, to be escalated to the Practice Group Leader or Director, where it is otherwise appropriate to do so.
The CDPP’s National Legal Direction: Right of Review - Prosecutions involving child and certain other complainants sets out guidelines regarding our obligations to inform and consult with certain complainants regarding decisions to commence or discontinue prosecutions.
The CDPP’s Victims of Crime Policy and Prosecution Policy also identifies the other types of information that victims of crime are entitled to receive upon request.
Underpinning the narrative is a fascinating and dimensional lens on the constant interplay of reason and emotion, intuition and rationality.
At its heart, Quiet is not only about how and why we internalize society’s extroversion bias very early on, but also about how to reconnect with the valuable qualities implicit to introversion and rethink our hard-wired strengths in a culture that categorizes them as weaknesses.
Since time immemorial, mankind has grappled with the question of what it means to be human. Different cultures have given different answers throughout history and across geography — answers composed of each culture’s myth and folklore, intellectual and spiritual tradition, artistic lens, and social context. In The Wayfinders: Why Ancient Wisdom Matters in the Modern World, anthropologist and National Geographic Explorer-in-Residence Wade Davis sets out to answer this grandest of questions through the wisdom of the world’s indigenous cultures. From the descendants of a true Lost Civilization in the Amazon to a	Nepalese Buddhist who spent 45 years in solitude to the last nomads of Borneo’s rainforest, Davis weaves a rich tapestry of human knowledge and imagination, a kind of Noah’s Ark of cultural diversity to preserve as we frame the future of the human legacy.
Over and Under the Snow by Kate Messer takes you on a journey into the white wilderness, where foxes and owls and bullfrogs play amidst the winter wonderland.
With wonderfully textured artwork by graphic artist Christopher Silas Neal, known for his album covers, posters, and spot illustrations, the book is an absolute treat and a fine belated addition to the best children’s books of 2011.
Messer and Neal have a fascinating image-annotated chat about the creative process behind the art.
 Using the only clue in common — a postage stamp from Gothenburg, Sweden — journalist and documentary filmmakerJon Ronson resolved to find the enigmatic sender, who turned out to be a bona fide psychopath. But what, exactly, is a psychopath? That’s what Ronson set out to investigate. The Psychopath Test: A Journey Through the Madness Industry, a potent blend of investigative journalism and captivating storytelling with a point of view, traces his quest to understand the fabric of psychopathy, from becoming a kind of qualified psychopath-spotter by learning the 20-point “psychopath checklist” to examining why psychopaths make excellent leaders in business and politics to brushing up against society’s worrisome propensity for pathologizing behavior.
In this teaser, Ronson offers a handful of behavioral cues to look for in a psychopath, while admonishing against the slippery slope of seeing “symptoms” in nearly everyone — a reminder that sanity is a continuum, not a binary divide.
For the past seven years, John Hodgman — actor, humorist, McSweeney’s contributor, “PC Guy” — has been showering the world with his singular brand of keen social observation disguised as offbeat satire in a series title Complete World Knowledge. In 2005, he released The Areas of My Expertise, a collection of absurdist historical anecdotes best described as nonfactual rather than fictional, followed by More Information Than You Require in 2008. That Is All is the third and final part of the series, humorously exploring the impending end of the world.
Bonus points: All three book covers were designed by the wonderful Sam Potts, a longtime favorite.
The reason pessimism is easily escapable, as Martin Seligman posits, might just be that its opposite is our natural pre-wired inclination. At least that’s the argument British neuroscientist Tali Sharot makes in The Optimism Bias: A Tour of the Irrationally Positive Brain — a fascinating yet accessible exploration of how and why our brains construct a positive outlook on life even in the direst of circumstances, and one of 7 essential books on optimism.
Sharot has been studying “flashbulb memories” — recollections with sharp-edged, picture-like qualities, usually about unexpected arousing or traumatic events — since the 9/11 attacks, investigating why the brain tends to “Photoshop” these images, adding contrast, enhancing resolution, inserting and deleting details. This phenomenon led her to probe deeper into the neural system responsible for recollecting these episodes from our past — a system that, contrary to previous belief, hadn’t evolved just for memory but to also imagine the future. These shared neural networks gleaned insight into how the brain generates hope, why we’re able to move forward after trauma, and what makes the brains of optimists different from those of pessimists.
When out with friends recently, one of them mentioned how awesome Julia is. I was surprised to hear someone talk about it, even from another person in science. She turned and gushed about how awesome it was, how supportive the community was, even though she was "not really someone who likes programming." And she liked it so much she was telling her friends about it at a bar!
If you make a programming language that people who don't like programming love enough to spread by word of mouth when not near a computer, which technically-oriented people also love, that's a lot like the OSX terminal + nice GUI blend.
That's a pretty rare thing. And for collaborative science it's pretty important. Often, you'll have people in a bio lab who are very proficient in their area of biological expertise, but who would be solving the wrong problem by spending 2 years trying to become C++ hackers. On the other hand, there are a lot of people who write computational libraries, but know they have to translate them to matlab, or write a matlab wrapper and pray that their users can get it to compile which might sound simple to folks here, but is really frustrating for less computationally oriented people when something goes wrong.
To be fair, there's also Python+NumPy and R in that space, not just Matlab. Besides the "tinker with LLVM" thing, what does Julia offer that Python (or Cython for speed)+NumPy does not?
Writing fast code in Julia requires less effort than it does in Python or R. You don't have to drop down to Cython or Rcpp to get good performance. If you write an algorithm in Julia the same way you'd write it in C, it will achieve equal performance. If you write it the same way you'd write it in Python or R, it may not be optimal due to the cost of memory allocation, but it's still faster than Python or R.
Julia is more concise than Python. The language was designed to work with multidimensional arrays; it wasn't bolted on afterwards. There is no difference between a 2D array and a matrix; * always does matrix multiplication and.* always does element-wise multiplication. There is no awkwardness involving differences between NumPy arrays and Python lists. Everything has a type, and you can make a multidimensional array that efficiently stores values of any type. You can define your own types and define how arithmetic operators act on them with a minimal amount of code.
Julia's type system makes writing efficient algorithms easy without sacrificing any performance. If you define your own immutable type and define your own operators on it, Julia can make those operators run as fast as they would on ordinary values. In addition to general matrices, we have diagonal, symmetric, and tridiagonal matrices. The same routines that work on general matrices work on these as well with the same syntax, just more efficiently.
Julia uses multiple dispatch instead of traditional class-based OO. Methods are not a part of the object; instead, they operate on the object. Different methods with the same name can be defined to work on different types, or a single method can operate on a set of types, but the functions it calls may be implemented differently for each of these types. This is a better fit for technical applications, where the data doesn't change much but the methods do.
Julia is homoiconic, which is more useful than this article makes it seem :). It's easy to write code that writes code. If built-in language features aren't enough to get good performance with concise syntax, you can write a hygenic macro that does this for you.
I love the multiple dispatch part about julia though.
My fear however is, that unlike Python, Julia will lack enough libraries, especially on the unscientific part (GUI, databases, network, all the other stuff you need).
The thing is that the multiplication operation for matrices is matrix multiplication, not elementwise multiplication. When you apply a polynomial like x^2 + y to matrices, you do not want to apply the polynomial elementwise – you want to square the x matrix and add the y matrix to it.
I cheered out loud when I first started tinkering with Julia, tested whether multiplication did the right thing with matrices and vectors, and saw that they did. Multiplying two row vectors should give an error! Element-by-element operations should get their own operator, not the other way around.
But as a long-time R user, I'm hesitant to bet the farm on Julia for a project at work where it