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相关概念视频

Sequence Networks of Rotating Machines01:24

Sequence Networks of Rotating Machines

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A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...
126
Heuristics01:21

Heuristics

112
Heuristics are problem-solving strategies that use mental shortcuts to simplify decision-making. Unlike algorithms, which must be followed precisely to achieve a correct result, heuristics offer a general problem-solving framework. They save time and energy but can sometimes lead to less rational decisions.
People often rely on heuristics when faced with an overload of information, limited time, low importance of the decision, limited information, or when a heuristic readily comes to mind. For...
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Structural Classification of Joints01:20

Structural Classification of Joints

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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.
A fibrous joint is where the adjacent bones are united by fibrous connective...
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Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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Mass Analyzers: Common Types01:19

Mass Analyzers: Common Types

659
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...
659
Storage01:23

Storage

107
A schema is a mental framework that helps individuals organize and interpret information. Schemata, formed from previous experiences, influence how we process new information: how we encode it, the inferences we make, and how we retrieve it. For instance, a schema for what a typical classroom looks like might include desks, a teacher's desk, a whiteboard, and students in such an environment. This expectation helps us quickly understand and navigate new classrooms without needing to analyze...
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相关实验视频

Updated: Jul 26, 2025

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
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MAGUS:机器学习和图形理论辅助的通用结构搜索器.

Junjie Wang1, Hao Gao1, Yu Han1

  • 1National Laboratory of Solid State Microstructures, School of Physics and Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing 210093, China.

National science review
|June 19, 2023
PubMed
概括

我们开发了MAGUS,这是一种使用机器学习和图形理论进行晶体结构预测的方法. 这种方法通过降低计算成本和有效地探索复杂系统,加速发现新材料和新现象.

关键词:
在 ab-initio 计算中.寻找晶体结构的搜索密度函数理论密度函数理论高压相位过渡的高压相位过渡.设计材料设计材料的设计.

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科学领域:

  • 材料科学 材料科学 材料科学
  • 固态物理 固态物理
  • 计算材料科学科学 计算材料科学

背景情况:

  • 第一原理计算对于晶体结构预测是成功的,但由于结构复杂性和高计算成本,大系统面临挑战.
  • 现有的方法在复杂材料和大型原子系统的可扩展性方面存在困难,限制了更广泛的应用.

研究的目的:

  • 介绍MAGUS,一种新的晶体结构预测方法,旨在克服大型原子系统计算成本和复杂性的局限性.
  • 证明机器学习潜力和基于图形理论的分解在加速材料发现方面的有效性.

主要方法:

  • 开发了MAGUS,一种基于进化算法的晶体结构预测方法,集成机器学习潜力和图形理论.
  • 利用机器学习潜力大幅减少昂贵的第一原则计算的数量.
  • 采用基于图形理论的晶体分解,以有效地减少结构预测所需的配置数量.

主要成果:

  • 通过机器学习潜力,MAGUS有效地降低了计算费用,从而最大限度地减少了对第一原则计算的需求.
  • 基于图形理论的晶体分解通过减少配置空间,显著简化了对目标晶体结构的搜索.
  • 在预测行星内部化合物和新型功能材料方面展示了成功的应用.

结论:

  • MAGUS代码通过有效预测晶体结构,加速了新材料和新现象的发现.
  • 机器学习和图形理论的整合提供了一种强大的方法来应对计算材料科学的挑战.
  • 像MAGUS这样的晶体结构预测方法对于推进材料科学和固态物理学具有重要价值.