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相关概念视频

Labeling DNA Probes03:31

Labeling DNA Probes

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DNA probes are fragments of DNA labeled with a reporter tag to enable their detection or purification. The resulting labeled DNA probes can then hybridize to target nucleic acid sequences through complementary base-pairing, and may be used to recover or identify these regions.
Radioisotopes, fluorophores, or small molecule binding partners like biotin or digoxigenin, are the most widely used reporter tags for labeling DNA probes. These labels can be attached to the probe DNA molecule via...
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Leaky Scanning02:28

Leaky Scanning

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During most eukaryotic translation processes, the small 40S ribosome subunit scans an mRNA from its 5' end until it encounters the first start AUG codon. The large 60S ribosomal subunit then joins the smaller one to initiate protein synthesis. The location of the translation initiation is largely determined by the nucleotides near the start codon as there may be multiple translation initiation sites present on the mRNA.  Marilyn Kozak discovered that the sequence RCCAUGG (where R...
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The Contractile Ring02:15

The Contractile Ring

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Contractile rings are composed of microfilaments and are responsible for separating the daughter cells during cytokinesis. Contractile ring assembly proceeds along with other cell cycle events; however, very few mechanistic details are known about the timing and coordination of the contractile rings with the cell cycle.
A small GTPase, RhoA, controls the function and assembly of the contractile ring. RhoA belongs to the Ras superfamily of proteins. The activation of formins by RhoA promotes...
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Mass Analyzers: Common Types01:19

Mass Analyzers: Common Types

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The quadrupole mass analyzer consists of four cylindrical metal rods arranged in a diamond carrying a DC voltage and a radio-frequency AC voltage. The motion of ions through the quadrupole depends on the field strength, causing only ions of a certain m/z to resonate successfully and strike the detector at a given field strength. Though the transmission rate for these analyzers is high, the exact elemental composition of the sample is not determined because of low resolution; however, they are...
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Distribution Reliability and Automation01:25

Distribution Reliability and Automation

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Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
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Labeling Emotion01:20

Labeling Emotion

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Emotional labeling is a cognitive process that involves identifying and naming one's emotions, such as anger, fear, happiness, or sadness. It allows individuals to recognize and express their internal emotional states, a critical aspect of emotional regulation and communication. Labeling emotions requires more than mere recognition; it also involves drawing upon memory and contextual cues to understand the current situation and apply a corresponding emotional label. For instance, feeling...
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相关实验视频

Updated: Mar 14, 2026

Proteome-wide Quantification of Labeling Homogeneity at the Single Molecule Level
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Proteome-wide Quantification of Labeling Homogeneity at the Single Molecule Level

Published on: April 19, 2019

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DIVE:一个多标签智能合约漏洞数据集

Shikah J Alsunaidi1, Hamoud Aljamaan2,3, Mohammad Hammoudeh1,4

  • 1Information and Computer Science Department, King Fahd University of Petroleum and Minerals, Dhahran, 31261, Saudi Arabia.

Scientific data
|March 13, 2026
PubMed
概括
此摘要是机器生成的。

本研究介绍了DIVE,这是一个用于检测智能合约 (SC) 漏洞的新数据集. DIVE提供了大量,多样化的真实世界SCs集合,具有全面的功能,以提高机器学习模型的可靠性.

相关实验视频

Last Updated: Mar 14, 2026

Proteome-wide Quantification of Labeling Homogeneity at the Single Molecule Level
08:29

Proteome-wide Quantification of Labeling Homogeneity at the Single Molecule Level

Published on: April 19, 2019

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科学领域:

  • 计算机科学 计算机科学
  • 软件工程 软件工程 软件工程
  • 网络安全 网络安全

背景情况:

  • 智能合约 (SC) 的漏洞带来了重大风险,导致财务损失和功能失败.
  • 现有用于SC漏洞检测的数据集通常受到大小,不平衡,不一致的标签和非标准化的特征的限制,这阻碍了可靠的机器学习 (ML) 模型开发.
  • 当前的特征表示往往忽略了合同生命周期的不同阶段,影响了模型的概括性和基准准确性.

研究的目的:

  • 引入DIVE,这是一种新的多标签数据集,旨在克服现有的SC漏洞数据集的局限性.
  • 为培训和评估用于SC漏洞检测的ML模型提供全面的资源.
  • 在智能合约生命周期的不同阶段实现更可靠和更普遍的漏洞检测.

主要方法:

  • DIVE包含了在2016年至2024年间部署的22,330个现实世界SC,涵盖了主要的Solidity编译器版本.
  • 根据去中心化应用安全项目 (DASP) 的十大分类,SCs对八种漏洞类型进行了注释.
  • 使用基于功率的投票和后期过的标准化多工具标签管道被采用,纠正了拒绝服务 (DoS) 和时间操纵漏洞中的重大错误阳性.

主要成果:

  • DIVE数据集提供了221个部署前和176个部署后的功能,提供了生命周期特定的功能集.
  • 标签管道成功纠正了DoS中的14.3%的假阳性和时间操纵漏洞中的24.9%.
  • 该数据集支持通过开源框架进行可重现的基准测试,促进与不断变化的脆弱性模式保持一致的定期重建.

结论:

  • DIVE解决了现有的SC漏洞数据集中的关键结构和特征级限制.
  • 数据集的综合性和生命周期特征提高了基于ML的SC漏洞检测的可靠性和通用性.
  • 在智能合约安全的不断变化的环境中,DIVE促进可复制的研究和可适应的漏洞检测方法.