Jove
Visualize
联系我们

相关概念视频

Scalar and Vector Triple Products01:06

Scalar and Vector Triple Products

2.4K
Two vectors can be multiplied using a scalar product or a vector product. The resultant of a scalar product is scalar, while with vector products, the resultant is a vector. These rules of the scalar or vector product between two vectors can be applied to multiple vectors to obtain meaningful combinations. The scalar triple product is the dot product of a vector with the cross product of two vectors.
The scalar triple product is the dot product of a vector with the cross product of two vectors....
2.4K
Interpreting ¹H NMR Signal Splitting: The (n + 1) Rule01:10

Interpreting ¹H NMR Signal Splitting: The (n + 1) Rule

1.3K
In the AX proton spin system, proton A can sense the two spin states of a coupled proton X, resulting in a doublet NMR signal with two peaks of equal (1:1) intensity. When proton A is coupled to two equivalent protons (AX2 spin system), the spin states of each X can be aligned with or against the external field, creating three possible scenarios. This results in a 1:2:1  triplet signal, where the central peak corresponds to the chemical shift of A and is twice as large or intense as the...
1.3K
¹H NMR Signal Multiplicity: Splitting Patterns01:13

¹H NMR Signal Multiplicity: Splitting Patterns

5.2K
When protons A and X are coupled, their nuclear spin energy levels are slightly modified. This is because the energy required to excite proton A to a spin state parallel to proton X is slightly different from the energy required for it to become anti-parallel to spin X. Consequently, there are two possible excitation frequencies for A (A1 and A2), depending on the spin state of X, and vice versa. The mutual nature of coupling implies that the difference between frequencies A1 and A2, indicated...
5.2K
From DNA to Protein03:06

From DNA to Protein

18.3K
The flow of genetic information in cells from DNA to mRNA to protein is described by the central dogma, which states that genes specify the sequence of mRNAs, which in turn specify the sequence of amino acids making up all proteins. The decoding of one molecule to another is performed by specific proteins and RNAs. Because the information stored in DNA is so central to cellular function, it makes intuitive sense that the cell would make mRNA copies of this information for protein synthesis...
18.3K
Trihybrid Crosses02:27

Trihybrid Crosses

23.3K
Trihybrid Crosses
Some of Mendel’s crosses examined three pairs of contrasting characteristics. Such a cross is called a trihybrid cross. A trihybrid cross is a combination of three individual monohybrid crosses. For example, plant height (tall vs. short), seed shape (round vs. wrinkled), and seed color (yellow vs. green).
The F1 generation plants of a trihybrid cross are heterozygous for all three traits and produce eight gametes. Upon self-fertilization, these gametes have an equal...
23.3K
¹H NMR: Pople Notation01:09

¹H NMR: Pople Notation

1.8K
The Pople nomenclature system classifies spin systems based on the difference between their chemical shifts. Coupled spins are denoted by capital letters with subscripts indicating the number of equivalent nuclei. When the coupled nuclei have well-separated chemical shifts, they are assigned letters that are far apart in the alphabet, such as A and X. When the difference in chemical shifts is small, coupled nuclei are named using adjacent letters of the alphabet (AB, MN, or XY).
A proton...
1.8K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Corrigendum to "Mechanistic insights into the role of USP14 in adipose tissue macrophage recruitment and insulin resistance in obesity" [Int. J. Biol. Macromol. 267 (2024) 131645].

International journal of biological macromolecules·2026
Same author

Artificial intelligence in thoracic surgery: a narrative review of clinical advances and applications in 2025.

Journal of thoracic disease·2026
Same author

Post-liver transplantation delirium: Pathogenesis, risk factors, clinical management, and future directions.

Liver transplantation : official publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society·2026
Same author

Spin-Polarized Luminescence Modulated by Magnetic Coupling in Glass-Embedded Eu<sup>2+</sup>-Doped Lead-Free Perovskite Nanocrystals.

ACS nano·2026
Same author

Ecosystem simulation: the software to platform leap.

Scientific reports·2026
Same author

Hydrogen crossover raises serious concerns on proton exchange membrane water electrolyzer.

Innovation (Cambridge (Mass.))·2026
Same journal

From Pixels to Patterns: A Multidimensional Framework to Decode Cytoskeletal Organization.

Computational and structural biotechnology journal·2026
Same journal

A Large Concept Model for Mechanistic Simulation of Disease Trajectories: A Hypothesis-Generating Exemplar for Pediatric Acute Lymphoblastic Leukemia.

Computational and structural biotechnology journal·2026
Same journal

Adversarial Sequence Mutations in AlphaFold and ESMFold Reveal Nonphysical Structural Invariance, Confidence Failures, and Concerns for Protein Design.

Computational and structural biotechnology journal·2026
Same journal

High-Throughput Prediction of Protein-Protein Interactions Uncovers Hidden Molecular Networks in Biosynthetic Gene Clusters.

Computational and structural biotechnology journal·2026
Same journal

A Region-Aware Structured Framework Improves Prediction of Gene Expression from DNA Methylation.

Computational and structural biotechnology journal·2026
Same journal

Ensemble Machine Learning Approaches Predict Survival in Lower-Grade Glioma Based on Glycosphingolipid Gene Expression and Metabolic Modeling.

Computational and structural biotechnology journal·2026
查看所有相关文章
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关实验视频

Updated: Jun 28, 2025

Generating Strictly Controlled Stimuli for Figure Recognition Experiments
05:39

Generating Strictly Controlled Stimuli for Figure Recognition Experiments

Published on: March 18, 2019

5.2K

探索简单的三重体表示学习学习.

Zeyu Ren1, Quan Lan2, Yudong Zhang1,3

  • 1University of Leicester, Leicester, UK.

Computational and structural biotechnology journal
|April 18, 2024
PubMed
概括
此摘要是机器生成的。

这项研究介绍了SimTrip,这是一种用于医学图像分析的新型无监督表示学习模型. 它有效地从未标记的数据中学习,优于目前使用部分标签的方法.

关键词:
相反的学习学习.深度学习是一种深度学习.机器学习是机器学习.医疗图像分析 医学图像分析自主监督学习学习半监督学习 半监督学习

更多相关视频

BEST: Barcode Enabled Sequencing of Tetrads
12:59

BEST: Barcode Enabled Sequencing of Tetrads

Published on: May 1, 2014

10.1K
Integrating a Triplet-triplet Annihilation Up-conversion System to Enhance Dye-sensitized Solar Cell Response to Sub-bandgap Light
11:26

Integrating a Triplet-triplet Annihilation Up-conversion System to Enhance Dye-sensitized Solar Cell Response to Sub-bandgap Light

Published on: September 12, 2014

12.6K

相关实验视频

Last Updated: Jun 28, 2025

Generating Strictly Controlled Stimuli for Figure Recognition Experiments
05:39

Generating Strictly Controlled Stimuli for Figure Recognition Experiments

Published on: March 18, 2019

5.2K
BEST: Barcode Enabled Sequencing of Tetrads
12:59

BEST: Barcode Enabled Sequencing of Tetrads

Published on: May 1, 2014

10.1K
Integrating a Triplet-triplet Annihilation Up-conversion System to Enhance Dye-sensitized Solar Cell Response to Sub-bandgap Light
11:26

Integrating a Triplet-triplet Annihilation Up-conversion System to Enhance Dye-sensitized Solar Cell Response to Sub-bandgap Light

Published on: September 12, 2014

12.6K

科学领域:

  • 计算机视觉 计算机视觉
  • 机器学习 机器学习
  • 医学图像分析 医学图像分析

背景情况:

  • 监督学习需要大量的标记数据,这在医学成像中是稀缺和昂贵的.
  • 从未标记的医疗图像中提取知识是一个重大挑战.

研究的目的:

  • 为医疗图像分析开发一个高效的无监督表示学习模型.
  • 利用未标记的数据来克服监督方法中数据稀缺性的局限性.

主要方法:

  • 介绍了SimTrip,一个简单的三重视图无监督表示学习模型.
  • 利用三重视图架构和损失函数进行高效的知识提取.
  • 在两个具有小批量大小的医疗图像数据集上进行测试.

主要成果:

  • 在使用部分标签的医疗图像数据集上取得了卓越的表现.
  • 在无监督表示学习中超越了最先进的方法.
  • 从未标记的数据中提取有效的知识.

结论:

  • SimTrip为计算机视觉中的无监督表示学习提供了一个新的范式.
  • 该模型为未来基于SimTrip的复杂方法建立了基线.
  • 这种方法是高效和有效的,即使有有限的标记数据.