In physics, slowly varying envelope approximation [1] (SVEA, sometimes also called slowly varying asymmetric approximation or SVAA) is the assumption that the envelope of a forward-travelling wave pulse varies slowly in time and space compared to a period or wavelength.

Svea's orbit is determined by observations dating back to March 21, 1892. It was last officially observed on Feb. 19, 2023. The IAU Minor Planet Center records 4,515 observations used to determine its orbit. Scientists have been able to determine this object's shape: View asteroid Svea in 3D. Accessibility and Exploration

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他们开发了一个名为 SVEA（Structural Variation detection with Enhanced AlexNet drchitecture）的深度学习模型，就像打造了一件超级厉害的 “武器”，专门用来对付基因组中的结构变异。 研究发现，SVEA 在检测复杂 SVs 方面表现出色，比现有的方法准确率提高了约 4%，这一成果意义重大，为基因组结构变异检测领域带来了新的希望，让我们在探索基因奥秘、预防和治疗相关疾病的道路上又前进了一大步。 研究人员在这项研究中用到了几个关键的技术方法。 首 …

Thorough end-capping and low polarity of the silica surface of SVEA C18 Gold gives significantly better peak shapes of anti-depressants, compared to competitor brands. SVEA C18 Gold is the first-choice LC column for a wide range of analytes.

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Nanologica offers best-in-class HPLC analytical columns that provide excellent chromatographic performance with sharp peak shapes and robust performance under extreme pH conditions (<1 and > 10 respectively).

2024年1月13日 · 在DQN中，Q更新的目标值过高的方差会阻碍算法的学习，由此才引入了Q-target网络来降低目标值的不稳定性。 而现有的数据增强方法中（比如Drq），在更新Q函数时会对 s t + 1 进行数据增强，这样就会对 Q (s t + 1 a u g, a ′) 引入很高的方差，同时由于a‘也是通过 π (. | s t + 1 a u g) 得到的，这样就会产生两次的累积误差。 本文提出的改进方法很简单，就是得到target Q值时，状态输入不使用数据增强（如果有actor网络也使用原始观测输入）。 效果很显 …

2018年8月9日 · Thorough end-capping together with very low acidity and homogenously distributed residual silanol groups gives excellent peak shape and efficiencies with bases as well as acidic compounds. SVEA C18 will experience reduced ligand cleavage at low pH due to extremely inert silica and high ligand density, providing excellent stability with acidic ...

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