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Titlebook: High Resolution Spectral Atlas of Nitrogen Dioxide 559–597 nm; Kiyoji Uehara,Hiroyuki Sasada Book 1985 Springer-Verlag Berlin Heidelberg 1

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樓主: tricuspid-valve
11#
發(fā)表于 2025-3-23 13:14:33 | 只看該作者
Introduction,n . = 1/2 of the unpaired electron, hyperfine structure due to the nuclear spin . = 1 of the .N atom, and overlapping of the excited electronic states are obviously among the causes of its complexity. In addition, it has been found that the coupling between the electronic states through various pert
12#
發(fā)表于 2025-3-23 16:30:28 | 只看該作者
13#
發(fā)表于 2025-3-23 20:21:02 | 只看該作者
14#
發(fā)表于 2025-3-24 00:06:23 | 只看該作者
,Selected Bibliography 1978–1983,he list has about 130 selected papers, including those reporting non-laser experiments and theoretical work which were not referred to in Chap. 3. All papers are given with full titles. The papers were searched for mainly through the CAS Database. A compilation of earlier work before 1978 was given
15#
發(fā)表于 2025-3-24 04:39:31 | 只看該作者
0172-6218 e investigations the molecule still resists complete analysis of its spectrum. Because of the high density of lines, it is apparent that high-resolution measurements are essential to a thorough understanding of the spectrum. The major part of this book consists of an atlas, described in Chap. 2, of
16#
發(fā)表于 2025-3-24 10:25:26 | 只看該作者
17#
發(fā)表于 2025-3-24 12:00:38 | 只看該作者
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發(fā)表于 2025-3-24 15:27:00 | 只看該作者
19#
發(fā)表于 2025-3-24 19:37:52 | 只看該作者
Kiyoji Uehara Ph.D.,Hiroyuki Sasada Ph.D.ive applications in German. Against this background, we position ourselves as advocates of an accessibility-by-hypertext approach. Further, we put forward for discussion building blocks for an AI Act-compliant self-regulated framework for participation-driven text simplification systems.
20#
發(fā)表于 2025-3-25 01:52:31 | 只看該作者
Kiyoji Uehara Ph.D.,Hiroyuki Sasada Ph.D.object pressure, and floor vibration sensors) are also used for the user’s health and behavior monitoring. The sensors can be connected to local devices to process raw signals and take decisions based on distinguished machine learning approaches. This chapter will focus on sensors and features for assisted living technologies.
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