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This study used a qualitative research methodology to classify and examine the large amount of information which was collected through field research. The research objective was to (1) An investigation of Hua'er song development in Gansu and Ningxia, China; and (2) Examine the characteristics of Hua'er song in Gansu and Ningxia, China. The research designed the interview and observation forms related to the interviews and observations. The interviews were divided into 3 groups: expert informant, inheritance, and the masses. The study's findings are as follows: (1) Gansu Hezheng and Ningxia Haiyuan are both ethnic minority enclaves containing more than fifty percent of the Hui ethnicity. All faith is isism. Share similar ethnic taboos. Due to the geographical and cultural differences between the two places, the transmission of Hua'er song has changed; and (2) The Hui nationality performs a crucial, irreplaceable function in the process of Hua'er's spread, which cannot be played by any other ethnicity. Directly linked with the material interactions and activities of humanity. Not only does the Hui spirit penetrate the transmission process of Hua'er song, but it also permeates the literature of Hua'er song.

Objective: To evaluate the effects of mechanical processing on the physicochemical properties of oat β-glucan and its in vitro fermentation. Methods: Oat coarse grains, oat flakes, and oat flour were respectively produced through mechanical progressing methods such as steel cutting, table pressing, and grinding. Then, scanning electron microscopy was used to observe the microstructure, the content, dissolution rate and relative molecular weight of oat β-glucan were determined, and the colon environment was simulated in vitro for fermentation. Results: The total β-glucan content and dissolution rate of steel-cutting oat were higher than those of untreated sample. The total β-glucan content of oat flake and oat flour were lower than untreated oat, but the dissolution rate was higher than it. Untreated oat showed a lower fermentation rate, with a significantly lower acid and gas production rate than those of steel-cutting oat, oat flake, and oat flour. The total short chain fatty acid content of untreated oat produced by fermentation was the lowest, but the content of propionic acid and butyric acid was significantly higher than the other three groups. Conclusion: Mechanical progressing can affect the in vitro fermentation characteristics of oats by altering the integrity of their cell wall structure, as well as the content and dissolution rate of β-glucan. Moderate processing can contribute to the health benefits of oats.

Currently, research on rapid excavation technology mainly focuses on the influencing factors and equipment optimization of rapid excavation. There is relatively little research on the joint optimization of roadway empty roof distance, support parameters, and construction technology. In order to solve the above problem, the study focuses on the return air roadway of the 1309 working face in the No.2 of Tianshuibao Coal Mine in Huanxian County, Gansu Province. The study investigates the optimization methods of coal roadway support parameters and equipment technology. The study analyzes the time features of each process of roadway excavation. It is found that excavation, permanent support, and temporary support take the most time, accounting for 25.3%, 49.9%, and 6.2% respectively. Focusing on the three most time-consuming processes as the optimization direction, a mechanical model of the roof in the goaf area of the excavation face is constructed. The theoretical maximum empty roof distance of the excavation face is obtained to be 2.32 meters. Considering the influence of equipment, geology, technology and other factors on site, the empty roof distance is determined to be 2.0 meters. Based on the distribution features of stress, deformation, and plastic zone in the surrounding rock of the roadway under different support schemes, combined with the efficient excavation requirements of the roadway, the optimal spacing between anchor rods is determined to be 800 mm × 1000 mm. Based on the actual geological conditions of the roadway, the excavation equipment, temporary support technology, and construction technology are optimized and matched. The on-site test results show that after optimization, the maximum daily footage has been increased from 8 meters to 10 meters, and the roadway excavation speed has been increased by 25%. The deformation of the surrounding rock in the roadway is basically in a stable state, with a maximum deformation of 226 mm. The optimization plan not only ensures the safety and stability of the roadway, but also significantly improves the excavation speed of the roadway.

ObjectiveWheat, as one of the major global food crops, plays a key role in food production and food supply. Different influencing factors can lead to different types of wheat lodging, e.g., root lodging may be due to improper use of fertilizers. While stem lodging is mostly due to harsh environments, different types of wheat lodging can have different impacts on yield and quality. The aim of this study was to categorize the types of wheat lodging by unmanned aerial vehicle (UAV) image detection and to investigate the effect of UAV flight altitude on the classification performance.MethodsThree UAV flight altitudes (15, 45, and 91 m) were set to acquire images of wheat test fields. The main research methods contained three parts: an automatic segmentation algorithm, wheat classification model selection, and an improved classification model based on EfficientNetV2-C. In the first part, the automatic segmentation algorithm was used to segment the UAV to acquire the wheat test field at three different heights and made it into the training dataset needed for the classification model. The main steps were first to preprocess the original wheat test field images acquired by the UAV through scaling, skew correction, and other methods to save computation time and improve segmentation accuracy. Subsequently, the pre-processed image information was analyzed, and the green part of the image was extracted using the super green algorithm, which was binarized and combined with the edge contour extraction algorithm to remove the redundant part of the image to extract the region of interest, so that the image was segmented for the first time. Finally, the idea of accumulating pixels to find sudden value added was used to find the segmentation coordinates of two different sizes of wheat test field in the image, and the region of interest of the wheat test field was segmented into a long rectangle and a short rectangle test field twice, so as to obtain the structural parameters of different sizes of wheat test field and then to generate the dataset of different heights. In the second part, four machine learning classification models of support vector machine (SVM), K nearest neighbor (KNN), decision tree (DT), and naive bayes (NB), and two deep learning classification models (ResNet101 and EfficientNetV2) were selected. Under the unimproved condition, six classification models were utilized to classify the images collected from three UAVs at different flight altitudes, respectively, and the optimal classification model was selected for improvement. In the third part, an improved model, EfficientNetV2-C, with EfficientNetV2 as the base model, was proposed to classify and recognized the lodging type of wheat in test field images. The main improvement points were attention mechanism improvement and loss function improvement. The attention mechanism was to replace the original model squeeze and excitation (SE) with coordinate attention (CA), which was able to embed the position information into the channel attention, aggregate the features along the width and height directions, respectively, during feature extraction, and capture the long-distance correlation in the width direction while retaining the long-distance correlation in the length direction, accurate location information, enhancing the feature extraction capability of the network in space. The loss function was replaced by class-balanced focal loss (CB-Focal Loss), which could assign different loss weights according to the number of valid samples in each class when targeting unbalanced datasets, effectively solving the impact of data imbalance on the classification accuracy of the model.Results and DiscussionsFour machine learning classification results: SVM average classification accuracy was 81.95%, DT average classification accuracy was 79.56%, KNN average classification accuracy was 59.32%, and NB average classification accuracy was 59.48%. The average classification accuracy of the two deep learning models, ResNet101 and EfficientNetV2, was 78.04%, and the average classification accuracy of ResNet101 was 81.61%. Comparing the above six classification models, the EfficientNetV2 classification model performed optimally at all heights. And the improved EfficientNetV2-C had an average accuracy of 90.59%, which was 8.98% higher compared to the average accuracy of EfficientNetV2. The SVM classification accuracies of UAVs at three flight altitudes of 15, 45, and 91 m were 81.33%, 83.57%, and 81.00%, respectively, in which the accuracy was the highest when the altitude was 45 m, and the classification results of the SVM model values were similar to each other, which indicated that the imbalance of the input data categories would not affect the model's classification effect, and the SVM classification model was able to solve the problem of high dimensionality of the data efficiently and had a good performance for small and medium-sized data sets. The SVM classification model could effectively solve the problem of the high dimensionality of data and had a better classification effect on small and medium-sized datasets. For the deep learning classification model, however, as the flight altitude increases from 15 to 91 m, the classification performance of the deep learning model decreased due to the loss of image feature information. Among them, the classification accuracy of ResNet101 decreased from 81.57% to 78.04%, the classification accuracy of EfficientNetV2 decreased from 84.40% to 81.61%, and the classification accuracy of EfficientNetV2-C decreased from 97.65% to 90.59%. The classification accuracy of EfficientNetV2-C at each of the three altitudes. The difference between the values of precision, recall, and F1-Score results of classification was small, which indicated that the improved model in this study could effectively solve the problems of unbalanced model classification results and poor classification effect caused by data imbalance.ConclusionsThe improved EfficientNetV2-C achieved high accuracy in wheat lodging type detection, which provides a new solution for wheat lodging early warning and crop management and is of great significance for improving wheat production efficiency and sustainable agricultural development.

BackgroundSmall RNAs (sRNAs) including microRNAs (miRNAs) and small interfering RNAs (siRNAs) serve as core players in gene silencing at transcriptional and post-transcriptional levels in plants, but their subcellular localization has not yet been well studied, thus limiting our mechanistic understanding of sRNA action.ResultsWe investigate the cytoplasmic partitioning of sRNAs and their targets globally in maize (Zea mays, inbred line "B73") and rice (Oryza sativa, cv. "Nipponbare") by high-throughput sequencing of polysome-associated sRNAs and 3' cleavage fragments, and find that both miRNAs and a subset of 21-nucleotide (nt)/22-nt siRNAs are enriched on membrane-bound polysomes (MBPs) relative to total polysomes (TPs) across different tissues. Most of the siRNAs are generated from transposable elements (TEs), and retrotransposons positively contributed to MBP overaccumulation of 22-nt TE-derived siRNAs (TE-siRNAs) as opposed to DNA transposons. Widespread occurrence of miRNA-mediated target cleavage is observed on MBPs, and a large proportion of these cleavage events are MBP-unique. Reproductive 21PHAS (21-nt phasiRNA-generating) and 24PHAS (24-nt phasiRNA-generating) precursors, which were commonly considered as noncoding RNAs, are bound by polysomes, and high-frequency cleavage of 21PHAS precursors by miR2118 and 24PHAS precursors by miR2275 is further detected on MBPs. Reproductive 21-nt phasiRNAs are enriched on MBPs as opposed to TPs, whereas 24-nt phasiRNAs are nearly completely devoid of polysome occupancy.ConclusionsMBP overaccumulation is a conserved pattern for cytoplasmic partitioning of sRNAs, and endoplasmic reticulum (ER)-bound ribosomes function as an independent regulatory layer for miRNA-induced gene silencing and reproductive phasiRNA biosynthesis in maize and rice.

MicroRNA156 (miR156) and miR529 have high sequence similarity and recognize overlapping sites in the same target genes, SQUAMOSA promoter binding protein-like (SPL or SBP box) genes, making it difficult to accurately distinguish their roles in regulatory networks that affect numerous biological functions. Here, we collected data about miR156 and miR529 family members from representative land plants and performed sequence comparisons, phylogenetic analysis, small RNA sequencing, and parallel analysis of RNA ends (PARE) analysis to dissect their evolutionary and functional differences. Although miR156 and miR529 are highly similar, there are differences in their mismatch-sensitive regions, which are essential for target recognition. In land plants, miR156 precursors are conserved mainly within the hairpin region, whereas miR529 precursors are conserved outside the hairpin region, including both the 5' and 3' arms. Phylogenetic analysis showed that MIR156 and MIR529 evolved independently, through divergent evolutionary patterns. The two genes also exhibit different expression patterns, with MIR529 preferentially expressed in reproductive tissues and MIR156 in other tissues. PARE analysis revealed that miR156 and miR529 possess specific targets in addition to common targets in maize, pointing to functional differences between them. Based on our findings, we developed a method for the rapid identification of miR529 and miR156 family members and uncovered the evolutionary divergence of these families, providing insights into their different regulatory roles in plant growth and development.

Instant rice with added coarse grain (IR/CG) is a new type of coarse grain product which is self-heating and convenient to eat and has the nutritional value of coarse grains. However, its health effects are not clear yet. Therefore, in this study, the effect of IR/CG on glucose and lipid metabolism was explored in mice with type 2 diabetes mellitus (T2DM) induced by high fat diet (HFD) combined with intraperitoneal injection of streptozotocin. The mice were fed on HFD alone (model), its mixture with IR/CG in different ratios: 25% (low-dose IR/CG, IR/CG-L), 50% (medium-dose IR/CG, IR/CG-M), and 75% (high-dose IR/CG, IR/CG-H), IR/CG alone, or a basal diet (control). During the dietary intervention, the body mass, fasting blood glucose, food intake and glucose tolerance of the mice were measured. After the IR/CG intervention for four weeks, the organ coefficients were calculated, and the pathological changes in liver and pancreas tissues were examined by hematoxylin and eosin (HE) staining. Fasting insulin levels, blood glucose and lipid levels, and proinflammatory cytokines levels were determined. The experimental results showed that dietary supplementation of IR/CG improved blood glucose and lipid levels in T2DM mice to different extents, and this effect was more prominent in the IR/CG-H and IR/CG groups. In addition, IR/CG-H and IR/CG significantly mitigated insulin resistance, decreased insulin secretion, glucagon and HbA1c levels, and reduced oxidative stress injury and inflammatory cytokine levels in T2DM mice. By analyzing the organ index and pathological sections of liver and pancreas tissues, it was found that IR/CG intervention could effectively alleviate liver steatosis and partially restore the structure of the pancreatic islets in mice. Therefore, the substitution of high-fat diet by IR/CG has a significant effect on regulating blood glucose and lipids in T2DM mice, which can provide a theoretical basis for the development of self-heating rice products and functional foods with coarse-grain.

The incidence of lumbar disc herniation (LDH) is increasing gradually. Surgical treatment combined with TCM physiotherapy can effectively relieve the pain of LDH patients. This paper summarized perioperative nursing management in a patient undergoing LDH surgery. Nursing intervention was mainly divided into two stages: Routine nursing measures were carried out in the preoperative stage; a comprehensive nursing plan with targeted nursing interventions was made after patient condition analysis. The aim of comprehensive nursing plan was to enhance the stability of spine and lumbar muscles and reduce the risk of complications. (随着现代生活方式的改变, 腰椎间盘突出症发病率呈现逐渐增高趋势。通过手术治疗配合中医理疗, 能够有效缓解患者病痛。本文总结1例腰椎间盘突出症患者的护理经验。护理干预主要分为术前和术后两个阶段, 术前护理干预主要为常规护理措施; 术后则针对患者病情制定护理计划, 给予针对性的护理措施, 旨在增强脊柱及腰背肌的稳定性, 减少各种并发症的发生风险。)

This paper summarized the postoperative nursing management of a child with spastic cerebral palsy. The child received selective posterior rhizotomy followed by preoperative examination and preparation. In addition to the interventions on postoperative pain, constipation and infection, a rehabilitation exercise program was carried out to improve the comprehensive recovery of the child after surgery. (本文总结1例痉挛型脑瘫患儿的术后护理体会。患儿入院后完善相关检查和术前准备, 采用选择性脊神经后根切断术治疗, 术后做好疼痛、便秘、感染等护理干预, 根据恢复期制定康复方案, 指导患儿及家属进行康复锻炼, 促使其全面康复。)

Recent findings regarding nicotinamide adenine dinucleotide (NAD+)-capped RNAs (NAD-RNAs) indicate that prokaryotes and eukaryotes employ noncanonical RNA capping to regulate gene expression. Two methods for transcriptome-wide analysis of NAD-RNAs, NAD captureSeq and NAD tagSeq, are based on copper-catalyzed azide-alkyne cycloaddition (CuAAC) click chemistry to label NAD-RNAs. However, copper ions can fragment/degrade RNA, interfering with the analyses. Here we report development of NAD tagSeq II, which uses copper-free, strain-promoted azide-alkyne cycloaddition (SPAAC) for labeling NAD-RNAs, followed by identification of tagged RNA by single-molecule direct RNA sequencing. We used this method to compare NAD-RNA and total transcript profiles of Escherichia coli cells in the exponential and stationary phases. We identified hundreds of NAD-RNA species in E. coli and revealed genome-wide alterations of NAD-RNA profiles in the different growth phases. Although no or few NAD-RNAs were detected from some of the most highly expressed genes, the transcripts of some genes were found to be primarily NAD-RNAs. Our study suggests that NAD-RNAs play roles in linking nutrient cues with gene regulation in E. coli.

Nicotinamide adenine diphosphate (NAD+) is a novel messenger RNA 5' cap in Escherichia coli, yeast, mammals, and Arabidopsis Transcriptome-wide identification of NAD+-capped RNAs (NAD-RNAs) was accomplished through NAD captureSeq, which combines chemoenzymatic RNA enrichment with high-throughput sequencing. NAD-RNAs are enzymatically converted to alkyne-RNAs that are then biotinylated using a copper-catalyzed azide-alkyne cycloaddition (CuAAC) reaction. Originally applied to E. coli RNA, which lacks the m7G cap, NAD captureSeq was then applied to eukaryotes without extensive verification of its specificity for NAD-RNAs vs. m7G-capped RNAs (m7G-RNAs). In addition, the Cu2+ ion in the CuAAC reaction causes RNA fragmentation, leading to greatly reduced yield and loss of full-length sequence information. We developed an NAD-RNA capture scheme utilizing the copper-free, strain-promoted azide-alkyne cycloaddition reaction (SPAAC). We examined the specificity of CuAAC and SPAAC reactions toward NAD-RNAs and m7G-RNAs and found that both prefer the former, but also act on the latter. We demonstrated that SPAAC-NAD sequencing (SPAAC-NAD-seq), when combined with immunodepletion of m7G-RNAs, enables NAD-RNA identification with accuracy and sensitivity, leading to the discovery of new NAD-RNA profiles in Arabidopsis Furthermore, SPAAC-NAD-seq retained full-length sequence information. Therefore, SPAAC-NAD-seq would enable specific and efficient discovery of NAD-RNAs in prokaryotes and, when combined with m7G-RNA depletion, in eukaryotes.