Steel Strip Surface Defect Detection Method Based on Improved YOLOv5s.

Steel strip is an important raw material for the engineering, automotive, shipbuilding, and aerospace industries. However, during the production process, the surface of the steel strip is prone to cracks, pitting, and other defects that affect its appearance and performance. It is important to use machine vision technology to detect defects on the surface of a steel strip in order to improve its quality. To address the difficulties in classifying the fine-grained features of strip steel surface images and to improve the defect detection rate, we propose an improved YOLOv5s model called YOLOv5s-FPD (Fine Particle Detection). The SPPF-A (Spatial Pyramid Pooling Fast-Advance) module was constructed to adjust the spatial pyramid structure, and the ASFF (Adaptively Spatial Feature Fusion) and CARAFE (Content-Aware ReAssembly of FEatures) modules were introduced to improve the feature extraction and fusion capabilities of strip images. The CSBL (Convolutional Separable Bottleneck) module was also constructed, and the DCNv2 (Deformable ConvNets v2) module was introduced to improve the model's lightweight properties. The CBAM (Convolutional Block Attention Module) attention module is used to extract key and important information, further improving the model's feature extraction capability. Experimental results on the NEU_DET (NEU surface defect database) dataset show that YOLOv5s-FPD improves the mAP50 accuracy by 2.6% before data enhancement and 1.8% after SSIE (steel strip image enhancement) data enhancement, compared to the YOLOv5s prototype. It also improves the detection accuracy of all six defects in the dataset. Experimental results on the VOC2007 public dataset demonstrate that YOLOv5s-FPD improves the mAP50 accuracy by 4.6% before data enhancement, compared to the YOLOv5s prototype. Overall, these results confirm the validity and usefulness of the proposed model.

Development of high-resolution multiple-SNP arrays for genetic analyses and molecular breeding through genotyping by target sequencing and liquid chip.

Genotyping platforms, as critical supports for genomics, genetics, and molecular breeding, have been well implemented at national institutions/universities in developed countries and multinational seed companies that possess high-throughput, automatic, large-scale, and shared facilities. In this study, we integrated an improved genotyping by target sequencing (GBTS) system with capture-in-solution (liquid chip) technology to develop a multiple single-nucleotide polymorphism (mSNP) approach in which mSNPs can be captured from a single amplicon. From one 40K maize mSNP panel, we developed three types of markers (40K mSNPs, 251K SNPs, and 690K haplotypes), and generated multiple panels with various marker densities (1K-40K mSNPs) by sequencing at different depths. Comparative genetic diversity analysis was performed with genic versus intergenic markers and di-allelic SNPs versus non-typical SNPs. Compared with the one-amplicon-one-SNP system, mSNPs and within-mSNP haplotypes are more powerful for genetic diversity detection, linkage disequilibrium decay analysis, and genome-wide association studies. The technologies, protocols, and application scenarios developed for maize in this study will serve as a model for the development of mSNP arrays and highly efficient GBTS systems in animals, plants, and microorganisms.

Assessment of the potential for gene flow from transgenic maize (Zea mays L.) to eastern gamagrass (Tripsacum dactyloides L.).

Eastern gamagrass (Tripsacum dactyloides L.) belongs to the same tribe of the Poaceae family as maize (Zea mays L.) and grows naturally in the same region where maize is commercially produced in the USA. Although no evidence exists of gene flow from maize to eastern gamagrass in nature, experimental crosses between the two species were produced using specific techniques. As part of environmental risk assessment, the possibility of transgene flow from maize to eastern gamagrass populations in nature was evaluated with the objectives: (1) to assess the seeds of eastern gamagrass populations naturally growing near commercial maize fields for the presence of a transgenic glyphosate-tolerance gene (cp4 epsps) that would indicate cross-pollination between the two species, and (2) to evaluate the possibility of interspecific hybridization between transgenic maize used as male parent and eastern gamagrass used as female parent. A total of 46,643 seeds from 54 eastern gamagrass populations collected in proximity of maize fields in Illinois, USA were planted in a field in 2014 and 2015. Emerged seedlings were treated with glyphosate herbicide and assessed for survival. An additional 48,000 seeds from the same 54 eastern gamagrass populations were tested for the presence of the cp4 epsps transgene markers using TaqMan® PCR method. The results from these trials showed that no seedlings survived the herbicide treatment and no seed indicated presence of the herbicide tolerant cp4 epsps transgene, even though these eastern gamagrass populations were exposed to glyphosate-tolerant maize pollen for years. Furthermore, no interspecific hybrid seeds were produced from 135 hand-pollination attempts involving 1529 eastern gamagrass spikelets exposed to maize pollen. Together, these results indicate that there is no evidence of gene flow from maize to eastern gamagrass in natural habitats. The outcome of this study should be taken in consideration when assessing for environmental risks regarding the consequence of gene flow from transgenic maize to its wild relatives.

[Research on the Tomato Metacaspase Protein Interactions with Ca2+ by Spectroscopy and Molecular Probe].

Metacaspases are cysteine-dependent proteases found in protozoa, fungi and plants and are distantly related to metazoan caspases. Most of MCPs activation are the calcium dependent, but the mechanisms are still unknown. Based on the techniques of CD spectroscopy, fluorescence spectroscopy, and Terbium Stains-all probe, we selected three purified recombinant proteins from key residues mutated in tomato metacaspase (LeMCA1), including conserved catalytic site (C139A) mutant, N-sequenced cleaved site (K223G) mutant and the predicted Ca2+ binding sites (D116A/D117A) mutant, to explore the interaction mechanism of LeMCA1 and Ca2+. CD spectroscopy and Stains-all probe results suggested that the intense binding does not exist between LeMCA1 and Ca2+ as well as Ca2+ has little effect on the secondary structure of LeMCA1. However, fluorescence spectroscopy and Tb3+ probe results showed that Ca(2+)-induced the changes occur in the tertiary structure of LeMCA1, which contributes to the activation of zymogen. In addition, predicted Ca2+ binding residues, Asp-116 and Asp117, are the key sites resporisible for the Ca2+ interaction with LeMCA1, and the loss of these two residues resulted in decreased interaction. Our data firstly provided insight on the mechanism of the interaction between Ca2+ and recombinant purified Solanaceae type II metacaspase by spectroscopy and molecular probe techniques. Combined the results we got before from sequence-alignment and sites-mutation, the key residues Asp-116 and Asp117 affect the Ca(2+)-induced the changes of LeMCA1 tertiary structure. Our data provided information for the further biochemical and crystal assays of LeMCA1.