Sentence examples for prepare for the deployment of from inspiring English sources

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The EU-supported project EUROPAIRS (2009 2011) has therefore carried out a comprehensive study of the complete European industrial heat market in order to prepare for the deployment of HTRs.

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The French president, François Hollande, said that the current mission — named Serval, after an African wildcat — would last "as long as necessary," but stressed that it was limited to "preparing for the deployment of an African intervention force".

The United States has spent billions of dollars funding the deployment of units such as the 3rd Armored BCT to Europe, and preparing for the deployment of even more force.

The official said the initial contracts were given out late last month and that the two contractors have 60 days to identify and prepare for the overseas deployment of about 60 civilians each, for a total of 120 people.

He also confirmed that an advance United Nations team had arrived in Damascus, the capital, to prepare for the possible deployment of observers who would monitor a cease-fire after the pullback.

Throughout the Spring of 2008, the unit prepared for the deployment by conducting training exercises in Germany.

Marine officials began preparing for the deployment last fall, with Turner and others visiting Afghanistan in October.

The first two years after return from deployment is a time of significant change for military personnel and their families, as service members adapt to the home environment, re-establish relationships, recover (if needed) from deployment related psychological disorders, and prepare for the next deployment [ 55].

The students will assemble the required components, train to be kytoon pilots, run test flights in Berkeley, and prepare for a deployment of the kytoon (along with student pilots) to a Department of Energy weather station in Oklahoma for some weeks in the summer of 2019.

Most of the initial Itanium buyers are likely to be software developers and corporate technology managers using the equipment to prepare for widespread deployment of Itanium systems in years to come.

The aim is to identify to which extent such heterogeneous information contributes and combines towards the prediction of a specific clinical presentation - comparing linear and non-linear machine learning models fitted with different feature combinations - and eventually prepare the grounds for the deployment of a personalized diagnostic tool.

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