Velocity Over Time

Date	Event	Magnitude	Damage	Deaths
1 Oct 1987	Whittier Narrows	5.9	$380 million	8	My first major earthquake; 5.6 magnitude aftershock on 4 Oct 1987
29 Jun 1991	Sierra Madre	5.6	$40 million	2	epicenter 12 miles from my parents' house. I almost forgot about this one because it didn't cause a lot of damage and didn't have a lot of aftershocks.
17 Jan 1994	Northridge	6.7	$20 billion	60	7,000 injuries, destroyed Golden State Fwy/Antelope Valley Fwy interchange (I-5/CA-14) and a large segment of the Santa Monica Fwy (I-10)

Now don't get me wrong. I'm a big fan of social networks and microblogging/nanoblogging, but I'm not really ready to buy into the hype about the obliteration of traditional media.

The Chengdu/Sichuan quake

in May was ballyhooed as a triumph of Twitter over traditional media, and in fact there was a significant time delay before stories from traditional channels finally hit. But this is more a commentary on the limitations of the press in a repressive Communist regime that has a stranglehold on information, not to mention a fact that the epicenter was in a relatively remote rural region almost 100 miles away from Chengdu.

The case is significantly different when you're dealing with a major metropolitan area in an industrialized country under a regime that allows relative freedom of the press. The local news happened to be on-the-air when the Chino Hills quake hit. They got in touch with Cal Tech seismologists relatively rapidly. In contrast, the first reports on Twitter localized it wrong (San Diego is over 100 miles away from the epicenter) and most of the chatter was simply reiterating what the local news was reporting.

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Not to say that Twitter didn't have any value. Certainly, since the cel phone network got overwhelmed by panicked callers and since land line service was disrupted by the quake, the only avenues of communication remaining were SMS and the Internet (thank you, ARPAnet!) But it's really more of an adjunct than a replacement to traditional media, and there's a lot of noise and misinformation.

I find it slightly weird that “Batman Begins” and “The Dark Knight” use Chicago to represent Gotham (while “Superman Returns” uses NYC to represent Metropolis!) I've always associated Chicago with Metropolis, and New York City has been Gotham City long before the Batman was around.

Apparently Gotham was first employed as a reference to NYC by Washington Irving (author of such American classics as “The Legend of Sleepy Hollow” and “Rip van Winkle”.)

The reason why I think of Metropolis as Chicago is because Clark Kent grew up in Kansas, making Chicago the closest major city with a waterfront. In fact, Metropolis was most heavily influenced by Toronto. But in DC canon, Metropolis, Gotham City, and NYC are all separate places which are all geographically close.

Another popular interpretation is that "Metropolis is NYC by day; Gotham City is NYC by night".

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Nevertheless, Superman seems to fit the Midwest better. The initial story actually had him living in Cleveland, where Joel Siegel and Joe Shuster thought up the entire idea.

So NYC has Batman. Chicago has Superman. Who does L.A. have?

Interestingly enough, L.A. has no superheroes, unless you count Hancock, or the "Adventures of Superman" 1950s-era series. I certainly can't think of any major comic book character who ever walked the streets of the City of Angels. The closest, larger-than-life, science fiction/fantasy cult-classic hero that I can think of is Rick Deckard from Blade Runner, played wonderfully by Harrison Ford.

Undoubtedly because they were created in the early 20th century, both Gotham City and Metropolis have definite retro aesthetics. Gotham City is an archetype of noir. Metropolis has that retro-futuristic 1950s feel to it. In contrast, Phillip K Dick's (and Ridley Scott's) L.A. is unabashed cyberpunk techno-dystopia.

In this regard, I've always thought of the three major cities of the U.S. as snapshots of the U.S.-at-large. NYC is America-in-the-present, the cultural capital of the nation, constantly in motion and flux. Chicago is an America-that-could-have-been, the metropolis in a vacuum, the America that many white, middle-class Americans favor. But L.A. is America-that-will-be. Part of it is because L.A. churns out these fantastic (in the literary sense) works of cinema that end up creating a normative vision of the U.S. But the seat of power always seems to be moving westward, always westward. In Western Civilization, it was Babylon, then Athens, then Rome, then London, and now NYC. Inevitably, it will move again, and L.A.—with its logistical proximity to Asia and South America—is bound to be that center until power is finally wrested from the North American continent.

Today is September 5435, 1993, according to the Eternal September Date Converter. In honor of 15 years of being September 1993, I think we ought to create a few more cryptically insulting acronyms/initialisms to keep up with the times.

In this day and age where most computer users have no idea what a man page is, I propose we retire RTFM and replace it with the following:

FGI

Google it

RTFWA

Read the Wikipedia article

I am more at ease with the direction Hofstadter is taking his argument about how the actual architecture of the brain and the actual molecular arrangements of proteins on neurons do not need to be fully explicated in order to at least think about thought processes. This is the same way how you don't really need to know how a microprocessor actually works in order to program it in assembly.

This is, however, in contrast to the example of the C++ programmer. While it's not necessary to understand what the compiler actually changes your code into, if you ever want to do optimization, it's helpful.

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Consciousness is yet another example of an emergent phenomenon—essentially a process that is not readily predictable from its component parts. In this way, he's right, you can't just look at individual neurons, or even encapsulated subsystems within the brain in order to understand consciousness.

A very common emergent phenomenon that most of us deal with almost daily is traffic. While clearly patterns are caused by socioeconomic trends, the price of real estate, the location of jobs, how well-repaired a particular road is, the particular way a segment of freeway curves, the price of gas, etc., etc., studying any of these things in isolation is not going to do much to inform you about where the slowdowns are going to be today. Even studying individual drivers and their cars will not yield very much.

Another example of emergence is weather: you can't really look at individual molecules of nitrogen, oxygen, water, and carbon dioxide, and decide whether it's going to rain or not.

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My point, though, is that we don't exactly know how many levels above the physical substrate consciousness arises from. While neuroanatomists tend to refer to particular subsystems in the brain as if you could disentangle them and look at them in a vacuum, any neurologist can tell you that there's no way you're going to hit just one subsystem with that blood clot or bleed. So we're stuck with looking alternately between the somewhat abstract idea of cortical subsystems, and with the realization that we're really just dealing with networks of neurons all connected in a particular, and remarkably reproducible way.

Which gets us to another point: how is my consciousness different from your consciousness? Clearly we have different genes. We've experienced different things. And yet, at least on a gross, subsystemic level, my neurons probably aren't hooked up very differently from your neurons. At least, that's what we assume (the thalamus is connected to the amygdala, the amygdala is connected to the hippocampus, the hippocampus is connected to the frontal lobe, etc., etc.) The individual connections probably differ minutely (no more than 1%, I bet), but is it enough to explain why I behave the way I do, and you behave the way you do?

I'm reading I am a Strange Loop by Douglas Hofstadter right now, which is a sequel to his widely popular book Godel, Escher, Bach. Hofstadter concerns himself with, among other things, the software of thought.

In the chapter he's trying to make the distinction between hardware and software when it comes to thinking machines and thought processes.

This is important if you're trying to posit that it should be feasible to implement intelligence on non-organic substrates such as silicon wafers. One can look at the human brain as a hyperconnected, super-complex, megacomputer, just like your Mac, except several orders of magnitude more complicated, with a design that is hundreds of millions of years old. But it is a distinction that has yet to be proven empirically. It may be that thought as we know it is dependent upon the hardware configuration upon which it is implemented, so you can't just ignore the neurobiologists.

The reason why I lean towards the hardware-software interdependence is because hardware-software independence is a recent thing in computer design. I don't think it was until the late '90's-early '00's that we had actual machines that could run multiple OSes with ease, whose parts were readily interchangeable. I still remember the 8-bit days of yore where you had to hand-optimize your code to cram functionality into 38k of RAM, and you had to rely on direct access to the hardware that the designers had hardwired into your machine. There were no abstraction layers. It was just you and the machine, with maybe 4k of convenience routines referred to as a kernel, and if you really wanted, another 4k for a language interpreter. But the higher level language did nothing to insulate you from direct hardware access. You still had to PEEK and POKE to get things done.

Still, you might think that Nature, having had several hundred millions years of a head-start on computer designers, would've figured out the abstraction thing and would've implemented cleaner designs with each iteration. Unfortunately, random chance doesn't really work that way. What you usually end up with is a lowest-common-denominator design that random chance mucks around with every so often, and more often than not, that change will be fatal, but occasionally, it may be an improvement. It's no coincidence that the basic plan of the human brain has been around for literal epochs, implemented in other creatures like dogs, velociraptors, frogs, and lampreys. And while absolute size has little to do with actual intelligence (after all, a baleen whale has a much bigger brain than a human), there are some morphological features that can be predictive of intelligence, like the surface area of the cerebral cortex, for example.

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Hofstadter tries to argue that you don't need to know the low level bits and pieces of the hardware in order to appreciate the software, and to a degree, this is a useful way to think. Unfortunately, his use of the heart as an analogy blows the argument to pieces.

If you ever want to piss-off a cardiologist, insist forcefully that the human heart is nothing but a pump. The pump analogy has indeed been extremely useful to physicians and physiologists alike, but we always have to remember that that's all it is: an analogy. While we may model the pump function of the heart with an extremely simplified form of Poiseuille's law (P=QR, pressure equals flow times resistance), it's obvious that there are no rigid pipes involved, there's a lot of non-laminar flow going on, mostly because the flow is actually pulsatile and not continuous.

The analogy helps physicians describe heart failure and pulmonary edema to their patients in simple terms, and while the extremely simplified form of Poiseuille's law allows us to study human physiology without having to resort to calculus, and to allow ICU physicians to make back-of-the-napkin calculations while they're screwing around with pressors and inotropes in someone who is dying. But the pump analogy eventually fails, though. The most spectacular way I've seen it fail is in the description of heart failure.

The pump description describes systolic dysfunction as simply the heart's inability to squeeze adequately to keep flow going forward. So the preload backs up, causing fluid build-up in the lungs, and in severe cases, the flow can't adequately overcome the afterload either, causing ischemic symptoms like passing out. Given the pump analogy, for decades, physicians treated systolic dysfunction with cardiac glycosides, namely, digitalis. What digitalis does is essentially force the heart to pump harder. Physicians also were taught to avoid medications that would weaken pump function, medications such as beta-blockers.

Well, wouldn't you know it, when they studied this more closely, it turns out that while digitalis can improve symptoms in patients with heart failure, thereby decreasing the number of hospitalizations, it did nothing to change mortality rates. In stark contrast, it was found that the addition of a beta-blocker not only decreased morbidity, it also prolonged survival time. How counter-intuitive is that?

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The reason why this probably works is because of the molecular physiology involved. You cannot avoid having to study signal transduction pathways if you want to understand how to treat heart failure. It has been discovered that the neurohormones epinephrine, norepinephrine, angiotensin, and aldosterone can bind to receptors in the heart and activate the TGF-beta pathway. What has been recently appreciated is that the reason why pump function continues to deteriorate in heart failure is because of remodeling. The heart becomes more fibrous, less muscular and elastic. How is this mediated? By growth factors like TGF-beta.

It is probably not coincidence that we have since discovered that beta-blockers, angiotensin-converting-enzyme inhibitors, angiotensin receptor blockers, and aldosterone antagonists all help with not only improving the quality of life of heart failure patients, but also with increasing their life expectancies. It used to be that a diagnosis of heart failure had a similar prognosis to metastatic cancer, but now people can live for years and decades. And we would never have figured any of this out if we had stuck to the pump analogy of heart function.

I think Kevin Drum almost gets—but ultimately misses—the point in his brief analysis of an article about Stuff White People Like, a blog that collates different cultural characteristics applicable to the young urban professional white person. What is novel about it is not that it targets a particular demographic that has been depicted by Hollywood as Normal™, but that it explicitly associates this culture with race.

This is significant because it at last explains what people-of-color mean when they tell other people-of-color, "You're acting white." This is significant because it makes it explicit that if a person-of-color buys into the American Dream™, they are necessarily buying into a particular subculture that, on one extreme, can totally obliterate one's root culture, and at the very least, must be reconciled with one's root culture.

Less significantly, it also illustrates what Chris Rock might describe as the difference between a "white person" and a "cracker."

People shouldn't be mucking around with software release terminology. I just read Rob Diana's rant about the abuse of the term beta on the Internet on Mashable! and the terms really shouldn't be as fungible as that.

The quick and dirty:

• alpha: Build and runs. Barely. Show-stopper bugs common. Sometimes runnable, but doesn't actually do anything.
• beta: Functional software but buggy.
• gamma: Ready to go gold. Probably still has some insidious bugs that haven't been ferreted out yet. Also commonly referred to as a "release candidate"

Anything beyond that is unnecessary. Delta is more commonly used to refer to quick bug fixes of already released software, sometimes synonymous with the z version in x.y.z terminology, since deltas are commonly associated with patches. Any other use of delta is confusing. Omega is, I suppose, equivalent to final release, but that's also probably unnecessary.

As far as I can tell, just because it's Web 2.0 doesn't mean these definitions don't apply. Releasing real alpha software as an accessible service is really asking for trouble. If there's a showstopper in there that's going to need an architectural change, you're either going to have to jump through hoops to preserve your alpha-testers' data, or you give them the finger and tell them "I told you it was an alpha!" On the other hand, I think it's legitimate for Google to continue calling Gmail beta, because there may very well be some insidious bug lying in their code base just waiting for the critical mass of users and data to nuke everyone's Inbox. That's the problem with networked systems: you can't easily trace all the paths through your code without actually releasing it to the real world. Most of the bugs tend to be related to (1) data volume (2) traffic volume (3) unintended/unforeseen interactions between components.

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Somewhat humorously, medicine has a similar release cycle for pharmaceuticals:

• preclinical:
  • pharmacodynamics: figuring out what the drug does to the body
  • pharmacokinetics: figuring out what the body does to the drug
    • absorption
    • distribution
    • metabolism
    • elimination
  • toxicity
• phase I: small trial on (usually) health subjects; pretty equivalent to alpha release software. You're mostly sure that it won't kill anyone, but you don't know whether it will actually do anything, and you could still do some harm.
• phase II: larger trial that includes target subjects. Beta release. No obvious show-stoppers (i.e., instantaneous death), but lots of insidious side-effects. Actually efficacy is tested. (Is the drug actually functional?)
• phase III: large, ideally, randomized clinical trial designed to test the new drug against the current standard of care. Release candidate: it actually does something, what it does is desirable, and no one has died. Even if the drug isn't better than the current standard of care, if they can at least demonstrate non-inferiority, they can still go gold.

They now have a phase 0 designation, but this is almost like animal testing on humans, really, from what I can tell.

I am still waiting for the veritable hammer to fall. I can only expect that it will happen exactly when I'm least expecting it.

I'm not sure what I'm trying to do any more. Friendship is all well and dandy, but no matter how close you are, it will always be eventually eclipsed by romance.

You'll find that your best friend ain't quite as available. It's bad enough when you're both guys (and both straight.) When there's a gender mismatch and/or the remotest possibility that someone is harboring unrequited tendencies, every complication seems to get magnified.

I kind of wonder just how many times I'll need to go down this road in my lifetime. At the very least, it will be a finite number.

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The other day I found myself asking myself if it would still be worth going on and living if I knew that this was the best it was gonna get, that's all there is, there ain't no mo'. Considering all the sorts of (often self-inflicted) emotional torture I've gone through in the past decade or so, I would think that anything would be bearable at this stage. That which doesn't kill you only delays the inevitable. But the thought of waking up to this loneliness every single day for the rest of my natural life sort of made me hesitate. If I had some sort of time machine and knew that this was going to be my destiny, I think I might be hard-pressed to keep going.