This video, linked by Tyler Cowen, is the best I have seen to simplify the basic theory of public key encryption:
This follow-up video takes this basic understanding and explains RSA encryption
Dispatches from District 48
Archive for the ‘Science’ Category.
This video, linked by Tyler Cowen, is the best I have seen to simplify the basic theory of public key encryption:
This follow-up video takes this basic understanding and explains RSA encryption
“Scientists have solid experimental and theoretical evidence to support…the following predictions: In a decade, urban dwellers will have to wear gas masks to survive air pollution…by 1985 air pollution will have reduced the amount of sunlight reaching earth by one half….”
• Life Magazine, January 1970
Other prediction fails from the first Earth Day here.
Several months ago, a lot of folks where shocked to find that the Clinton Foundation only spent $9 million in direct aid out of a total budget of $150 million, with the rest going to salaries and bonuses and luxury travel for family and friends and other members of the Clinton posse.
None of this surprised me. From my time at Ivy League schools, I know any number of kids from rich families that work for some sort of trust or non-profit that has nominally charitable goals, but most of whose budget seems to go to lavish parties, first-class travel, and sinecures for various wealthy family scions.
But this week comes a story from the climate world that demonstrates that making a fortune from your non-profit is not just for the old money any more -- it appears to be a great way for activists to build new fortunes.
The story starts with the abhorrent letter by 20 university professors urging President Obama to use the RICO statute (usually thought of as a tool to fight organized crime) to jail people who disagree with them in a scientific debate. The letter was authored by Jagadish Shukla of George Mason University, and seems to take the position that all climate skeptics are part of an organized coordinated gang that are actively promoting ideas they know to be wrong solely for financial enrichment. (I will give the near-universal skeptic reply to this: "So where is my Exxon check?!"
Anyway, a couple of folks, including Roger Pielke, Jr. and Steve McIntyre, both folks who get accused of being oil industry funded but who in fact get little or no funding from any such source, wondered where Shukla's funding comes from. Shukla gets what looks like a very generous salary from George Mason University of $314,000 a year. Power to him on that score. However, the more interesting part is where he makes the rest of his money, because it turns out his university salary is well under half his total income. The "non-profits" he controls pays him, his family, and his friends over $800,000 a year in compensation, all paid out of government grants that supposedly are to support science.
A number of years ago Shukla created a couple of non-profits called the Institute for Global Environment and Security (IGES) and the Center for Ocean Land Atmosphere Interactions (COLA). Both were founded by Shukla and are essentially controlled by him, though both now have some sort of institutional relationship with George Mason University as well. Steve McIntyre has the whole story in its various details.
COLA and IGES both seem to have gotten most of their revenues from NSF, NASA, and NOAA grants. Over the years, the IGES appears to have collected over $75 million in grants. As an aside, this single set of grants to one tiny, you-never-even-heard-of-it climate non-profit is very likely way higher than the cumulative sum total of all money ever paid to skeptics. I have always thought that warmists freaking out over the trivial sums of money going to skeptics is a bit like a football coach who is winning 97-0 freaking out in anger over the other team finally picking up a first down.
Apparently a LOT of this non-profit grant money ends up in the Shukla family bank accounts.
In 2001, the earliest year thus far publicly available, in 2001, in addition to his university salary (not yet available, but presumably about $125,000), Shukla and his wife received a further $214,496 in compensation from IGES (Shukla -$128,796; Anne Shukla – $85,700). Their combined compensation from IGES doubled over the next two years to approximately $400,000 (additional to Shukla’s university salary of say $130,000), for combined compensation of about $530,000 by 2004.
Shukla’s university salary increased dramatically over the decade reaching $250,866 by 2013 and $314,000 by 2014. (In this latter year, Shukla was paid much more than Ed Wegman, a George Mason professor of similar seniority). Meanwhile, despite the apparent transition of IGES to George Mason, the income of the Shuklas from IGES continued to increase, reaching $547,000 by 2013.
Grant records are a real mess but it looks like from George Mason University press releases that IGES and its successor recently got a $10 million five-year grant, or $2 million a year from the government. Of that money:
- approximately $550,000 a year goes to Shukla and his wife as salaries
- some amount, perhaps $90,000 a year, goes to Shukla's daughter as salary
- $171,000 a year goes as salary to James Kinter, an associate of Shukla at George Mason
- An unknown amount goes for Shukla's expenses, for example travel. When was the last time you ever heard of a climate conference, or any NGO conference, being held at, say, the Dallas-Ft Worth Airport Marriott? No, because these conferences are really meant as paid vacation opportunities as taxpayer expense for non-profit executives.
I don't think it would be too much of a stretch, if one includes travel and personal expenses paid, that half the government grants to this non-profit are going to support the lifestyle of Shukla and his friends and family. Note this is not money for Shukla's research or lab, this is money paid to him personally.
Progressives always like to point out examples of corruption in for-profit companies, and certainly those exist. But there are numerous market and legal checks that bring accountability for such corruption. But nothing of the sort exists in the non-profit world. Not only are there few accountability mechanisms, but most of these non-profits are very good at using their stated good intentions as a shield from scrutiny -- "How can you accuse us of corruption, we are doing such important work!"
Postscript: Oddly, another form of this non-profit scam exists in my industry. As a reminder, my company privately operates public recreation areas. Several folks have tried to set up what I call for-profit non-profits. An individual will create a non-profit, and then pay themselves some salary that is equal to or even greater than the profits they would get as an owner. They are not avoiding taxes -- they still have to pay taxes on that salary just like I have to pay taxes (at the same individual tax rates) on my pass-through profits.
What they are seeking are two advantages:
The latter can have hilarious results. There is one non-profit I know of that is a total dodge, but the "owner" is really good at piously talking about his organization being "cleaner" because it is a non-profit, while all the while paying himself a salary higher than my last year's profits.
When first presented with the idea of the Hyperloop (a train running in vaccuum in an underground tube), I was extremely skeptical it made any sense. Sure it might work (after all the London tube started out as a pneumatic system much like those that older ones of us remember sending receipts around department stores). But did it make any economic sense. Was it really likely that, if we can't afford rail lines above ground easily, we could afford to build thousands of miles of air-tight large-diameter tubes? Honestly, it looked to me like any other silly idea on the cover of Popular Mechanics, right next to the titanium zeppelin the size of Connecticut that would someday be doing construction work.
So enter Elon Musk, who is very passionate about the idea, claims to be convinced it will work, and appears to be putting some money behind it. With his support, the idea must immediately be treated as more credible, and it does indeed get a lot of press. But here is the problem for me with Musk: With him, the idea must also be treated as very probably another attempt by him to drain money out of the taxpayers' pockets into his. Because that is what he does in so many of his enterprises.
... but the images are pretty awesome. via here. Taken from the DSCOVR satellite orbiting a million miles away from Earth (my guess is that it sits at the Earth-Sun L1 Lagrange point, where the side of Earth it could see would always be in full sun and the back side of the moon would be fully illuminated as it passes Earth)
It is a long article, covering a lot of ground, and is full of links to literature on both sides of the debate. But its conclusions are pretty definite
I’ve spent much of the past year digging into the evidence. Here’s what I’ve learned. First, it’s true that the issue is complicated. But the deeper you dig, the more fraud you find in the case against GMOs. It’s full of errors, fallacies, misconceptions, misrepresentations, and lies. The people who tell you that Monsanto is hiding the truth are themselves hiding evidence that their own allegations about GMOs are false. They’re counting on you to feel overwhelmed by the science and to accept, as a gut presumption, their message of distrust.
Second, the central argument of the anti-GMO movement—that prudence and caution are reasons to avoid genetically engineered, or GE, food—is a sham. Activists who tell you to play it safe around GMOs take no such care in evaluating the alternatives. They denounce proteins in GE crops as toxic, even as they defend drugs, pesticides, and non-GMO crops that are loaded with the same proteins. They portray genetic engineering as chaotic and unpredictable, even when studies indicate that other crop improvement methods, including those favored by the same activists, are more disruptive to plant genomes.
Third, there are valid concerns about some aspects of GE agriculture, such as herbicides, monocultures, and patents. But none of these concerns is fundamentally about genetic engineering. Genetic engineering isn’t a thing. It’s a process that can be used in different ways to create different things. To think clearly about GMOs, you have to distinguish among the applications and focus on the substance of each case. If you’re concerned about pesticides and transparency, you need to know about the toxins to which your food has been exposed. A GMO label won’t tell you that. And it can lull you into buying a non-GMO product even when the GE alternative is safer.
This is just the management summary, the article goes into great depth on all of these.
A while back I wrote a long post on topics like climate change, vaccinations, and GMO foods where I discussed the systematic problems many in the political-media complex have in evaluating risks in a reasoned manner.
I didn't have any idea who the "Food Babe" was but from this article she sure seems to be yet another example. If you want to see an absolute classic of food babe "thinking", check out this article on flying. Seriously, I seldom insist you go read something but it is relatively short and you will find yourself laughing, I guarantee it.
Postscript: I had someone tell me the other day that I was inconsistent. I was on the side of science (being pro-vaccination) but against science (being pro-fossil fuel use). I have heard this or something like it come up in the vaccination debate a number of times, so a few thoughts:
Anyone want to explain this? It was sent in one of those emails that sort of go around.
Water straight from the tap becomes cloudy when frozen.
To make ice cubes crystal clear, allow a kettle of boiled water to cool slightly
and use this to fill your ice cube trays.
I know that crystal growth is path dependent. Is this just the water equivalent of annealing in metal and glass?
Update: Long-time reader Travis says that boiling the water drives all the trapped air out, making the cubes clear. Jeez, I so wanted this to be some wonky crystal formation answer
Post-modernism is many things and its exact meaning is subject to argument, but I think most would agree that it explicitly rejects things like formalism and realism in favor of socially constructed narratives. In that sense, what I mean by "post-modern science" is not necessarily a rejection of scientific evidence, but a prioritization where support for the favored narrative is more important than the details of scientific evidence. We have seen this for quite a while in climate science, where alarmists, when they talk among themselves, discuss how it is more important for them to support the narrative (catastrophic global warming and, tied with this, an increasing strain of anti-capitalism ala Naomi Klein) than to be true to the facts all the time. As a result, many climate scientists would argue (and have) that accurately expressing the uncertainties in their analysis or documenting counter-veiling evidence is wrong, because it dilutes the narrative.
I think this is the context in which Naomi Oreskes' recent NY Times article should be read. It is telling she uses the issue of secondhand tobacco smoke as an example, because that is one of the best examples I can think of when we let the narrative and our preferred social policy (e.g. banning smoking) to trump the actual scientific evidence. The work used to justify second hand smoke bans is some of the worst science I can think of, and this is what she is holding up as the example she wants to emulate in climate. I have had arguments on second hand smoke where I point out the weakness and in some cases the absurdity of the evidence. When cornered, defenders of bans will say, "well, its something we should do anyway." That is post-modern science -- narrative over rigid adherence to facts.
If you want post-modern science in a nutshell, think of the term "fake but accurate". It is one of the most post-modern phrases I can imagine. It means that certain data, or an analysis, or experiment was somehow wrong or corrupted or failed typical standards of scientific rigor, but was none-the-less "accurate". How can that be? Because accuracy is not defined as logical conformance to observations. It has been redefined as "consistent with the narrative." She actually argues that our standard of evidence should be reduced for things we already "know". But know do we "know" it if we have not checked the evidence? Because for Oreskes, and probably for an unfortunately large portion of modern academia, we "know" things because they are part of the narrative constructed by these self-same academic elites.
This seems to claim to be able to take photos fast enough to capture the movement of light. Is that really possible? Reminds me of watching sunrise on Discworld.
I got an email today from some random Gmail account asking me to write about HyrdoInfra. OK. The email begins: "HydroInfra Technologies (HIT) is a Stockholm based clean tech company that has developed an innovative approach to neutralizing carbon fuel emissions from power plants and other polluting industries that burn fossil fuels."
Does it eliminate CO2? NOx? Particulates? SOx? I actually was at the bottom of my inbox for once so I went to the site. I went to this applications page. Apparently, it eliminates the "toxic cocktail" of pollutants that include all the ones I mentioned plus mercury and heavy metals. Wow! That is some stuff.
Their key product is a process for making something they call "HyrdroAtomic Nano Gas" or HNG. It sounds like their PR guys got Michael Crichton and JJ Abrams drunk in a brainstorming session for pseudo-scientific names.
But hold on, this is the best part. Check out the description of HNG and how it is made:
Splitting water (H20) is a known science. But the energy costs to perform splitting outweigh the energy created from hydrogen when the Hydrogen is split from the water molecule H2O.
This is where mainstream science usually closes the book on the subject.
We took a different approach by postulating that we could split water in an energy efficient way to extract a high yield of Hydrogen at very low cost.
A specific low energy pulse is put into water. The water molecules line up in a certain structure and are split from the Hydrogen molecules.
The result is HNG.
HNG is packed with ‘Exotic Hydrogen’
Exotic Hydrogen is a recent scientific discovery.
HNG carries an abundance of Exotic Hydrogen and Oxygen.
On a Molecular level, HNG is a specific ratio mix of Hydrogen and Oxygen.
The unique qualities of HNG show that the placement of its’ charged electrons turns HNG into an abundant source of exotic Hydrogen.
HNG displays some very different properties from normal hydrogen.
Some basic facts:
- HNG instantly neutralizes carbon fuel pollution emissions
- HNG can be pressurized up to 2 bars.
- HNG combusts at a rate of 9000 meters per second while normal Hydrogen combusts at a rate 600 meters per second.
- Oxygen values actually increase when HNG is inserted into a diesel flame.
- HNG acts like a vortex on fossil fuel emissions causing the flame to be pulled into the center thus concentrating the heat and combustion properties.
- HNG is stored in canisters, arrayed around the emission outlet channels. HNG is injected into the outlets to safely & effectively clean up the burning of fossil fuels.
- The pollution emissions are neutralized instantly & safely with no residual toxic cocktail or chemicals to manage after the HNG burning process is initiated.
Exotic Hyrdrogen! I love it. This is probably a component of the "red matter" in the Abrams Star Trek reboot. Honestly, someone please tell me this a joke, a honeypot for mindless environmental activist drones. What are the chemical reactions going on here? If CO2 is captured, what form does it take? How does a mixture of Hydrogen and Oxygen molecules in whatever state they are in do anything with heavy metals? None of this is on the website. On their "validation" page, they have big labels like "Horiba" that look like organizations thave somehow put their impremature on the study. In fact, they are just names of analytical equipment makers. It's like putting "IBM" in big print on your climate study because you ran your model on an IBM computer.
SCAM! Honestly, when you see an article written to attract investment that sounds sort of impressive to laymen but makes absolutely no sense to anyone who knows the smallest about of Chemistry or Physics, it is an investment scam.
But they seem to get a lot of positive press. In my search of Google, everything in the first ten pages or so are just uncritical republication of their press releases in environmental and business blogs. You actually have to go into the comments sections of these articles to find anyone willing to observe this is all total BS. If you want to totally understand why the global warming debate gets nowhere, watch commenter Michael at this link desperately try to hold onto his faith in HydroInfra while people who actually know things try to explain why this makes no sense.
Update: If you want an actual nano-material that absorbs various pollutants, this may be one.
How do I know that average people do not believe the one in five women raped on campus meme? Because parents still are sending their daughters to college, that's why. In increasing numbers that threaten to overwhelm males on campus. What is more, I sat recently through new parent orientations at a famous college and parents asked zillions of stupid, trivial questions and not one of them inquired into the safety of their daughters on campus or the protections afforded them. Everyone knows that some women are raped and badly taken advantage of on campus, but everyone also knows the one in five number is overblown BS.
Imagine that there is a country with a one in 20 chance of an American woman visiting getting raped. How many parents would yank their daughters from any school trip headed for that country -- a lot of them, I would imagine. If there were a one in five chance? No one would allow their little girls to go. I promise. I am a dad, I know.
Even if the average person can't articulate their source of skepticism, most people understand in their gut that we live in a post-modern world when it comes to media "data". Political discourse, and much of the media, is ruled by the "fake but accurate" fact. That is, the number everyone knows has no valid source or basis in fact or that everyone knows fails every smell test, but they use anyway because it is in a good cause. They will say, "well one in five is probably high but it's an important issue anyway".
The first time I ever encountered this effect was on an NPR radio show years ago. The hosts were discussing a well-accepted media statistic at the time that there were a million homeless people (these homeless people only seem to exist, at least in the media, during Republican presidencies so I suppose this dates all the way back to the Reagan or Bush years). Someone actually tracked down this million person stat and traced it back to a leading homeless advocate, who admitted he just made it up for an interview, and was kind of amazed everyone just accepted it. But the interesting part was a discussion with several people in the media who still used the statistic even after they knew it to be outsourced BS, made up out of thin air. Their logic: homelessness was a critical issue and the stat may be wrong, but it was OK to essentially lie (they did not use the word "lie") about the facts in a good cause. The statistic was fake, but accurately reflected a real problem. Later, the actual phrase "fake but accurate" would be coined in association with the George W. Bush faked air force national guard papers. Opponents of Bush argued after the forgery became clear to everyone but Dan Rather that the letters may have been fake but they accurately reflected character flaws in the President.
And for those on the Left who want to get bent out of shape that this is just aimed at them, militarists love these post-modern non-facts to stir up fear in the war on terror, the war on crime, the war on drugs, and the war on just about everyone in the middle east.
PS- Neil deGrasse Tyson has been criticized of late for the same failing, the use of fake quotes that supposedly accurately reflect the mind of the quoted person. It is one thing for politicians to play this game. It is worse for scientists. It is the absolute worst for a scientist to play this anti-science game in the name of defending science.
The BBC has decided not to every talk to climate skeptics again, in part based on the "evidence" of computer modelling
Climate change skeptics are being banned from BBC News, according to a new report, for fear of misinforming people and to create more of a "balance" when discussing man-made climate change.
The latest casualty is Nigel Lawson, former London chancellor and climate change skeptic, who has just recently been barred from appearing on BBC. Lord Lawson, who has written about climate change, said the corporation is silencing the debate on global warming since he discussed the topic on its Radio 4 Today program in February.
This skeptic accuses "Stalinist" BBC of succumbing to pressure from those with renewable energy interests, like the Green Party, in an editorial for the Daily Mail.
He appeared on February 13 debating with scientist Sir Brian Hoskins, chairman of the Grantham Institute for Climate Change at Imperial College, London, to discuss recent flooding that supposedly was linked to man-made climate change.
Despite the fact that the two intellectuals had a "thoroughly civilized discussion," BBC was "overwhelmed by a well-organized deluge of complaints" following the program. Naysayers harped on the fact that Lawson was not a scientist and said he had no business voicing his opinion on the subject.
Among the objections, including one from Green Party politician Chit Chong, were that Lawson's views were not supported by evidence from computer modeling.
I see this all the time. A lot of things astound me in the climate debate, but perhaps the most astounding has been to be accused of being "anti-science" by people who have such a poor grasp of the scientific process.
Computer models and their output are not evidence of anything. Computer models are extremely useful when we have hypotheses about complex, multi-variable systems. It may not be immediately obvious how to test these hypotheses, so computer models can take these hypothesized formulas and generate predicted values of measurable variables that can then be used to compare to actual physical observations.
This is no different (except in speed and scale) from a person in the 18th century sitting down with Newton's gravitational equations and grinding out five years of predicted positions for Venus (in fact, the original meaning of the word "computer" was a human being who ground out numbers in just his way). That person and his calculations are the exact equivalent of today's computer models. We wouldn't say that those lists of predictions for Venus were "evidence" that Newton was correct. We would use these predictions and compare them to actual measurements of Venus's position over the next five years. If they matched, we would consider that match to be the real evidence that Newton may be correct.
So it is not the existence of the models or their output that are evidence that catastrophic man-made global warming theory is correct. It would be evidence that the output of these predictive models actually match what plays out in reality. Which is why skeptics think the fact that the divergence between climate model temperature forecasts and actual temperatures is important, but we will leave that topic for other days.
The other problem with models
The other problem with computer models, besides the fact that they are not and cannot constitute evidence in and of themselves, is that their results are often sensitive to small changes in tuning or setting of variables, and that these decisions about tuning are often totally opaque to outsiders.
I did computer modelling for years, though of markets and economics rather than climate. But the techniques are substantially the same. And the pitfalls.
Confession time. In my very early days as a consultant, I did something I am not proud of. I was responsible for a complex market model based on a lot of market research and customer service data. Less than a day before the big presentation, and with all the charts and conclusions made, I found a mistake that skewed the results. In later years I would have the moral courage and confidence to cry foul and halt the process, but at the time I ended up tweaking a few key variables to make the model continue to spit out results consistent with our conclusion. It is embarrassing enough I have trouble writing this for public consumption 25 years later.
But it was so easy. A few tweaks to assumptions and I could get the answer I wanted. And no one would ever know. Someone could stare at the model for an hour and not recognize the tuning.
Robert Caprara has similar thoughts in the WSJ (probably behind a paywall) Hat tip to a reader
The computer model was huge—it analyzed every river, sewer treatment plant and drinking-water intake (the places in rivers where municipalities draw their water) in the country. I'll spare you the details, but the model showed huge gains from the program as water quality improved dramatically. By the late 1980s, however, any gains from upgrading sewer treatments would be offset by the additional pollution load coming from people who moved from on-site septic tanks to public sewers, which dump the waste into rivers. Basically the model said we had hit the point of diminishing returns.
When I presented the results to the EPA official in charge, he said that I should go back and "sharpen my pencil." I did. I reviewed assumptions, tweaked coefficients and recalibrated data. But when I reran everything the numbers didn't change much. At our next meeting he told me to run the numbers again.
After three iterations I finally blurted out, "What number are you looking for?" He didn't miss a beat: He told me that he needed to show $2 billion of benefits to get the program renewed. I finally turned enough knobs to get the answer he wanted, and everyone was happy...
I realized that my work for the EPA wasn't that of a scientist, at least in the popular imagination of what a scientist does. It was more like that of a lawyer. My job, as a modeler, was to build the best case for my client's position. The opposition will build its best case for the counter argument and ultimately the truth should prevail.
If opponents don't like what I did with the coefficients, then they should challenge them. And during my decade as an environmental consultant, I was often hired to do just that to someone else's model. But there is no denying that anyone who makes a living building computer models likely does so for the cause of advocacy, not the search for truth.
I mostly ignore, and tend to be skeptical of, most pronouncements on foods that supposedly kill us and foods that are supposedly superfoods. I have a solid love of meat and have never let the fear of saturated fat stop me from enjoying a good steak from time to time.
I had heard that a lot of the "settled science" on saturated fat was iffy but I had no idea it was this bad.
Our distrust of saturated fat can be traced back to the 1950s, to a man named Ancel Benjamin Keys, a scientist at the University of Minnesota. Dr. Keys was formidably persuasive and, through sheer force of will, rose to the top of the nutrition world...
As the director of the largest nutrition study to date, Dr. Keys was in an excellent position to promote his idea. The "Seven Countries" study that he conducted on nearly 13,000 men in the U.S., Japan and Europe ostensibly demonstrated that heart disease wasn't the inevitable result of aging but could be linked to poor nutrition.
Critics have pointed out that Dr. Keys violated several basic scientific norms in his study. For one, he didn't choose countries randomly but instead selected only those likely to prove his beliefs, including Yugoslavia, Finland and Italy. Excluded were France, land of the famously healthy omelet eater, as well as other countries where people consumed a lot of fat yet didn't suffer from high rates of heart disease, such as Switzerland, Sweden and West Germany. The study's star subjects—upon whom much of our current understanding of the Mediterranean diet is based—were peasants from Crete, islanders who tilled their fields well into old age and who appeared to eat very little meat or cheese.
As it turns out, Dr. Keys visited Crete during an unrepresentative period of extreme hardship after World War II. Furthermore, he made the mistake of measuring the islanders' diet partly during Lent, when they were forgoing meat and cheese. Dr. Keys therefore undercounted their consumption of saturated fat. Also, due to problems with the surveys, he ended up relying on data from just a few dozen men—far from the representative sample of 655 that he had initially selected. These flaws weren't revealed until much later, in a 2002 paper by scientists investigating the work on Crete—but by then, the misimpression left by his erroneous data had become international dogma.
In 1961, Dr. Keys sealed saturated fat's fate by landing a position on the nutrition committee of the American Heart Association, whose dietary guidelines are considered the gold standard. Although the committee had originally been skeptical of his hypothesis, it issued, in that year, the country's first-ever guidelines targeting saturated fats. The U.S. Department of Agriculture followed in 1980.
Don't these guys know this is settled science? These saturated fat skeptics must be in the pay of big cattle.
The cherry-picking and small sample sizes are unfortunately a staple of science, but I particularly laughed at the practice of assessing meat consumption during Lent.
The footprints are cool. But what really had an effect on me is how vividly this picture portrays the power of geologic forces (combined with time). This wall of rock was obviously once horizontal.
NEITHER dead or alive, knife-wound or gunshot victims will be cooled down and placed in suspended animation later this month, as a groundbreaking emergency technique is tested out for the first time....
The technique involves replacing all of a patient's blood with a cold saline solution, which rapidly cools the body and stops almost all cellular activity. "If a patient comes to us two hours after dying you can't bring them back to life. But if they're dying and you suspend them, you have a chance to bring them back after their structural problems have been fixed," says surgeon Peter Rhee at the University of Arizona in Tucson, who helped develop the technique.
The benefits of cooling, or induced hypothermia, have been known for decades. At normal body temperature – around 37 °C – cells need a regular oxygen supply to produce energy. When the heart stops beating, blood no longer carries oxygen to cells. Without oxygen the brain can only survive for about 5 minutes before the damage is irreversible.
However, at lower temperatures, cells need less oxygen because all chemical reactions slow down. This explains why people who fall into icy lakes can sometimes be revived more than half an hour after they have stopped breathing.
From an entirely unexpected quarter, comes a story of the shortcomings of computer modelling, in this case in the America's cup. It is a great example of how models reflect the biases of their authors. In this case, the author assumed that the fastest upwind path was the shortest path (ie with the shallowest possible tacks). It turns out that with the changing technology of boats, particularly the hydrofoil, a longer but higher velocity path was more optimal, but the model refused to consider that solution because it was programmed not to.
Here is the problem: There exists a highly dynamic, multi- multi- variable system. One input is changed. How much, and in what ways, did that change affect the system?
Here are two examples:
The difficulty, of course, is that there is no way to do a controlled study, and while one's studied variable is changing, so are thousands, even millions of others. These two examples have a number of things in common:
So, for those of you who may think that we are at the end of math (or science), here is a class of problem that is clearly, just from these two examples, enormously important. And we cannot solve it -- we can't even come close, despite the hubris of Paul Krugman or Michael Mann who may argue differently. We are explaining fire with Phlogiston.
I have no idea where the solution lies. Perhaps all we can hope for is a Goedel to tell us the problem is impossible to solve so stop trying. Perhaps the seeds of a solution exist but they are buried in another discipline (God knows the climate science field often lacks even the most basic connection to math and statistics knowledge).
Maybe I am missing something, but who is even working on this? By "working on it" I do not mean trying to build incrementally "better" economics or climate models. Plenty of folks doing that. But who is working on new approaches to tease out relationships in complex multi-variable systems?
After years of being demonized by friends and family for saying that the moon is not bigger when it is on the horizon, that it is just an optical illusion, I am happy to be vindicated
I thought the various explanations were fascinating, though I think the commenter's suggestion that it is a glitch in the matrix is the most compelling.
Hat tip: Tom Kirkendall
A reader sends me a story of global warming activist who clearly doesn't know even the most basic facts about global warming. Since this article is about avoiding appeals to authority, so I hate to ask you to take my word for it, but it is simply impossible to immerse oneself in the science of global warming for any amount of time without being able to immediately rattle off the four major global temperature data bases (or at least one of them!)
I don't typically find it very compelling to knock a particular point of view just because one of its defenders is a moron, unless that defender has been set up as a quasi-official representative of that point of view (e.g. Al Gore). After all, there are plenty of folks on my side of issues, including those who are voicing opinions skeptical of catastrophic global warming, who are making screwed up arguments.
However, I have found over time this to be an absolutely typical situation in the global warming advocacy world. Every single time I have publicly debated this issue, I have understood the opposing argument, ie the argument for catastrophic global warming, better than my opponent. In fact, I finally had to write a first chapter to my usual presentation. In this preamble, I outline the case and evidence for manmade global warming so the audience could understand it before I then set out to refute it.
The problem is that the global warming alarm movement has come to rely very heavily on appeals to authority and ad hominem attacks in making their case. What headlines do you see? 97% of scientists agree, the IPCC is 95% sure, etc. These "studies", which Lord Monkton (with whom I often disagree but who can be very clever) calls "no better than a show of hands", dominate the news. When have you ever seen a story in the media about the core issue of global warming, which is diagnosing whether positive feedbacks truly multiply small bits of manmade warming to catastrophic levels. The answer is never.
Global warming advocates thus have failed to learn how to really argue the science of their theory. In their echo chambers, they have all agreed that saying "the science is settled" over and over and then responding to criticism by saying "skeptics are just like tobacco lawyers and holocaust deniers and are paid off by oil companies" represents a sufficient argument.** Which means that in an actual debate, they can be surprisingly easy to rip to pieces. Which may be why most, taking Al Gore's lead, refuse to debate.
All of this is particularly ironic since it is the global warming alarmists who try to wrap themselves in the mantle of the defenders of science. Ironic because the scientific revolution began only when men and women were willing to reject appeals to authority and try to understand things for themselves.
** Another very typical tactic: They will present whole presentations without a single citation. But make one statement in your rebuttal as a skeptic that is not backed with a named, peer-reviewed study, and they will call you out on it. I remember in one presentation, I was presenting some material that was based on my own analysis. "But this is not peer-reviewed" said one participant, implying that it should therefore be ignored. I retorted that it was basic math, that the data sources were all cited, and they were my peers -- review it. Use you brains. Does it make sense? Is there a flaw? But they don't want to do that. Increasingly, oddly, science is about having officially licensed scientists delivery findings to them on a platter.
Former vice president Al Gore on Monday called for making climate change "denial" a taboo in society.
“Within the market system we have to put a price on carbon, and within the political system, we have to put a price on denial,” Gore said at the Social Good Summit New York City.
Incredibly, the suggestion of introducing taboos and penalties in a scientific debate is coming from the side that claims to be the great defenders of science.
Kevin Drum preahces against the evils of teen tanning, which he follows with a conclusion that obviously Republicans are evil for opposing a tanning tax
Indoor tanning, on the other hand, is just plain horrifically bad. Aaron Carroll provides the basics:indoor tanning before age 25 increases the risk of skin cancer by 50-100 percent, and melanoma risk (the worst kind of skin cancer) increases by 1.8 percent with each additional tanning session per year. Despite this, the chart on the right shows the prevalence of indoor tanning among teenagers. It's high! Aaron is appalled:
This is so, so, so, so, so, so, so bad for you. Why don’t I see rage against this in my inbox like I do for diet soda? Why can’t people differentiate risk appropriately?
And who would fight a tax on this?
I am not going to get into the argument here (much) about individual choice and Pigovian taxes (by the way, check out the comments for a great example of what I call the Health Care Trojan Horse, the justifying of micro-regulation of our behavior because it might increase government health care costs).
I want to write about risk. Drum and Carroll are taking the high ground here, claiming they are truly the ones who understand risk and all use poor benighted folks do not. But Drum and Carroll repeat the mistake in this post which is the main reason no one can parse risk.
A key reason people don't understand risk is that the media talks about large percent changes to a small risk, without ever telling us the underlying unadjusted base risk. A 100% increase in a risk may be trivial, or it might be bad. A 100% increase in risk of death in a car accident would be very bad. A 100% increase in the risk of getting hit by lightning would be trivial.
In this case, it's probably somewhere in between. The overall lifetime risk of melanoma is about 2%. This presumably includes those with bad behavior so the non-tanning number is likely lower, but we will use 2% as our base risk understanding that it is likely high. The 5-year survival rate from these cancers (which by the way tend to show up after the age 60) is 90+% if you are white -- if you are black it is much lower (I don't know if that is a socio-economic problem or some aspect of the biology of darker skin).
So a teenager has a lifetime chance of dying early from melanoma of about 0.2%. A 50% increase to this would raise this to 0.3%. An extra one in one thousand chance of dying early from something likely to show up in old age -- is that "so, so, so, so, so, so, so bad"? For some yes, for some no. That is what individual choice is all about.
But note the different impacts on perception.
Both are true. Both should likely be in any article on the topic. Only the first ever is included, though.
I spent years, before I burned out on the task, picking over bad climate studies, and at the time reached the conclusion that there was something about the climate science field that was anomalous, tolerating so much bad science, bad sampling methodology, and bad statistical approaches.
However, now I am coming to the conclusion that perhaps most studies in every field are dominated by this same crap. Here is an example, from the NTSB on busses.