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相关概念视频

Introduction to Nuclear Reprogramming01:14

Introduction to Nuclear Reprogramming

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Nuclear reprogramming is the process of switching gene expression of one cell type to that of another cell type, usually from a differentiated cell state to an undifferentiated cell state. Differentiation occurs during processes such as development and morphogenesis, tissue regeneration, and malignancy. Cells can also be artificially induced to reprogram their gene expression by techniques such as nuclear transfer, induced pluripotency, and cell fusion. Such techniques have many applications in...
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Methods of Nuclear Reprogramming01:24

Methods of Nuclear Reprogramming

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Nuclear reprogramming is a process of transforming one cell type into an unrelated cell type by epigenetic changes that alter the cell’s original gene expression pattern. Such epigenetic changes force cells to express a different set of genes, which play a significant role in inducing transformation into other cell types. Nuclear reprogramming offers applications in reproductive cloning for livestock propagation and regenerative medicine — developing patient-specific cells for...
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Directionality of Nuclear Transport01:42

Directionality of Nuclear Transport

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Ras-related nuclear protein or Ran is a small G protein that cycles between its GTP and GDP bound states. Ran specific regulators, a Ran GTPase Activating Protein or RanGAP present in the cytosol and a Ran guanine nucleotide exchange factor or RanGEF present inside the nucleus regulate GTP/GDP exchange. A high concentration of GTP inside the cells, in addition to this asymmetric distribution of  Ran-specific regulators, leads to a higher RanGTP concentration inside the nucleus. This...
3.2K
Nuclear Binding Energy02:13

Nuclear Binding Energy

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The difference between the calculated and experimentally measured masses is known as the mass defect of the atom. In the case of helium-4, the mass defect indicates a “loss” in mass of 4.0331 amu – 4.0026 amu = 0.0305 amu. The loss in mass accompanying the formation of an atom from protons, neutrons, and electrons is due to the conversion of that mass into energy that is evolved as the atom forms. The nuclear binding energy is the energy produced when the atoms’ nucleons...
12.4K
Nuclear Stability03:18

Nuclear Stability

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Protons and neutrons, collectively called nucleons, are packed together tightly in a nucleus. With a radius of about 10−15 meters, a nucleus is quite small compared to the radius of the entire atom, which is about 10−10 meters. Nuclei are extremely dense compared to bulk matter, averaging 1.8 × 1014 grams per cubic centimeter. If the earth’s density were equal to the average nuclear density, the earth’s radius would be only about 200 meters.
To hold positively charged protons together...
18.8K
Nuclear Overhauser Enhancement (NOE)01:07

Nuclear Overhauser Enhancement (NOE)

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Irradiation of a spin-active nucleus causes an increase or decrease in the signal intensity of neighboring nuclei that are not necessarily chemically bonded or involved in J-coupling.  This phenomenon, called the Nuclear Overhauser Enhancement (NOE), results from through-space interactions between the nuclear spins. The NOE effect decreases with increasing internuclear distance and is generally not observed beyond 4 angstroms. In NOE, dipole-dipole interactions between neighboring...
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相关实验视频

Updated: Jul 4, 2025

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
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一个拉格朗格编程神经网络方法用于核规范优化.

Xiangguang Dai1, Jian Qiu2, Chaoyang Wan2

  • 1Chongqing Engineering Research Center of Internet of Things and Intelligent Control Technology, Chongqing Three Gorges University, Chongqing, China.

PloS one
|February 8, 2024
PubMed
概括
此摘要是机器生成的。

本研究引入了一种连续时间优化方法,拉格朗日编程神经网络 (LPNN),以解决核规范最小化 (NNM) 问题,与传统技术相比增强图像恢复.

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A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM
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Surrogate Model Development for Digital Experiments in Welding
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Surrogate Model Development for Digital Experiments in Welding

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A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM
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科学领域:

  • 优化优化 优化优化
  • 机器学习 机器学习
  • 图像处理 图像处理

背景情况:

  • 传统的优化方法在解决核规范最小化 (NNM) 问题时面临着挑战.
  • 核规范最小化对于各种应用,包括图像恢复至关重要.

研究的目的:

  • 为核规范最小化问题提出一种新的连续时间优化方法.
  • 引入拉格朗日编程神经网络 (LPNN) 作为NNM的解决方案.
  • 分析拟议LPNN的收性质.

主要方法:

  • 将NNM问题重新构成矩阵形式.
  • 开发一个拉格朗日编程神经网络 (LPNN).
  • 使用Lyapunov方法来确定LPNN的收条件.

主要成果:

  • 拟议的LPNN证明了通过实验结果验证的趋同.
  • 与传统的NNM算法相比,LPNN算法在图像恢复方面表现优越.

结论:

  • 使用LPNN的连续时间优化方法对于解决NNM问题是有效的.
  • 与现有方法相比,LPNN提供了改进的图像恢复功能.