kevgnulldev
1) some introductory material on receptor theory:
http://en.wikipedia.org/wiki/Receptor_theory
Yes, I know Wikipedia, a more comprehensive intro to basic neuro is "Principles of Neural Science, 5th Ed" (http://www.mhprofessional.com/product.php?isbn=0071390111)... It's large book but the de facto standard.
2) a reference to some basic pharmacology with respect to opioid receptors that includes a summary discussion on receptor interactions (i.e. full agonists/antagonists/partial agonists):
http://www.ncbi.nlm.nih.gov/books/NBK64236/
3) some explanation per the specifics of the mu receptor (click on this only if you are truly thirsting for knowledge on the mu receptor):
http://www.iuphar-db.org/DATABASE/ObjectDisplayForward?objec...
Have a nice night!
http://en.m.wikipedia.org/wiki/Buprenorphine
In short, users can get "strung out" on suboxone but if used in certain ways (I.e not for the long term "maintenance" that the pharma companies make their money on, but as a short therapy to quiet some of the discomfort experienced during opiate withdrawal, it can be effective and safe and not lead to long term use.
http://learning.media.mit.edu/content/publications/EA.Piaget...
A move that I'd like to see but that this particular project only tips its hat to.
http://download.springer.com/static/pdf/967/bfm%253A978-3-64...
http://books.google.com/books/about/The_elements_of_typograp...
for a discussion of LOD in typography from a master designer)
To properly design his multi-volume set of CS/mathematics books:
http://www-cs-faculty.stanford.edu/~uno/taocp.html
Knuth developed an entire software toolchain that spans type face creation (metafont) to the document layout programming language TeX (yup, it's an actual Turing complete language!):
http://en.m.wikipedia.org/wiki/TeX http://dl.acm.org/citation.cfm?id=67555
He is also responsible for the creation of "literate programming"... All this in his spare time, of course, while he wasn't occupied with his responsibilities as a CS professor at Stanford, teaching, doing research (on things other than digital typography, e.g. the content of his books, combinatorics, etc. (...). Truly an inspiration!
http://www.mitpressjournals.org/doi/abs/10.1162/neco.1992.4....
Abstract: We show that a recurrent, second-order neural network using a real-time, forward training algorithm readily learns to infer small regular grammars from positive and negative string training samples. We present simulations that show the effect of initial conditions, training set size and order, and neural network architecture...