Titlebook: Lautbildungsschwierigkeit im Deutschen; Eine phonetisch- p?d Heinrich M?hring Book 1938 Springer-Verlag Berlin Heidelberg 1938 Deutsch.deut

長(zhǎng)處

雪上輕舟飛過(guò)

Land and Food Access in the Context of Climate Change: Implications to Rural Development in Mozambi to rural livelihoods, land access and food production. It sheds light on the fact that both direct and indirect impacts of climate change are adversely affecting livelihoods and causing land expropriation in rural areas. Both of these impacts will shape rural development in the next decades in coun

FEAT

Analysis of a Database of Research Projects Using Text Mining and Link Analysision technology European program in years 2000–2005. The main items in the research project database were textual description of each project and the list of organizations participating in the project. The goal was to find various informative insights into the research project database, which would e

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Debrief

Untersuchungen über den Metabolismus der Digitalisglykoside unter Verwendung radioaktiver Isotopewirksame Glykoside sehr empfindlich ist und deshalb nur geringe Dosen verabreicht werden k?nnen. Entsprechendes gilt für die meisten Tiere, mit Ausnahme der Ratte, deren Herz gegen Digitalisglykoside sehr unempfindlich ist. Der Ratte k?nnen pro kg K?rpergewicht etwa 100fach h?here Dosen als dem Mens

lethal

drusen

to construct scenarios that will help teachers to adopt emer.This book reports on a novel and comprehensive approach to the uptake of ICT in Schools. It focuses on key questions, pedagogically sound ways of introducing ICT, new technical artifacts supporting the approach, the evaluation in a large-s

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Anni Loukomies,Taina Makkonen,Jari Lavonen,Kalle Juuti Aryl Halides and Arylboronic Acids. Assembly of N-containing heterocycles via Pd and Cu-catalyzed C-N bond formation reactions. Copper-Catalyzed C(aryl)-N Bond Formation.978-3-662-50566-3978-3-642-40546-4Series ISSN 1436-6002 Series E-ISSN 1616-8534

HAWK

Topic Model Kernel: An Empirical Study towards Probabilistically Reduced Features for Classificatiopic models. The applicability of our proposed kernel is demonstrated in several classification tasks from real world datasets. We outperform existing kernels on the distributional features and give the comparative results on non-probabilistic data types.

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