very important part in the flotation mineral separation process. This article introduces one application of the Modbus RTU protocol which used in the flotation liquid level control system, discusses the S7-300's programming ideas and methods which based on the form of communication, and optimize the communication strategy. The practical application shows that the system of flotation liquid level control which based on Modbus RTU protocol can get better control effect, and ensure a good target for the mineral separation.

For bank employees, it’s more sensitive to organizational politics because of the special industry and work. The study investigates bank employees’ perceptions of organizational politics and analyzes its effects on job performance by the questionnaire survey. The conclusions show that: two aspects of perceptions of organizational politics, self-serving behaviors and coworker relation, have significantly positive correlation with task performance. But pay and promotion policies has significantly negative correlation with both task performance and relationship performance.

Kernel fuzzy C-means (KFCM) clustering Algorithm is one of the most widely used methods in data mining, but this algorithm still exists some defects, such as the local optima and sensitivity to initialization and noise data. Artificial bee colony (ABC) is a very simple, robust, stochastic global optimization tool which is used in many optimization problems. In this paper, an improved KFCM algorithm based on ABC (ABC-KFCM) is proposed. It can integrate advantages of KFCM and ABC algorithm. According to the test, compared with the FCM and KFCM clustering algorithm, the proposed algorithm improves the optimization ability of the algorithm, the number of iterations is fewer, and the convergence speed is faster. In addition, there is also a large improved in the clustering result.