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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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Joints, also known as articulations, are classified based on their structural characteristics, i.e., based on whether the articulating surfaces of the adjacent bones are directly connected by fibrous connective tissue or cartilage, or whether the articulating surfaces contact each other within a fluid-filled joint cavity. These differences serve to divide the joints of the body into three structural classifications.
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A time-series graph is a line graph with repeated measurements taken at successive intervals of time. It is also called a time series chart. To construct a time-series graph, one must look at both pieces of a paired data set. The horizontal axis is used to plot the time increments, and the vertical axis is used to plot the values of the variable that one is measuring. By using the axes in this way, each point on the graph will correspond to time and a measured quantity. The points on the graph...
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Brain lateralization refers to the division of mental processes and functions between the two hemispheres of the brain, a phenomenon that optimizes neural efficiency and underpins complex abilities in humans. This specialization allows each hemisphere to perform tasks where it has a comparative advantage, facilitating more refined cognitive capabilities across different domains.
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Associative Learning01:27

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Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
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In order to make good decisions, we use our knowledge and our reasoning. Often, this knowledge and reasoning is sound and solid. However, sometimes, we are swayed by biases or by others manipulating a situation. For example, let’s say you and three friends wanted to rent a house and had a combined target budget of $1,600. The realtor shows you only very run-down houses for $1,600 and then shows you a very nice house for $2,000. Might you ask each person to pay more in rent to get the...
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相关实验视频

Updated: Jul 4, 2025

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps
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基于嵌入的跨语言时间知识图的实体对齐.

Luyi Bai1, Nan Li1, Guishun Li1

  • 1School of Computer and Communication Engineering, Northeastern University (Qinhuangdao), Qinhuangdao 066004, China.

Neural networks : the official journal of the International Neural Network Society
|February 3, 2024
PubMed
概括
此摘要是机器生成的。

这项研究介绍了CTEA,一种用于跨语言时间知识图中的实体对齐的新方法. 通过整合时间动态和跨语言信息,CTEA提高了对准准确度,优于现有的方法.

关键词:
跨语言的跨语言.实体对齐 实体对齐 实体对齐图形神经网络的神经网络知识图嵌入知识图.时间知识图表时间知识图表.

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Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody
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科学领域:

  • 知识图 建筑 建筑知识图
  • 人工智能的人工智能
  • 自然语言处理自然语言处理.

背景情况:

  • 现有的实体对齐方法主要针对静态知识图.
  • 实体关系和属性的时间特征经常被忽视,导致对齐不准确.
  • 在时间知识图中跨语言实体对齐仍然是一个未被充分探索的研究领域.

研究的目的:

  • 为跨语言的时间知识图提出一个新的实体对齐方法.
  • 为了解决实体对齐中的静态和非时间方法的局限性.
  • 提高跨不同语言和时间维度匹配实体的准确性和可靠性.

主要方法:

  • 开发了CTEA,这是一个联合嵌入模型,结合了实体,关系和属性嵌入.
  • 利用图形卷积网络 (GCN) 和TransE进行嵌入生成.
  • 集成距离和相似性计算以提高跨语言对齐可靠性.

主要成果:

  • CTEA模型在实体调整任务中表现得更好.
  • 实验结果显示,与最先进的方法相比,Hits@m和MRR的增加约为0.82.4个百分点.
  • 提出的方法有效地处理知识图中的时间动态和跨语言复杂性.

结论:

  • CTEA为跨语言时间知识图中的实体对齐提供了一个强大的解决方案.
  • 联合嵌入方法和综合相似性措施提高了对齐精度.
  • 这项工作有助于推进知识图表完成和管理领域.