https://news.ycombinator.com/item?id=5572765
and yesterday too:
450 karma · joined July 30, 2009
Background: Physics, Informatics, Medicine, Biology
https://news.ycombinator.com/item?id=5572765
and yesterday too:
2574 New Zealand companies with 1-10 employees are listed in Linkedin: http://www.linkedin.com/csearch/results?type=companies&k...
Largest discussion group: http://www.linkedin.com/groups/Kiwi-Scrum-51900?gid=51900
10 hn accounts: http://hackernewsers.com/users.html?User%5Bcity%5D=Auckland&...
Abstract of the original article: http://www.sciencemag.org/content/332/6037/1524.abstract
I like this visualization of America's richest people that shows some patterns:
http://www.forbes.com/2007/09/18/billionaire-social-mapping-...
It shows that all those with a net worth over 5.5 bln got graduate degrees or went to prestigious schools, or both
Peers influence is strongest in adolescence
see http://home.comcast.net/~aurametrix/site/?/page/Health_2.0/ for more gadgets
Mathematical approaches differ greatly depending on the area of biology. I could recommend a good review if I knew your favorite area.
or, if you do not want to mention retired or former, nor start your own company, just provide your home address and indicate your preferred/non-preferred reviewers
A new authentication device will be available later this year - based on Hitachi's Finger Vein imaging (VeinID) and fingerprint identification technology.
http://founderdating.com/ http://startupsquare.com/
Why don't you start a meetup group like this one? http://www.meetup.com/Co-Founders-Wanted-Meetup/ Briefings from the meetings: http://aurametrix.blogspot.com/2010/03/bay-area-startups-loo... http://aurametrix.blogspot.com/2009/11/bay-area-startups-loo...
If you want to build something similar to what already exists, you will be able to do it by yourself. If you want to create something like e-Harmony - matching people based on demographic, educational, job history, psychological and behavioral characteristics and their encounters, feeding gigabytes of data into sophisticated models on a daily basis, think about measurable expectations before proceeding.