67 research outputs found

    Complex knowledge graph embeddings based on convolution and translation

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    Link prediction involves the use of entities and relations that already exist in a knowledge graph to reason about missing entities or relations. Different approaches have been proposed to date for performing this task. This paper proposes a combined use of the translation-based approach with the Convolutional Neural Network (CNN)-based approach, resulting in a novel model, called ConCMH. In the proposed model, first, entities and relations are embedded into the complex space, followed by a vector multiplication of entity embeddings and relational embeddings and taking the real part of the results to generate a feature matrix of their interaction. Next, a 2D convolution is used to extract features from this matrix and generate feature maps. Finally, the feature vectors are transformed into predicted entity embeddings by obtaining the inner product of the feature mapping and the entity embedding matrix. The proposed ConCMH model is compared against state-of-the-art models on the four most commonly used benchmark datasets and the obtained experimental results confirm its superiority in the majority of cases. </p

    Plasmid used in this study.

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    <p>Plasmid used in this study.</p

    Constructing LiF-Dominated Interphases with Polymer Interwoven Outer Layer Enables Long-Term Cycling of Si Anodes

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    Constructing a robust solid electrolyte interphase (SEI) is extremely critical to developing high-energy-density silicon (Si)-based lithium-ion batteries. However, it is still elusive how to accurately manipulate the chemical composition and structure of the SEI layer. Herein, a LiF-dominated SEI film intertwined by a highly elastic polymer is achieved by regulating the defluorination mechanism of the fluorinated carbonate additive on the Si electrode surface. The experimental and computational results confirm that the decomposition route of trans-difluoroethylene carbonate (DFEC) molecules can be significantly altered in the presence of lithium difluoro(oxalato)borate (LiDFOB) additive. The induction of direct defluorination of DFEC step by LiDFOB, as opposed to the breaking of C–O bonds without LiDFOB addition, is crucial in ensuring the exclusive formation of LiF-dominated SEI and maintaining the cyclic structure of DFEC. The defluorinated DFEC easily polymerizes to form poly(vinylene carbonate), enhancing the elasticity of the SEI. The resulting LiF-dominated SEI film with a polymer interwoven outer layer shows enhanced ionic conductivity and mechanical stability, which can effectively accelerate electrode reaction kinetics and maintain the structural stability of the Si electrode. As a result, the Si electrode with the electrolyte containing the designed dual-additive exhibits superior cycling stability and excellent rate performance, delivering a high reversible capacity of 1487.3 mAh g–1 after 1000 cycles at 2 A g–1

    Phylogenetic tree constructed by the unweighted pair group method with arithmetic mean.

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    <p>Bootstrap values indicate the number of times that a given node was detected out of 100. The Asd sequences were obtained from NCBI's Entrez Protein database for <i>Edwardsiella ictaluri</i> YP_002935083.1; <i>Edwardsiella tarda</i> YP_003297386.1; <i>Escherichia coli</i> AP_004358.1; <i>Salmonella</i> Typhi NP_807591.1; <i>Salmonella</i> Paratyphi A YP_152515.1; <i>Salmonella</i> Typhimurium AAB69392.1; <i>Shigella flexnieri</i> YP_690789.1; <i>Shigella sonnei</i> YP_312455.1; <i>Citrobacter koseri</i> YP_001456333.1; <i>Enterobacter cancerogenus</i> ZP_05969786.1; <i>Enterobacter</i> sp. YP_001178547.1; <i>Yersinia pestis</i> NP_671174.1; <i>Yersinia ruckeri</i> ZP_04615435.1; <i>Proteus mirabilis</i> YP_002152826.1; <i>Aeromonas hydrophila</i> ABK39477.1; <i>Aeromonas salmonicida</i> YP_001142146.1; <i>Sodalis glossinidius</i> YP_456010.1; <i>Vibrio cholerae</i> YP_002810714.1; <i>Pseudomonas aeruginosa</i> NP_251807.1; <i>Erwinia carovora atrosepticum</i> YP_052242.1; <i>Streptococcus mutans</i> NP_721384.1; <i>Edwardsiella ictaluri</i> YP_002934124; <i>Edwardsiella tarda</i> YP_003296462; <i>Vibrio cholerae</i> YP_001217630.1; <i>Bacillus cereus</i> YP_085142.1; <i>Legionella longbeachae</i> CBJ10915; <i>Legionella pneumophila</i> YP_096311.1; <i>Xanthomonas axonopodis</i> NP_643032.1; <i>Xanthomonas campestris</i> NP_637897.1; <i>Mycobacterium tuberculosis</i> NP_218225.1; <i>Mycobacterium marinum</i> YP_001853481.1; <i>Chlamydia trachomatis</i> YP_002887982.1.</p

    Complementation of <i>asdA</i> gene with Asd<sup>+</sup><b>vectors.</b>

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    <p>(<b>A</b>) Plasmid profile of <i>E. ictaluri</i> Δ<i>asdA01</i> complemented with AsdA<sup>+</sup> vectors of different copy number. pEI1 (5.7 kb), pEI2 (4.9 kb), pYA3620 (3169 bp), pYA3493 (3113 bp), pYA3341 (2595 bp); Supercoiling ladder, from the top to the bottom: 16210 bp, 14174 bp, 12138 bp, 10102 bp, 8066 bp, 7045 bp, 6030 bp, 5012 bp, 3990 bp, 2972, 2067 bp; (<b>B</b>) Growth of <i>E. ictaluri</i> Δ<i>asdA01</i> complemented with different AsdA<sup>+</sup> vectors; The strains were grown in BHI at 28°C with agitation (180 r.p.m.).</p

    Synthesis of heterologous antigens in <i>E. ictaluri</i> J112 Δ<i>asdA01</i> by using AsdA<sup>+</sup> expression vectors.

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    <p><b>A.</b> Plasmid profile of J112 (pYA3994); <b>B.</b> Expression of GFP J112 (pYA3994); <b>C</b>. Expression and secretion of <i>Y. pestis</i> LcrV antigen by J112 (pYA3840); <b>D.</b> Expression and secretion of <i>S. pneumoniae</i> PspA-Rx1 antigen by J112 (pYA4088).</p

    Survival of catfish (<i>I. punctatus</i>) infected with <i>E. ictaluri</i> wild type and <i>E. ictaluri</i> Δ<i>asdA01</i> with and without Asd<sup>+</sup> vectors.

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    <p>The catfish were infected i.p. with 100 µl and orally with 20 µl of the respective <i>E. ictaluri</i> strain.</p><p>*death within 48 h.</p

    Bacterial strains and plasmids.

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    <p>Bacterial strains and plasmids.</p
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