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相关概念视频

Improving Translational Accuracy02:07

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Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
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Extraction: Advanced Methods00:56

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Metal ions can be separated from one another by complexation with organic ligands–the chelating agent– to form uncharged chelates. Here, the chelating agent must contain hydrophobic groups and behave as a weak acid, losing a proton to bind with the metal. Since most organic ligands used in this process are insoluble or undergo oxidation in the aqueous phase, the chelating agent is initially added to the organic phase and extracted into the aqueous phase. The metal-ligand complex is...
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Predicting Products: SN1 vs. SN202:27

Predicting Products: SN1 vs. SN2

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Nucleophilic substitution reactions of alkyl halides can proceed via an SN1 or an SN2 mechanism. While in SN2 reactions, the nucleophile attacks the substrate simultaneously as the leaving group departs, in SN1 reactions, the substrate first dissociates to give the carbocation intermediate. Various factors such as the structure of the substrate, the strength of the nucleophile, and the nature of the solvent promote one mechanism over the other.
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The tip-of-the-tongue (TOT) phenomenon is a cognitive experience characterized by a temporary inability to retrieve specific information from memory despite having a strong feeling of knowing the information. Although individuals cannot access the target word or detail, they frequently recall related elements, such as its initial letter, syllable count, or context. This partial retrieval often causes frustration, as one might recognize a familiar face or know that a name starts with a specific...
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Predicting Products: Substitution vs. Elimination02:52

Predicting Products: Substitution vs. Elimination

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When a nucleophile and an alkyl halide react, nucleophilic substitution and β-elimination reactions compete to generate products.
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Sign Test for Matched Pairs01:17

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The sign test for matched pairs offers a robust method for comparing two paired samples, often for the effects of an intervention in one of them. This method is very useful in situations where the underlying distribution of the data is unknown. The test compares two related samples—often pre- and post-treatment measurements on the same subjects—to determine if there are significant differences in their median values.
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KBPT:基于知识的提示调整,用于零射击关系三重提取.

Qian Guo1, Yi Guo1, Jin Zhao2

  • 1Department of Computer Science and Engineering, East China University of Science and Technology, Shanghai, China.

PeerJ. Computer science
|June 10, 2024
PubMed
概括

本研究介绍了基于知识的提示调整 (KBPT),用于零射击关系三重提取,通过将训练数据与外部本体知识合成来有效地解决数据稀缺问题.

科学领域:

  • 自然语言处理自然语言处理.
  • 提取信息 提取信息
  • 知识表示 知识表示

背景情况:

  • 知识表示对于信息提取至关重要,但在零射击环境中经常被忽视.
  • 零射击关系三重提取 (RTE) 旨在识别培训数据中不存在的关系,面临数据稀缺的挑战.

研究的目的:

  • 开发一个新的框架,基于知识的快速调整 (KBPT),用于零射击关系三重提取.
  • 在RTE的低资源场景中解决数据稀缺问题.

主要方法:

  • KBPT将外部本体学知识与语言模型提示集成,以合成结构化培训示例.
  • 一个多重三重解码 (MTD) 算法被开发用于提取多重关系三重.
  • 一种集体培训方法共同优化了嵌入式表示,桥梁知识和文本.

主要成果:

  • KBPT表现出显著的改进,在Wiki-ZSL和TACRED-Revisit数据集上分别实现了高达14.65%和24.19%的F1得分提升.
  • 该模型在F1得分,P-R曲线和AUC方面表现优于当前最先进的 (SOTA) 模型.
  • 该框架是无模型的,适用于各种预训练语言模型 (PLM).

结论:

关键词:
基于知识的知识.快速调整调整的提示零射击关系三重提取零射击关系.

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  • KBPT为零射击关系三重提取提供了有效的解决方案,特别是在资源较低的环境中.
  • 外部知识和基于提示的合成的整合提高了提取性能.
  • 拟议的方法在具有挑战性的,数据稀缺的场景中推进了信息提取领域.