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The series is based on Hasbro's My Little Pony line of toys and animated works and is often referred by collectors to be the fourth generation, or "G4", of the My Little Pony franchise. Season 5 of the series premiered on April 4, 2015 on Discovery Family, an American pay television channel partly owned by Hasbro, and concluded on November 28.
My Little Pony: Friendship Is Magic is an animated television series based on Hasbro's My Little Pony franchise. The series follows a studious pony named Twilight Sparkle (Tara Strong), her dragon assistant Spike (Cathy Weseluck) and her friends, Applejack (Ashleigh Ball), Rarity (Tabitha St. Germain), Fluttershy (Andrea Libman), Rainbow Dash (Ball) and Pinkie Pie (Libman).
Here’s how a master limited partnership works, examples of MLPs and their pros and cons.
Last year was a huge year for initial public offerings as 222 companies went public. Master limited partnerships proved to be no exception, and the 20 MLP IPOs of 2013 was good for an all-time record.
MLPs are bought to provide income. While partnerships that ooze lots of cash are tempting, be careful that your distribution is safe. Poor coverage and tiny distribution raises that keep the ...
The series is based on Hasbro's My Little Pony line of toys and animated works and is often referred by collectors to be the fourth generation, or "G4", of the My Little Pony franchise. Season 8 of the series premiered on March 24, 2018, on Discovery Family, an American pay television channel partly owned by Hasbro, and concluded on October 13.
Even if you've already completed all shopping and are ready to embrace the holiday season, these MLPs are worth a second glance. Simply consider them an early gift for 2014. High demand First ...
These potentials are referred to as MLIPs or MLPs. Such machine learning potentials promised to fill the gap between density functional theory , a highly accurate but computationally intensive modelling method, and empirically derived or intuitively-approximated potentials, which were far lighter computationally but substantially less accurate.