Landis is being punished for daring to defy the anti-doping authorities, insist on his rights to a public hearing (no longer allowed), and embarrassing the hell out of the USADA and WADA by absolutely demolishing their scientific credibility with regard to the testosterone case (after they had to dig in their heels because they had already illegally released the preliminary reports, pre-B sample test to the media). I would note that in the original (and appealed) decisions, the panels through out the initial T-E ratio test as being hopelessly compromised. The mass spectrometry tests were allowed to stand, despite being the quality of lab work that would get laughed out of a college chemistry class, because both panels chose to totally disregard the testimony of John Amory. (see: http://rant-your-head-off.com/WordPress/?p=383 or http://trustbut.blogspot.com/2008/12/winnowing-john-amory.html)

Now, as it turned out, Landis later admitted to doping with HGH that season, and testosterone in previous seasons. But I really think that's incidental to this case. He's being punished because he showed the WADA and UCI are just as corrupt as the cyclists, and the Chatenay-Malabry lab technicians are too incompetent to run a mass spectrometer that undergraduates successfully use thousands of times a day in research labs.

So at the moment I'm playing through a Japan campaign in Victoria 2, which is Paradox's pseudo-realtime complex conquest and development game simulating from 1836-1936. The Brits obviously start the game with a huge advantage (as do the other European powers) and indeed, Japan starts as an uncivilized nation, with major penalties to research and the inability to industrialize among other things. There is however, a path to becoming civilized (which Japan can do through the Meiji restoration decision) and indeed by 1878, I'm in a war with my allies France and (uncivilized) China against Great Britain and the North German federation in an attempt to take Northern India. In this war, about 2.5 million men are fighting on either side, and there will be about 3 million dead (mostly through the British and Chinese armies marching over the Himalayas) by the time the war is over.

In Victoria 2, each soldier is a member of an individual 'pop' living in a certain province, and having its own needs, incomes and political positions. In this war, there are many conscripted regiments who belong to specific 'poor strata' pops of jobs such as farmers, laborers and craftsmen (which I will note, separate men of working/fighting age from women and other parts of the population). Each death on the battle field decreases the size of the 'pop' by the same number of men. Also, I've enacted policies of minority building restrictions, and a discriminatory schooling system to speed assimilation.

By this rationale, aren't I doing worse (in both war and peace) in a single playing session than all the Call of Duty players can do in a similar session combined?

Looking at the following source: http://www.sturmvogel.orbat.com/SovLendLease.html which may or may not be accurate, but does jive with my memory (the most recent essay I've written about a related topic was about 12 years ago and I no longer have the library books), about 75% of the (total) rail stock was delivered pre-December 1941, as well as with a big chunk, 60% or so of the (available) aviation fuel.. which would have been vital to sustaining defensive supply lines. The best thing I found on trucks is http://www.armchairgeneral.com/forums/showthread.php?t=74473 which, if true, would indicate that lend-lease trucks were vital to sustaining the Soviet advances in 1943 and 1944.

In both WWI and WWII the German army managed to critically damage Russia's railstock at the outset of the conflict (albeit, for different reasons), to say that several hundred locomotives weren't vital to sustaining the Soviet defensive positions in late 1941 requires affirming evidence.

And how did the Soviet weapons get deployed to the front? Using 2000 Lend-Lease locomotives, 11,000 Lend-Lease rail cars, and 70%+ Lend-Lease truck strength, and about 18,700 aircraft, about 80% of which were transport aircraft. It may not be glamorous, but that's what allowed the USSR to counter-attack.

http://en.wikipedia.org/wiki/Lend-Lease

S&P had such a major effect when they downgraded Japan's debt in 2002!!!!!! I'm sure S&P etc are still hoping for another 4 or 5 disasters to make that come true. Let's of course, not forget that S&P rated the rags that we previously knew as collective mortgage assets AAA up unto the last day... and I'm supposed to invest? Heh.

In the last month or so, I haven't printed out a single research paper. I've found that using an iPad2 with iAnnotate, a stylus, and Papers (syncing with a Mac laptop, and using dropbox to transfer any pdfs I actually need to open on my workstation) has adequately replaced having a printed copy. You can hand the iPad across the table (and even better, download referenced paper pdfs onto it in a matter of seconds if that comes up), iAnnotate allows you to write freehand notes, markup figures etc, and Papers allows you to sync in all into one convenient database. I've also found that Penultimate (again with a stylus) is a perfectly adequate replacement for a paper notebook in most circumstances... particularly for taking notes during talks, since you have multiple colors available, which makes replicating graphs/figures a lot easier.

I don't know of any similar non-Apple based workflow, but would be interested to hear any suggestions.

.. who works with primates... I do so because I'm convinced there is no other way of collecting data that is important to our health and understanding about how our minds work. Food.. there are other sources.. but neuronal data, we're limited. I'm a big fan of the Reduce, Refine, and Replace idea, and if this is confirmed it's a big step, for 2 R's, and that's exciting.

There were also times in our country's history when such grand investments were politically out of reach. The Land Grant College Act and the Transcontinental railroad were only passed after the departure of the southern states during the Civil War. Rural electrification, despite being shown feasible in 1923, was part of the New Deal.

But even knowing that, it really does annoy me is that we currently have a lot of unemployed from the construction sector. Our infrastructure, according to the American Assc of Civil Engineers is a D. We can borrow money long term (30 year bonds) at about 4.7%, which is about where it was when we decided to build the Interstate system (debt/GDP is also similar). This is the most fiscally favorable time to get our infrastructure back into shape in the last 50 years.

And instead of taking the opportunity to catch up on the repair bill, we have a Republican congress screaming bloody murder about rounding errors in 12% of the budget weeks after blessing a tax cut of similar size, while Obama proposes cutting Pell grants and loans to students pursuing graduate degrees weeks after declaring we're in an education race.

Think about this from a Hollywood perspective for a moment (and I don't mean the snorting middle-manager suits). Hollywood wields the modern day pen with considerable acumen, and they understand the making of a political 'plot' and what's required to be plausible all too well. And they already make their money at the high end of the risk spectrum (I don't know of any studio bailouts).

Shutting down Google is not an objective, it's the denouement of the first act. The misinformed people, the 'other' and even the gods are against them, but down on their luck they still are fighting, and you, the intrepid state senator who would really like a movie-middleman job can help!

The first part of Act 2 will be when they lobby most of the state legislatures into passing draconian infringement or usage laws, while we're busy chortling over how Google stomped on them.

I don't even know how we get through Act 2, much less Act 26.

To put it another way: Would you rather have $100m and the ability to invest it with 2% better return than the S&P, or the ability to talk anybody you meet into giving you 1% of their wealth?

If writing isn't emphasized as the major professional skill learned in college, it still speaks badly of the engineering program. While it's obviously inappropriate to force large written assignments into pure math or core engineering classes, in a good technical curriculum, writing should be emphasized in corollary discipline and core distribution classes. I'd say the 'average' experience for my college friends in engineering is they spend the majority of their time writing technical reports, white papers or memos. Luckily for them, Michigan has strong distribution requirements which emphasize writing, even in the engineering school. An even better example of a purpose built technical school that emphasizes the necessity of communicating clearly in professional settings is WPI with their projects and global perspectives program (which, among other things, makes students propose a project, plan it, go off and spend a semester trying to execute their plan, and then evaluate the entire process with strong faculty support).

Having about 2/3rds of engineering/technical students admitting to cheating is a horrific indictment of our K-12 system.. but I guess class categories would be important to understand to help remedy it. If it's technical classes that they cheat in, then the Race to the Top, etc, trying to force more math and science into high school makes some sense (although with only 30% of biology teachers willing to teach evolution, one wonders..), but if they're plagiarizing instead of writing, Race to the Top is barking up the wrong tree, and we should probably at the least create a college-prep track that focuses on a single goal: graduate high-school knowing how to write a coherent position paper.

Unfortunately mere distribution doesn't take something out of copyright, only explicit assignment to the public domain can do that.. and even there are ways to claw it back into copyright, if any piece of the final product is a collaboration.

With regard to the brain, I agree that Bayesian inference can be a good phenomenological tool to model many complex behaviors, but it does not produce useful mechanistic predictions as to how real neural networks actually compute information. Also, Bayesian models have a very difficult time matching the single-event learning capability of the brain. See here (page 31;PDF) for a brief review in the context of motion processing or here (large pdf) for a more rigorous discussion.

I also give three cheers for Jaynes... I have the habit of giving books to my friends if I think they'd be interesting or useful, and I've dropped a several hundred dollars on re-buying Jaynes. There used to be a 'pre-print' version of the book available, but that source now seems to be down to a few chapters due to copyright issues, although his papers are still there.

With regard to the human brain however, it is (very) unlikely that Bayes' rule is actually computed in any sense of the word. Bayes requires at least one neuron with a global scope (ie. a grandmother cell) to compute the posterior, which is biologically implausible.

What I'm more curious about, is what is the statute of limitations, so to speak, of the police having consent. I was the victim of an (attempted) armed robbery a few years ago in the apartment I currently live in (he didn't think anybody was around, and ran out after threatening me.. it sucks waking up from a nap to an intruder with a gun standing over you), and I sure as hell didn't mind the police searching my apartment then.. but when is that consent removed? All they found was the guy's jacket, the case is still open.. could they still come back and search without a warrant, even if they were interested in a different case? Or do they have to re-establish consent after the first search?

Given that I mentioned (and linked) the Hawthorne effect in my original post, I'm well aware of it (I also discussed some of the statistical issues in response to martin-boundary's comment above).

The Hawthorne experiment was not a shockingly bad mistake, they went in looking for something and found an effect they hadn't been thinking about, then they did a pretty decent job investigating several possible manipulations and published it so other's could have a look. It has since been refined considerably, and plays a major role in how we design experiments. Welcome to wet science. The 'mistakes' you mention are only experienced in hindsight.

The fact remains: wet science and 'hard' science aren't really in the same ballpark in terms of difficulty and complexity, which I also discussed above. Robert Hooke discovered the cell in 1655, 30 years before Newton published his theory of gravity. Newton, and many physicists who came later (Maxwell, Mach, Hemholtz to name a few) understood quite a bit about biology and psychology. They chose physics because it was the accessible problem for them.

Life has been forced by natural selection to come up with incredibly dense, optimized hardware. DNA is on the scale of nanometers, and we literally could not see its structure until the 50s. Which is to say, it took about 300 years of "proper, rigorous" science to produce the tools required to probe the cell and its various amalgamations.. and that's what's being done, and it's going to be just as messy figuring out if there's aether out there.

I wrote a similar post below, but make a slightly different criticism. The difference between wet science and "hard" science boils down to one issue: non-linear recurrence (here is a nice history of the split between physics and psychology [big pdf]).

The theory of experimental errors (and all the derived statistics we use) separates errors into two components: systemic, and random error. The random error is by definition assumed to be uncorrelated between observations (sampling errors).

Random error actually contains another component: non-sampling errors, which are systemic errors that have not been identified. The "hard" sciences, since the Renaissance, has been a mostly successful project of identifying non-sampling errors and improving measurements. This was possible because the experimental mediums didn't change very much (the boiling temperature of water was the same for Galileo).

Doing the same thing in wet science is orders of magnitude more difficult, because biological organisms have memory, adapt and change the environment around them. So it's extremely difficult (likely impossible) to maintain a consistent experimental mediums for long periods of time. This in turn, means two very important things: 1) That the systemic errors change between replications of an experiment (asking Galileo "what is a planet?" and the current chair of the physics department at Padua will yield different answers) and 2) Early differences in random error can propagate through the system and become systemic error in later trials in the same setup (eg. Shaking hands causing slight differences in cellular distribution in the petri dish at the beginning of a growth cycle).

I'm not aware of any statistical methods that can be used to better classify the error in this type of environment. So you're left with changing the underlying distribution.. but to what (and for which protocols.. etc etc)?

While there are wet scientists who use statistics poorly, I think the bigger problem is that the statistical tools currently available are pretty wimpy. Econometrics is likely the most developed mathematical formulation for statistical analysis of non-linear recurrent systems. That's not a good thing.