Fracture failure analysis and bias tearing strength criterion for PVDF coated bi-axial warp knitted fabrics

This paper concerns the fracture failure and bias tearing strength criterion for a PVDF coated bi-axial warp knitted fabrics (BWKFs) widely used in air supported membrane structures (ASMSs). Central slit tearing tests were carefully conducted on bias specimens with seven off-axis angles, and the corresponding tearing properties, including failure behaviors and tearing strength criterion were discussed. Results show that coated bi-axial warp knitted fabrics are typical direction-depended materials, and their tearing characteristics vary greatly with the bias angles. Typical tearing stress-displacement curves of bias samples could exhibit four characteristic regions: a co-deformation region, a shear deformation region, a plateau region, and a post peak region. No matter what the orientation of the initial slit or the yarn is, the propagation is always parallel to the secondary yarns. For specimens with different bias angles, some obvious differences in tearing behaviors are observed in terms of maximum displacement, damage mode, curve slope, and number of stress peaks, and these differences could be attributed to the material orthotropy and different failure mechanism of constituent materials. Unlike results of tensile strength for most of woven fabrics, for the studied BWKF composite, there is a W-shaped relationship between tearing strength and bias angle, with a local strength peak at 45o angle. The new tearing strength criterion proposed in the prior research is validated due to the strong agreements between the calculated and experimental results for the BWKF

Increased concentrations of soluble B7-H3 and interleukin 36 in bronchoalveolar lavage fluid of Children with Mycoplasma pneumoniae pneumonia

Supporting data. (XLS 58 kb

Comparative analysis of 17 complete chloroplast genomes reveals intraspecific variation and relationships among Pseudostellaria heterophylla (Miq.) Pax populations

Pseudostellaria heterophylla (Miq.) Pax is a well-known medicinal and ecologically important plant. Effectively distinguishing its different genetic resources is essential for its breeding. Plant chloroplast genomes can provide much more information than traditional molecular markers and provide higher-resolution genetic analyses to distinguish closely related planting materials. Here, seventeen P. heterophylla samples from Anhui, Fujian, Guizhou, Hebei, Hunan, Jiangsu, and Shandong provinces were collected, and a genome skimming strategy was employed to obtain their chloroplast genomes. The P. heterophylla chloroplast genomes ranged from 149,356 bp to 149,592 bp in length, and a total of 111 unique genes were annotated, including 77 protein-coding genes, 30 tRNA genes, and four rRNA genes. Codon usage analysis showed that leucine had the highest frequency, while UUU (encoding phenylalanine) and UGC (encoding cysteine) were identified as the most and least frequently used codons, respectively. A total of 75–84 SSRs, 16–21 short tandem repeats, and 27–32 long repeat structures were identified in these chloroplast genomes. Then, four primer pairs were revealed for identifying SSR polymorphisms. Palindromes are the dominant type, accounting for an average of 47.86% of all long repeat sequences. Gene orders were highly collinear, and IR regions were highly conserved. Genome alignment indicated that there were four intergenic regions (psaI-ycf4, ycf3-trnS, ndhC-trnV, and ndhI-ndhG) and three coding genes (ndhJ, ycf1, and rpl20) that were highly variable among different P. heterophylla samples. Moreover, 10 SNP/MNP sites with high polymorphism were selected for further study. Phylogenetic analysis showed that populations of Chinese were clustered into a monophyletic group, in which the non-flowering variety formed a separate subclade with high statistical support. In this study, the comparative analysis of complete chloroplast genomes revealed intraspecific variations in P. heterophylla and further supported the idea that chloroplast genomes could elucidate relatedness among closely related cultivation materials

Surface Charge Induced Dirac Band Splitting in a Charge Density Wave Material (TaSe4)2I

(TaSe4)2I, a quasi-one-dimensional (1D) crystal, shows a characteristic temperature-driven metal-insulator phase transition. Above the charge density wave (CDW) temperature Tc, (TaSe4)2I has been predicted to harbor a Weyl semimetal phase. Below Tc, it becomes an axion insulator. Here, we performed angle-resolved photoemission spectroscopy (ARPES) measurements on the (110) surface of (TaSe4)2I and observed two sets of Dirac-like energy bands in the first Brillion zone, which agree well with our first-principles calculations. Moreover, we found that each Dirac band exhibits an energy splitting of hundreds of meV under certain circumstances. In combination with core level measurements, our theoretical analysis showed that this Dirac band splitting is a result of surface charge polarization due to the loss of surface iodine atoms. Our findings here shed new light on the interplay between band topology and CDW order in Peierls compounds and will motivate more studies on topological properties of strongly correlated quasi-1D materials.Comment: 18 pages, 4 figures. Comments are welcom

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Nucleophilic Trapping Nitrilimine Generated by Photolysis of Diaryltetrazole in Aqueous Phase

Nitrilimine generated by photolysis of diaryltetrazole in aqueous phase under mild conditions was trapped by nucleophiles including amines and thioalcohols. The representative products were characterized, while products with all 20 natural amino acids and a peptide were observed by MALDI-TOF mass spectroscopy. Competitive studies showed that this reaction also occurred in the presence of acrylamide. These results provided new information for understanding the potential side reactions when tetrazole-alkene pairs were used as a bioorthogonal reaction in labeling proteins and related studies in buffered systems

A study of metallic coatings on ceramic particles for thermal emissivity control and effective thermal conductivity enhancement in packed bed thermal energy storage

Ceramic particles-based packed bed systems are attracting the interest from various high-temperature applications such as thermal energy storage, nuclear cooling reactors, and catalytic support structures. Considering that these systems work above 600 ◦C, thermal radiation becomes significant or even the major heat transfer mechanism. The use of coatings with different thermal and optical properties could represent a way to tune and enhance the thermodynamic performances of the packed bed systems. In this study, the thermal stability of several metallic (Inconel, Nitinol, and Stainless Steel) based coatings is investigated at both high temperature and cyclic thermal conditions. Consequently, the optical properties and their temperature dependence are measured. The results show that both Nitinol and Stainless Steel coatings have excellent thermal stability at temperatures as high as 1000 ◦C and after multiple thermal cycles. Contrarily, Inconel (particularly 625) based coatings show abundant coating degradation. The investigated coatings also offer a wide range of thermal emissivity (between0.6 and 0.9 in the temperature range of 400–1000 ◦C), and variable trends against increasing temperature. This work is a stepping-stone towards further detailed experimental and modelling studies on the heat transfer enhancement in different ceramic-based packed bed applications through using metallic coatings.QC 20211103</p

Plant growth, development and change in GSH level in safflower (Carthamus tinctorius L.) exposed to copper and lead

The effects of exposure to heavy metals, copper (Cu) and lead (Pb) in the soil, separately and in combination, were examined in Safflower (Carthamus tinctorius L.). Plant growth and development, GSH level and GSH2 expression at seedling, branching, and flowering stages were studied. Cu at lower concentrations had a stimulating effect on seedling height and root length. A significant positive correlation was observed between heavy metal concentrations and inhibition of plant growth. Plant height, root length and lateral root numbers decreased progressively with increasing concentrations of Cu and Pb. Except at the seedling stage, the metal mixture elicited a synergistic effect on safflower growth and development. The GSH content was significantly reduced in both safflower roots and leaves at increased concentrations of heavy metals, with the exception of the treatment with a low concentration of Cu that resulted in a slightl increase in GSH content at the seedling and branching stages. RT-PCR analysis revealed a negative correlation between GSH2 expression levels and metal concentration. Short exposure to low concentrations of Cu induce an increase in GSH synthesis to preserve normal plant growth, whereas prolonged exposure and large Cu and Pb concentrations affect the GSH metabolic chain, and are severely toxicity. The findings obtained in this study enhance our understanding of the role of the GSH pool in the response of plants to heavy metal-induced stress, and serve as a basis for improved cultivation of safflower

Transformer-Based Distillation Hash Learning for Image Retrieval

In recent years, Transformer has become a very popular architecture in deep learning and has also achieved the same state-of-the-art performance as convolutional neural networks on multiple image recognition baselines. Transformer can obtain global perceptual fields through a self-attention mechanism and can enhance the weights of unique discriminable features for image retrieval tasks to improve the retrieval quality. However, Transformer is computationally intensive and finds it difficult to satisfy real-time requirements when used for retrieval tasks. In this paper, we propose a Transformer-based image hash learning framework and compress the constructed framework to perform efficient image retrieval using knowledge distillation. By combining the self-attention mechanism of the Transformer model, the image hash code is enabled to be global and unique. At the same time, this advantage is instilled into the efficient lightweight model by knowledge distillation, thus reducing the computational complexity and having the advantage of an attention mechanism in the Transformer. The experimental results on the MIRFlickr-25K dataset and NUS-WIDE dataset show that our approach can effectively improve the accuracy and efficiency of image retrieval