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関連する概念動画

State Space Representation01:27

State Space Representation

617
The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...
617
Graphical Representation of Inequalities01:28

Graphical Representation of Inequalities

236
The graph of the equation where y equals x squared forms a curve known as a parabola. This curve acts as a boundary in the coordinate plane, dividing it into distinct regions based on the relative position of points.When the equality sign in the equation is replaced with an inequality—such as greater than, less than, greater than or equal to, or less than or equal to—the graphical representation changes from a single curve into a broader shaded area that signifies the set of all...
236
Control Volume and System Representations01:16

Control Volume and System Representations

1.6K
Two key frameworks are employed to analyze mass, energy, and momentum transfer: the control volume approach and the system approach. These frameworks offer different perspectives, depending on whether the focus is on a specific region in space (control volume approach) or a defined mass of fluid (system approach).
The control volume approach considers a stationary region in space through which fluid flows. This region is bounded by a control surface.  For instance, in the case of water...
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Sensory Modalities01:15

Sensory Modalities

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Sensation typically is the process by which the sensory receptors and sense organs detect stimuli from the internal and external environment and transmit this information to the central nervous system for processing.
General senses refer to the broad category of sensory information detected by receptors in the body and can be further grouped into somatic and visceral senses. Somatic sensations include touch, pressure, temperature, and pain and are essential for navigating our environment and...
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Vector Representation of Complex Numbers01:16

Vector Representation of Complex Numbers

563
Complex numbers, represented in Cartesian coordinates, can also be visualized as vectors. These vectors can be expressed in polar form, emphasizing their magnitude and angle. When a complex number is input into a function, the output is another complex number, highlighting the function's zero point from which the vector representation can originate.
Consider a function defined as the product of the complex factors in the numerator divided by the product of the complex factors in the...
563
Graphical and Analytic Representation of Sinusoids01:20

Graphical and Analytic Representation of Sinusoids

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Analyzing two sinusoidal voltages with equal amplitude and period but different phases on an oscilloscope, an instrument used to display and analyze waveforms, involves a three-step process.
The first step is measuring the peak-to-peak value, which is twice the amplitude of the sinusoid. This provides information about the maximum voltage swing of the waveform.
Secondly, the period and angular frequency are determined. The period is the time taken for one complete cycle of the waveform, while...
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関連する実験動画

Updated: Feb 16, 2026

Using Virtual Reality to Transfer Motor Skill Knowledge from One Hand to Another
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マルチ・トゥ・ユニモダル知識移転 分子表現学習のための予備訓練

Zhankun Xiong1, Ziyan Wang1, Feng Huang1

  • 1College of Informatics, Huazhong Agricultural University, Wuhan, China.

Nature communications
|February 14, 2026
PubMed
まとめ

この研究は,分子表現学習 (MRL) のための新しいマルチモダルのプレトレーニングフレームワークであるM2UMolを紹介しています. M2UMolは,不完全なデータであっても,複数の分子データ型から2Dグラフエンコーダーに知識を効果的に転送し,薬剤発見のタスクを改善します.

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Multi-Modal Signals for Analyzing Pain Responses to Thermal and Electrical Stimuli

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関連する実験動画

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科学分野:

  • 計算化学はコンピュータ化学である.
  • 化学情報学 (Cheminformatics) とは,化学情報学 (Cheminformatics) とは,化学情報学 (Cheminformatics) とは,化学情報学 (Cheminformatics) とは,化学情報学 (Cheminformatics) とは,化学情報学 (Cheminformatics) とは,化学情報学 (Cheminformatics) とは,化学情報学 (Cheminformatics) とは,化学情報学 (Cheminformatics) とは,化学情報学 (Cheminformatics) とは,化学情報学 (Cheminformatics) とは,
  • ドラッグ・ディスカバリー・ドラッグ・ディスカバリー

背景:

  • 分子表現学習 (MRL) は,コンピュータによる薬剤発見に不可欠です.
  • 既存のマルチモダルのMRL方法は,完全な分子データを要求することが多く,現実世界の適用性を制限しています.
  • 多くのシナリオには,特に2Dトポロジカルグラフを超えて,完全な分子様式が欠けている.

研究 の 目的:

  • 不完全な分子データを扱うマルチモダルの予備研修MRLフレームワーク (M2UMol) を開発する.
  • 複数のモダリティから2Dグラフエンコーダーへの効果的な知識転送を可能にします.
  • 薬剤発見のタスクにおけるMRLの性能と効率を改善する.

主な方法:

  • M2UMolを提案し,2D分子グラフを他のモダリティと一致させるフレームワークである.
  • 2Dエンコーダをモダリティ分類器で共同で予備訓練し,マルチモダルの知識を転送します.
  • ダウンストリームタスクにおける不完全な2Dデータからのマルチモダルの情報のシミュレーションを可能にします.

主要な成果:

  • M2UMolは,既存の方法と比較して,様々な分子タスクにおいて優れたパフォーマンスを示しています.
  • このフレームワークは,先駆的なモデルよりも高い予備訓練効率を達成します.
  • 実験結果は,M2UMol.を使用したマルチモダルの知識移転の有効性を検証しています.

結論:

  • M2UMolは,不完全な分子データでマルチモダルの予備訓練のための堅牢なソリューションを提供します.
  • このフレームワークは,分子マルチモダルの情報の正確なシミュレーションを容易にし,薬物発見を強化します.
  • M2UMolをベースにしたユーザーフレンドリーなパッケージが用意されており,様々な化学情報学ツールを統合しています.