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Losing the Center
Many Americans consider John F. Kennedy's presidency to represent the apex of American liberalism. Kennedy's "Vital Center" blueprint united middle-class and working-class Democrats and promoted freedom abroad while recognizing the limits of American power. Liberalism thrived in the early 1960s, but its heyday was short-lived. In Losing the Center, Jeffrey Bloodworth demonstrates how and why the once-dominant ideology began its steep decline, exploring its failures through the biographies of some of the Democratic Party's most important leaders, including Daniel Patrick Moynihan, Henry "Scoop" Jackson, Bella Abzug, Harold Ford Sr., and Jimmy Carter. By illuminating historical events through ...
Donald Thomson In Arnhem Land
'I had lived and hunted with these people, accompanied them on their nomadic wanderings and learned their customs and their languages with the result that I understood and believed in them and resented the injustices under which they had suffered for so long at the hands of the white man and other invaders of their territory.' In 1932-33, Yolngu people living in the Caledon Bay area of north-east Arnhem Land were involved in the killing of five Japanese fishermen and three Europeans. A punitive expedition was proposed to 'teach the Aborigines a lesson'. In response, Donald Thomson, a Melbourne-born anthropologist, offered to investigate the causes of the conflict. After seven months of inves...
Vegetarian Times
To do what no other magazine does: Deliver simple, delicious food, plus expert health and lifestyle information, that's exclusively vegetarian but wrapped in a fresh, stylish mainstream package that's inviting to all. Because while vegetarians are a great, vital, passionate niche, their healthy way of eating and the earth-friendly values it inspires appeals to an increasingly large group of Americans. VT's goal: To embrace both.
Air Force Register
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Changes of Problem Representation
The purpose of our research is to enhance the efficiency of AI problem solvers by automating representation changes. We have developed a system that improves the description of input problems and selects an appropriate search algorithm for each given problem. Motivation. Researchers have accumulated much evidence on the impor tance of appropriate representations for the efficiency of AI systems. The same problem may be easy or difficult, depending on the way we describe it and on the search algorithm we use. Previous work on the automatic im provement of problem descriptions has mostly been limited to the design of individual learning algorithms. The user has traditionally been responsible f...
