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Amazon.com: GU Energy Original Sports Nutrition …
GU Original Sports Nutrition Energy Gel is the energy gel that started it all. In 1993, Dr. Bill Vaughn developed the world's first energy gel to help his daughter perform better during ultra-marathons, and GU has been helping to propel the world's most successful extreme athletes to success ever since.
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GU | definition of GU by Medical dictionary
GU: [ jen´ĭ-to-u´rĭ-ner″e ] pertaining to the urinary system and genitalia; called also urinogenital and urogenital .
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Zhen Gu | UCLA Samueli School Of Engineering
Dr. Zhen Gu is an adjunct professor in the Department of Bioengineering. Dr. Gu received his B.S. degree in Chemistry and M.S. degree in Polymer Chemistry and Physics from Nanjing University. In 2010, he obtained Ph.D. at UCLA, under the guidance of Dr. Yi Tang in the Department of Chemical and Biomolecular Engineering. He was a Postdoctoral Associate working with Dr. Robert Langer at MIT …
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What does Gu stand for in medical dictionary?
Miller-Keane Encyclopedia and Dictionary of Medicine, Nursing, and Allied Health, Seventh Edition. © 2003 by Saunders, an imprint of Elsevier, Inc. All rights reserved. Abbreviation for genitourinary.
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What does GU energy gel do for You?
GU Energy Gel sustains all forms of athletic activity with a highly compact, portable, and calorie-dense packet that is loaded with carbohydrates that can be rapidly absorbed. Branched-chain amino acids limit muscle fiber damage and increase speed of recovery, and extra electrolytes help maintain water balance.
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What kind of research does Zhen gu do?
Dr. Gu’s group studies controlled drug delivery, bio-inspired materials and nanobiotechnology, especially for cancer and diabetes treatment. He has published over 160 research papers and applied over 50 patents.
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What kind of computer science does Quanquan gu do?
I am an Assistant Professor of Computer Science at UCLA. My research is in statistical machine learning, with a focus on developing and analyzing nonconvex optimization algorithms for machine learning to understand large-scale, dynamic, complex and heterogeneous data, and building the theoretical foundations of deep learning.
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