A Novel Driver Distraction Behavior Detection Based on Self-Supervised Learning Framework with Masked Image Modeling

Driver distraction causes a significant number of traffic accidents every year, resulting in economic losses and casualties. Currently, the level of automation in commercial vehicles is far from completely unmanned, and drivers still play an important role in operating and controlling the vehicle. Therefore, driver distraction behavior detection is crucial for road safety. At present, driver distraction detection primarily relies on traditional Convolutional Neural Networks (CNN) and supervised learning methods. However, there are still challenges such as the high cost of labeled datasets, limited ability to capture high-level semantic information, and weak generalization performance. In order to solve these problems, this paper proposes a new self-supervised learning method based on masked image modeling for driver distraction behavior detection. Firstly, a self-supervised learning framework for masked image modeling (MIM) is introduced to solve the serious human and material consumption issues caused by dataset labeling. Secondly, the Swin Transformer is employed as an encoder. Performance is enhanced by reconfiguring the Swin Transformer block and adjusting the distribution of the number of window multi-head self-attention (W-MSA) and shifted window multi-head self-attention (SW-MSA) detection heads across all stages, which leads to model more lightening. Finally, various data augmentation strategies are used along with the best random masking strategy to strengthen the model's recognition and generalization ability. Test results on a large-scale driver distraction behavior dataset show that the self-supervised learning method proposed in this paper achieves an accuracy of 99.60%, approximating the excellent performance of advanced supervised learning methods

Fault location of multi-point hybrid transmission line based on HHT

Due to the discontinuous wave impedance, uneven line parameters, and complex and changeable fault transient traveling waves of overhead-cable hybrid transmission lines, the traditional double-ended traveling wave ranging method will produce large errors. Aiming at this problem, this paper proposes a fault location method for multi-point hybrid transmission lines based on Hilbert-Huang transform (HHT). First, the effective identification of the traveling wave head is completed at both ends of the line and at the connection point between the overhead line and the cable line, and then the HHT is used to extract the time when the fault traveling wave head reaches the measurement point, and finally it is substituted into the multi-point ranging equation to calculate the fault. The result of the ranging. The simulation results of MATLAB/PSCAD show that the method proposed in this paper avoids the influence of traveling wave velocity on the ranging accuracy, and is not affected by the line structure. Compared with the traditional double-ended ranging method, its ranging accuracy is higher. At the same time, it can also meet the requirements of engineering practice positioning accuracy within 200m

Physical Mapping of a Novel Locus Conferring Leaf Rust Resistance on the Long Arm of Agropyron cristatum Chromosome 2P

Wheat leaf rust is one of the most common wheat diseases worldwide and can cause up to 40% wheat yield loss. To combat the growth and spread of leaf rust disease, continual exploration and identification of new and effective resistance genes are needed. Here, we report for the first time a locus conferring leaf rust resistance located on the long arm of Agropyron cristatum chromosome 2P in Triticum aestivum–A. cristatum 2P translocation lines. This study used 50 leaf rust races, including two Chinese major dominant leaf rust races, named by THT and PHT, and other 48 different leaf rust races collected from 11 provinces, 1autonomous region and 1 municipality of China to test the resistance to T. aestivum–A. cristatum 2P chromosome translocation lines and their backcross populations, the results indicated that the novel leaf rust resistance locus was immune or nearly immune to all tested leaf rust races. Four long arm translocation lines with different breakpoints of A. cristatum chromosome 2PL and their backcross populations were tested with leaf rust race THT at the seedling and adult stages and genotyped with 2P-specific STS markers. The results showed that the novel leaf rust resistance locus of the T. aestivum–A. cristatum 2P translocation lines was located in the chromosomal bin FL 0.66–0.86 of 2PL. Therefore, T. aestivum–A. cristatum 2P chromosome translocation lines conferring leaf rust resistance locus could provide a novel disease-resistance resource for future wheat breeding programs

Algorithm of Route Searching for Mine Geographic Network

AbstractAccording to the features of mine geographic network, the paper presents an algorithm of route searching for mine geographic network called tree growth. This algorithm can improve the searching efficiency for avoiding searching for the intersection part of the routes. If the node of the subsequent growing branch is the same as any element of the intersection namely node (or called meeting with a refusal), it will immediately change the direction. The tree growth algorithm can avoid the problem of searching combination explosion and is applicable to route searching for large-scale mine

SSR Genotypes of the <i>Puccinia triticina</i> in 15 Provinces of China Indicate Regional Migration in One Season from East to West and South to North

Leaf rust of wheat caused by Puccinia triticina (Pt) is one of the most common fungal diseases in the southwest and northwest of China, the middle and lower reaches of the Yangtze River, and the southern part of the Huang-Huai-Hai river basin. Using 13 simple sequence repeat (SSR) markers, we systematically revealed the genotypic diversities, population differentiation and reproduction of Pt isolates in 15 wheat-producing areas in China. A total of 622 isolates were divided into 3 predominant populations, including the eastern Pt populations, consisting of Pt samples from 8 eastern provinces of Beijing, Hebei, Shanxi, Shaanxi, Anhui, Shandong, Henan, and Heilongjiang; the 4 western Pt populations from Gansu, Qinghai, Sichuan, and Inner Mongolia provinces; and the bridge Pt populations including Jiangsu, Hubei, and Yunnan, which communicated the other 2 populations as a “bridge”. The pathogen transmission of eastern Pt populations was more frequent than western Pt populations. The linkage disequilibrium test indicated that the whole Pt population was in a state of linkage disequilibrium. However, populations of Beijing, Hebei, Shaanxi, Jiangsu, Henan, and Heilongjiang provinces showed obvious linkage equilibrium, while the five provinces of Qinghai, Hubei, Anhui, Shandong, and Inner Mongolia supported clonal modes of reproduction

Metabolomic Analysis of Wheat Grains after <i>Tilletia laevis</i> Kühn Infection by Using Ultrahigh-Performance Liquid Chromatography–Q-Exactive Mass Spectrometry

Tilletia laevis causes common bunt disease in wheat, with severe losses of production yield and seed quality. Metabolomics studies provide detailed information about the biochemical changes at the cell and tissue level of the plants. Ultrahigh-performance liquid chromatography–Q-exactive mass spectrometry (UPLC-QE-MS) was used to examine the changes in wheat grains after T. laevis infection. PCA analysis suggested that T. laevis-infected and non-infected samples were scattered separately during the interaction. In total, 224 organic acids and their derivatives, 170 organoheterocyclic compounds, 128 lipids and lipid-like molecules, 85 organic nitrogen compounds, 64 benzenoids, 31 phenylpropanoids and polyketides, 21 nucleosides, nucleotides, their analogues, and 10 alkaloids and derivatives were altered in hyphal-infected grains. According to The Kyoto Encyclopedia of Genes and genomes analysis, the protein digestion and absorption, biosynthesis of amino acids, arginine and proline metabolism, vitamin digestion and absorption, and glycine, serine, and threonine metabolism pathways were activated in wheat crops after T. laevis infection

ITRAQ-Based Proteomic Analysis of Wheat (Triticum aestivum) Spikes in Response to Tilletia controversa K&uuml;hn and Tilletia foetida K&uuml;hn Infection, Causal Organisms of Dwarf Bunt and Common Bunt of Wheat

Dwarf bunt and common bunt diseases of wheat are caused by Tilletia controversa K&uuml;hn and Tilletia foetida K&uuml;hn, respectively, and losses caused by these diseases can reach 70&ndash;80% in favourable conditions. T. controversa and T. foetida are fungal pathogens belonging to the Exobasidiomycetes within the basidiomycetous smut fungi (Ustilaginomycotina). In order to illuminate the proteomics differences of wheat spikes after the infection of T. controversa and T. foetida, the isobaric tags for relative and absolute quantification (iTRAQ) technique was used for better clarification. A total of 4553 proteins were differentially detected after T. controversa infection; 4100 were upregulated, and 453 were downregulated. After T. foetida infection, 804 differentially expressed proteins were detected; 447 were upregulated and 357 were downregulated. In-depth data analysis revealed that 44, 50 and 82 proteins after T. controversa and 9, 6 and 16 proteins after T. foetida were differentially expressed, which are antioxidant, plant-pathogen interaction and glutathione proteins, respectively, and 9 proteins showed results consistent with PRM. The top 20 KEGG enrichment pathways were identified after pathogen infection. On the basis of gene ontology, the upregulated proteins were linked with metabolic process, catalytic activity, transferase activity, photosynthetic membrane, extracellular region and oxidoreductase activity. The results expanded our understanding of the proteome in wheat spikes in response to T. controversa and T. foetida infection and provide a basis for further investigation for improving the defense mechanism of the wheat crops

Comparative Transcriptome Analysis Reveals the Gene Expression and Regulatory Characteristics of Broad-Spectrum Immunity to Leaf Rust in a Wheat–<i>Agropyron cristatum</i> 2P Addition Line

Wheat leaf rust (caused by Puccinia triticina Erikss.) is among the major diseases of common wheat. The lack of resistance genes to leaf rust has limited the development of wheat cultivars. Wheat–Agropyron cristatum (A. cristatum) 2P addition line II-9-3 has been shown to provide broad-spectrum immunity to leaf rust. To identify the specific A. cristatum resistance genes and related regulatory pathways in II-9-3, we conducted a comparative transcriptome analysis of inoculated and uninoculated leaves of the resistant addition line II-9-3 and the susceptible cultivar Fukuhokomugi (Fukuho). The results showed that there were 66 A. cristatum differentially expressed genes (DEGs) and 1389 wheat DEGs in II-9-3 during P. triticina infection. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and gene set enrichment analysis (GSEA) revealed that the DEGs of II-9-3 were associated with plant–pathogen interaction, MAPK signaling pathway–plant, plant hormone signal transduction, glutathione metabolism, and phenylpropanoid biosynthesis. Furthermore, many defense-related A. cristatum genes, such as two NLR genes, seven receptor kinase-encoding genes, and four transcription factor-encoding genes, were identified. Our results indicated that the key step of resistance to leaf rust involves, firstly, the gene expression of chromosome 2P upstream of the immune pathway and, secondly, the effect of chromosome 2P on the co-expression of wheat genes in II-9-3. The disease resistance regulatory pathways and related genes in the addition line II-9-3 thus could play a critical role in the effective utilization of innovative resources for leaf rust resistance in wheat breeding