But physical altercation is very different than a verbal one. As I said once you engage in a physical altercation I am of the opinion that you hold more responsibility for what happens to either yourself or the other person. Again I see why people are upset it easy to see the video and say there was 0 reason to pull the trigger, but it was a very stressful situation and I don see enough evidence to decide that this man wanted someone dead..
The symptoms of diabetes, including lethargy, excessive thirst and hunger, and dramatic weight loss are due to the body’s attempt to “flush out” the blood sugar that builds up, and its desire for fuel/energy. Left untreated, it is as if the diabetic patient is not eating. Symptoms eventually progress to include a loss of consciousness, seizures and possibly death..
The gray wolves of Yellowstone are heard more often than seen. Their eerie howls can echo up to fifty miles, summoning the pack before or after a hunt. Yellowstone’s wolves are efficient predators, able to take down animals many times their weight by hunting in packs.
7. Nike, “Hare Jordan.” This feat of animation mixed with live footage from Wieden Kennedy gave us basketball great Michael Jordan teaming with Bugs Bunny to trounce bullies on the court. According to a Los Angeles Times story from 1992, the year the spot ran in the Super Bowl: “The Nike spot cost nearly $1 million to make excluding Jordan’s salary estimated Scott Bedbury, Nike’s director of advertising.
8 points submitted 2 months agoWe took a random sample of 6,231 recent job applications, applicants and outcomes across 681 cities and 116 roles and industries from recent activity on TalentWorks.For each resume, we calculated the maximum a posteriori parse tree using a custom, dynamic vocabulary PCFG (our ResumeParser), extracted the objective subtree if present and estimated the years of experience based on parsed employments. For each job, we classified it into one of 800 job roles. Finally, we independently regressed the interview callback rate for each sub population with a blended Matern kernel using a bagged Gaussian process against years of experience, job role, etc.We did all of the analysis with in house algorithms and sklearn/scipy in python.