For all of the other languages, the researchers discovered, the more data-dense the average syllable is, the fewer of those syllables had to be spoken per second — and the slower the speech thus was. English, with a high information density of .91, is spoken at an average rate of 6.19 syllables per second. Mandarin, which topped the density list at .94, was the spoken slowpoke at 5.18 syllables per second. Spanish, with a low-density .63, rips along at a syllable-per-second velocity of 7.82. The true speed demon of the group, however, was Japanese, which edges past Spanish at 7.84, thanks to its low density of .49. Despite those differences, at the end of, say, a minute of speech, all of the languages would have conveyed more or less identical amounts of information.

Wind power proponent and author Paul Gipe estimated in Wind Energy Comes of Age that the mortality rate for wind power from 1980–1994 was 0.4 deaths per terawatt-hour. Paul Gipe's estimate as of end 2000 was 0.15 deaths per TWh, a decline attributed to greater total cumulative generation.

Hydroelectric power was found to to have a fatality rate of 0.10 per TWh (883 fatalities for every TW·yr) in the period 1969–1996

Nuclear power is about 0.04 deaths/TWh.

Given our development processes we found the average productivity of a single Django developer to be equivalent to the output generated by two C# ASP.NET developers. Given equal-sized teams, Django allowed our developers to be twice as productive as our ASP.NET team.

I suspect these results may actually reflect a lower bound of the productivity differences. It should be noted that about half of the Team Python developers, while fluent in Python, had not used Django before. They quickly learned Django, but it is possible this fluency disparity may have caused an unintended bias in results–handicapping overall Django velocity.

sux0r 2.1.0 is a blogging package, an RSS aggregator, a bookmark repository, and a photo publishing platform with a focus on Naive Bayesian categorization and probabilistic content.

OpenID enabled (version 1.1); as both a consumer and a provider.

Srivastava realized that the same logic could be applied to the lottery. The apparent randomness of the scratch ticket was just a facade, a mathematical lie. And this meant that the lottery system might actually be solvable, just like those mining samples. “At the time, I had no intention of cracking the tickets,” he says. He was just curious about the algorithm that produced the numbers. Walking back from the gas station with the chips and coffee he’d bought with his winnings, he turned the problem over in his mind. By the time he reached the office, he was confident that he knew how the software might work, how it could precisely control the number of winners while still appearing random. “It wasn’t that hard,” Srivastava says. “I do the same kind of math all day long.”

Oxford mathematician Peter Donnelly reveals the common mistakes humans make in interpreting statistics -- and the devastating impact these errors can have on the outcome of criminal trials.

"We can't send mail farther than 500 miles from here," he repeated.

"A little bit more, actually.

Call it 520 miles.

But no farther."

Munin is a networked resource monitoring tool that can help analyze resource trends and "what just happened to kill our performance?" problems. It is designed to be very plug and play. A default installation provides a lot of graphs with almost no work.

Almost everyone knows the power of twitter now but very few know how to get more out of it. To use Twitter fully and become successful, you must check statistics of your account and analyze it. But, the basic Twitter service does not provide full and advanced stats, you can get those only by using tools developed by others.

Here is the list of 8 useful twitter statistics and analytics tools.

Since September 27, 2007, I have been documenting the graffiti left in public study areas in the Joseph Regenstein Library ("the Reg"): the study nooks tucked into the stacks, the whiteboards in the all-night study space, and the study carrels in the reading rooms. I have transcribed over 620 “pieces” of graffiti—many of which contain more than one single contribution—and over 410 of them are datable to within a week of their creation. The following is an analysis of the data to date; you can access the entire data set at my website, Crescat Graffiti, Vita Excolatur.