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Titlebook: Die physikalischen Erscheinungen der Bogenentladung in ihrer Bedeutung für die spektralanalytischen ; Habilitationsschrift Walter Rollwagen

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樓主: mortality
21#
發(fā)表于 2025-3-25 05:01:55 | 只看該作者
Hanjun Jiang,Xinkai Chen,Zhihua Wanged by state-of-the-art organic semiconductors are remarkable in their tolerance to disorder, their ability to display high charge carrier mobility values and bipolar transport, and in that they can be engineered to display optical activity in the spectral range from the visible to the near-infrared.
22#
發(fā)表于 2025-3-25 07:40:01 | 只看該作者
23#
發(fā)表于 2025-3-25 14:36:44 | 只看該作者
24#
發(fā)表于 2025-3-25 18:27:28 | 只看該作者
Principles of AEoI-CRSuss the bilateral and multi-lateral components of AEoI and similarities to FATCA. The chapter outlines the basis for due diligence under CRS as the part opf AEoI that applies to financial institutions as well as the AEoI itself that handles, predominantly, the data exchange between partner competent
25#
發(fā)表于 2025-3-25 23:46:07 | 只看該作者
Picosecond Distributed Feedback Dye Laser Tunable in a Broad Spectral Rangeectral range. The generation of tunable picosecond pulses in dye lasers has been demonstrated in a number of experiments, in particular with cw dye lasers. Unfortunately, laser systems allowing single ultrashort high-power pulses that are tunable in a broad spectral region are still too complicated
26#
發(fā)表于 2025-3-26 01:42:44 | 只看該作者
27#
發(fā)表于 2025-3-26 06:33:45 | 只看該作者
28#
發(fā)表于 2025-3-26 09:52:26 | 只看該作者
,Kapitel?1 Einführung, Wohnungseigentümergemeinschaft ergibt sich Konfliktpotential. Aus verfassungsrechtlicher Perspektive stellt sich die Frage, welche Ma?st?be zur Aufl?sung dieser Konflikte zwischen verschiedenen Grundrechtstr?gern bereitstehen und insbesondere, ob das Wohnungseigentum als verfassungsrechtliches Eigentum i.S.d. Art. 14 GG zu qualifizieren ist.
29#
發(fā)表于 2025-3-26 14:03:03 | 只看該作者
30#
發(fā)表于 2025-3-26 17:23:38 | 只看該作者
Mango Species Detection from Raw Leaves Using Image Processing System,ing. This research used convolutional neural network (CNN) and deep learning for training the dataset. This method can showcase the species of the mango sapling only by observing the image of a leaf holding an accuracy of 78.65%.
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