Today I Learned:
1) A watt is 1 Joule/second. I should have known there would be a stupidly simple relationship between the two.
2) Fact 1 leads to fact 2. I know, from previous lectures and other sources, that the human body generates approximately the same amount of heat as a 100 watt lightbulb. That also means it's drawing about the same amount of power (though chemically instead of electrically). That means we can peg the approximate power consumption of the human body at around 100 jouls/second... which finally gives me a meaningful reference point for a joule -- about 1/100th the energy required to power a human body for 1 second.
3) The sum of all the whole numbers is -1/12. Yeah, (1 + 2 + 3 + 4 + ...) = -1/12. This is probably the most ridiculous, bizarre, and potentially insightful fact (if I can really get why it's true) I think I've ever written in this TIL series. And yes, I know it's obviously false; and yes, it's actually true.
This 'fact' was discovered hundreds of years ago by a well-meaning monk, and was the subject of much debate for a century and a half. I think the mathematicians eventually came to the consensus that it's true, but the real kicker is that this sum comes up ALL THE TIME in physics, and the identity (1 + 2 + 3 + 4...) = -1/12 makes the physics come out to the physically correct, experimentally-verifiable answer. This is the first time I know of that a physical experiment has confirmed a mathematical result*.
There's a nice video about this... thing here: https://www.youtube.com/watch?v=w-I6XTVZXww. Personally, I think the proof in the "extra footage" video linked from the above video is more convincing. Check them both out, though! *I say this with some glibness -- again, I think sure mathematicians were convinced well before it turned up in physics... but it certainly is what convinces me.
Sunday, November 29, 2015
Saturday, November 28, 2015
Waterproof Drywall, Cooking Brown Rice, and Educational Politics
Today I Learned:
1) There is a special kind of waterproof drywall that's used in the walls and floors right around bathtubs and showers. At least some of the time, it's painted to look like the cross-hatching pattern common in metal flooring.
2) Brown rice takes *significantly* longer to cook than white rice -- about 2.5 times as long, to be precise.
3) Educational politics is pretty intense and pretty hideous.
Example: there is a coalition of states which use a shared standardized test called PARCC. Massachusetts has just joined this coalition, making it one of the largest, most influential, and wealthiest members. However, Massachusetts has opted for "hybrid" test system, meaning it retains the right to modify any of the test questions in the PARCC for their students... which makes the test no longer standardized. Which essentially makes it useless for the purpose of actually figuring out what works and what doesn't. The PARCC coalition is unlikely to do anything like disallow Massachusetts from using the PARCC materials because the state is so influential. This will likely open the door to other states doing the same, which may completely destroy the effectiveness of PARCC as a research tool.
Why has Massachusetts chosen this route? Well, I'm not involved in the decision, and I'm not even an educational expert, so what I'm about to tell you is decidedly third-hand information. The argument I've heard is that educational systems get a lot of backlash from... someone... (probably taxpayers and politicians) when they use standardized tests written and enforced by outside agencies. By retaining the ability to modify the test, (whoever makes these decisions in) Massachusetts makes using the PARCC a much more politically palatable decision.
Why use the PARCC at all if they're not going to stick to it? After all, one of the most useful functions of nationwide standardized tests is their comparability, and Massachusetts is removing that. Well, it turns out it's really expensive and difficult to get *good* test questions. There's a lot that goes into making them fair and comparable and actually test the material, and it's really, really not worth it for every school or school system to make their own. You can buy test questions from companies like McGraw Hill and ETS, but that's super expensive. By signing up with PARCC, which is state-run and almost certainly not-for-profit(...?), Massachusetts gets access to some quality, vetted test questions at a fraction of the cost of the commercially-available ones. So, as so often, it comes down to money.
The weirdest thing is, I'm not sure Massachusetts isn't doing exactly the right thing. Money in education is tight all around, and it doesn't look like there's more funding coming any time soon... if this does nothing but free up money in the Massachusetts school system that would otherwise go towards more expensive test questions, then that still sounds an awful lot like a win. I'm talking WAY out of my field here, more than usual, so if anyone knows more about the situation with Massachusetts and PARCC, please let me know.
(Also learned once again how to spell Massachusetts....)
1) There is a special kind of waterproof drywall that's used in the walls and floors right around bathtubs and showers. At least some of the time, it's painted to look like the cross-hatching pattern common in metal flooring.
2) Brown rice takes *significantly* longer to cook than white rice -- about 2.5 times as long, to be precise.
3) Educational politics is pretty intense and pretty hideous.
Example: there is a coalition of states which use a shared standardized test called PARCC. Massachusetts has just joined this coalition, making it one of the largest, most influential, and wealthiest members. However, Massachusetts has opted for "hybrid" test system, meaning it retains the right to modify any of the test questions in the PARCC for their students... which makes the test no longer standardized. Which essentially makes it useless for the purpose of actually figuring out what works and what doesn't. The PARCC coalition is unlikely to do anything like disallow Massachusetts from using the PARCC materials because the state is so influential. This will likely open the door to other states doing the same, which may completely destroy the effectiveness of PARCC as a research tool.
Why has Massachusetts chosen this route? Well, I'm not involved in the decision, and I'm not even an educational expert, so what I'm about to tell you is decidedly third-hand information. The argument I've heard is that educational systems get a lot of backlash from... someone... (probably taxpayers and politicians) when they use standardized tests written and enforced by outside agencies. By retaining the ability to modify the test, (whoever makes these decisions in) Massachusetts makes using the PARCC a much more politically palatable decision.
Why use the PARCC at all if they're not going to stick to it? After all, one of the most useful functions of nationwide standardized tests is their comparability, and Massachusetts is removing that. Well, it turns out it's really expensive and difficult to get *good* test questions. There's a lot that goes into making them fair and comparable and actually test the material, and it's really, really not worth it for every school or school system to make their own. You can buy test questions from companies like McGraw Hill and ETS, but that's super expensive. By signing up with PARCC, which is state-run and almost certainly not-for-profit(...?), Massachusetts gets access to some quality, vetted test questions at a fraction of the cost of the commercially-available ones. So, as so often, it comes down to money.
The weirdest thing is, I'm not sure Massachusetts isn't doing exactly the right thing. Money in education is tight all around, and it doesn't look like there's more funding coming any time soon... if this does nothing but free up money in the Massachusetts school system that would otherwise go towards more expensive test questions, then that still sounds an awful lot like a win. I'm talking WAY out of my field here, more than usual, so if anyone knows more about the situation with Massachusetts and PARCC, please let me know.
(Also learned once again how to spell Massachusetts....)
Friday, November 27, 2015
Door Handles, Mine Problems, and Warfarin
Today I Learned:
1) Door handles are not, as a rule, found halfway up the door, which unfortunately makes them asymmetric to rotations around the horizontal axis through the plane of the door (so you can't flip them upside-down to switch from inward-facing to outward-facing or vice versa).
2) Arsenic and selenium are notoriously problematic metals for metal mines. Like many other heavy metals, arsenic and selenium are common toxic contaminants and have to be removed from the main ores. Unlike many other heavy metals, there isn't much of a market for arsenic or selenium, so it's not economical to extract them and sell them, so many mines have to dispose of them somehow.
3) Warfarin, a blood-thinning drug, is used as a mouse poison. It's laced into tasty food traps, and once eaten it causes the mice to hemmorage to death.
1) Door handles are not, as a rule, found halfway up the door, which unfortunately makes them asymmetric to rotations around the horizontal axis through the plane of the door (so you can't flip them upside-down to switch from inward-facing to outward-facing or vice versa).
2) Arsenic and selenium are notoriously problematic metals for metal mines. Like many other heavy metals, arsenic and selenium are common toxic contaminants and have to be removed from the main ores. Unlike many other heavy metals, there isn't much of a market for arsenic or selenium, so it's not economical to extract them and sell them, so many mines have to dispose of them somehow.
3) Warfarin, a blood-thinning drug, is used as a mouse poison. It's laced into tasty food traps, and once eaten it causes the mice to hemmorage to death.
Thursday, November 26, 2015
Marijuana In Colorado, An Alternative to Milk, and One More Thing Not To Do With Raisins
Today I Learned:
1) ...a couple of facts about the marijuana industry in Colorado. Firstly, there are some interesting conflicts between Colorado law (which allows the growth and sale of marijuana) and federal law (which prohibits it). One of the effects of this is that national banks generally won't touch marijuana sales, which means that the industry is currently a cash-only business, which has led to a large influx of cash (as in physical bills) to the state.
One unfortunate effect of the industry is that a ton of warehouses have opened up for growing the stuff, which has spiked energy demand and screwed over Colorado's plans to get some percentage of their energy budget from renewable resources. Instead of powering the state off of solar energy, Colorado uses more fossil fuels to *produce* solar energy for a rather different green industry.
2) A very tasty alternative to milk in ceral is a bowl of microwaved frozen blueberries.
3) Apparently a pretty common accident among young children is for them to stick raisins up their nose, which over the course of hours or days swell to something more like the size of a grape and get stuck. I'm not joking.
Also, soaking raisins in warm water does cause them to swell up, but not as quickly as I would have thought. Warm or hot water seems to speed the process considerably. It also works for craisins. Banana chips not so much.
1) ...a couple of facts about the marijuana industry in Colorado. Firstly, there are some interesting conflicts between Colorado law (which allows the growth and sale of marijuana) and federal law (which prohibits it). One of the effects of this is that national banks generally won't touch marijuana sales, which means that the industry is currently a cash-only business, which has led to a large influx of cash (as in physical bills) to the state.
One unfortunate effect of the industry is that a ton of warehouses have opened up for growing the stuff, which has spiked energy demand and screwed over Colorado's plans to get some percentage of their energy budget from renewable resources. Instead of powering the state off of solar energy, Colorado uses more fossil fuels to *produce* solar energy for a rather different green industry.
2) A very tasty alternative to milk in ceral is a bowl of microwaved frozen blueberries.
3) Apparently a pretty common accident among young children is for them to stick raisins up their nose, which over the course of hours or days swell to something more like the size of a grape and get stuck. I'm not joking.
Also, soaking raisins in warm water does cause them to swell up, but not as quickly as I would have thought. Warm or hot water seems to speed the process considerably. It also works for craisins. Banana chips not so much.
Wednesday, November 25, 2015
Gyrases, More Gyrases, and Diesel Fuel
Today I Learned:
1) As bacteria switch from exponential phase (when they grow like mad) to stationary phase (when they're in population equilibrium and don't grow much), they severely curtail the amount of gyrases and other DNA-relaxing enzymes. Makes sense -- they're not replicating or transcribing a ton, so they're not introducing as much strain into their genomes/plasmids.
2) Speaking of gyrases and topoisomerases, there's experimental evidence that, at least on plasmids, the amount of gyrases and topoisomerases in bacterial cells is not even close to enough to actually keep plasmids relaxed. Once expression starts, the plasmid pretty quickly gets supercoiled, which may be part of what drives burstiness in bacterial transcription. Do bacterial genes on plasmids burst more than bacterial genes on chromosomes? Could you reduce burstiness by expressing a ton of gyrase?
3) ...a few things about diesel fuel. Diesel fuel is a by-product of gasoline production, and is chemically fairly similar to jet fuel. It is more efficient than gasoline, and currently burns cleaner. I'm not entirely sure why we use predominantly gasoline, but I think it's because a) diesel is fairly hard to burn, so simple sparking doesn't work on diesel, and b) because diesel used to be super dirty and produced a lot of pollutants.
Also, diesel is surprisingly similar to vegetable oil and can basically be run straght on vegetable oil (peanut oil works particularly nicely). The problem vegetable oil has is that it's very viscous compared to real diesel, which gunks up the engine. There are a few ways around this. One is to rig up a system that heats the vegetable oil a lot before introducing it into the engine. This works, but can be kind of a pain. Some people also just pour engine oil into their tanks to help lubricate stuff. That sounds risky to me. The most elegant option IMHO is to chemically take out the impurities that make it viscous. Specifically, there are enough surfactants in vegetable oil that allow water-soluble contaminants to stay in the oil, and you can remove those surfactants with some chemistry involving methanol and some other stuff I didn't catch in the conversation where I learned this. With the surfactants gone, the water-soluble contaminants just fall right out of solution, and you have clean oil for your diesel engine!
1) As bacteria switch from exponential phase (when they grow like mad) to stationary phase (when they're in population equilibrium and don't grow much), they severely curtail the amount of gyrases and other DNA-relaxing enzymes. Makes sense -- they're not replicating or transcribing a ton, so they're not introducing as much strain into their genomes/plasmids.
2) Speaking of gyrases and topoisomerases, there's experimental evidence that, at least on plasmids, the amount of gyrases and topoisomerases in bacterial cells is not even close to enough to actually keep plasmids relaxed. Once expression starts, the plasmid pretty quickly gets supercoiled, which may be part of what drives burstiness in bacterial transcription. Do bacterial genes on plasmids burst more than bacterial genes on chromosomes? Could you reduce burstiness by expressing a ton of gyrase?
3) ...a few things about diesel fuel. Diesel fuel is a by-product of gasoline production, and is chemically fairly similar to jet fuel. It is more efficient than gasoline, and currently burns cleaner. I'm not entirely sure why we use predominantly gasoline, but I think it's because a) diesel is fairly hard to burn, so simple sparking doesn't work on diesel, and b) because diesel used to be super dirty and produced a lot of pollutants.
Also, diesel is surprisingly similar to vegetable oil and can basically be run straght on vegetable oil (peanut oil works particularly nicely). The problem vegetable oil has is that it's very viscous compared to real diesel, which gunks up the engine. There are a few ways around this. One is to rig up a system that heats the vegetable oil a lot before introducing it into the engine. This works, but can be kind of a pain. Some people also just pour engine oil into their tanks to help lubricate stuff. That sounds risky to me. The most elegant option IMHO is to chemically take out the impurities that make it viscous. Specifically, there are enough surfactants in vegetable oil that allow water-soluble contaminants to stay in the oil, and you can remove those surfactants with some chemistry involving methanol and some other stuff I didn't catch in the conversation where I learned this. With the surfactants gone, the water-soluble contaminants just fall right out of solution, and you have clean oil for your diesel engine!
Tuesday, November 24, 2015
Yet Another Reason Not To Use Excell, Blue River Technology, and Tamale Sauce
Today I Learned:
1) There is no way to apply formatting to multiple series of data in Excell 2011 (with the possible exception of scripting, and frankly if I ever find myself scripting in Excell I'm probably doing something wrong).
2) A startup company called Blue River Technology is building a robot that identifies weeds by sight and kills them with an injection of fertilizer. They've also built a robotic farming system for lettuce which automatically thins lettuce crops for optimal yield (and, I think, gets rid of weeds while it's at it).
Blue River Technology is an interesting-looking company. It was supposedly founded "to make farming more sustainable through robotics and computer vision.". Thats a tall order. From their web page: "Based in Mountain View, California, Blue River Technology’s mission is simple: to deliver advanced technology for better agriculture. Our pioneering approach utilizes computer vision and robotics to build a future of plant-by-plant agriculture – where the needs of each plant are precisely measured and delivered, significantly reducing chemical use." They're also looking to hire a software developer and a computer vision engineer, with relatively light position requirements. If you're looking for a coding job involving machine learning and food sustainability, you might want to check them out.
Thanks to Mikas Kuprenas for pointing me to this one! (Also, the author of this post declares no conflicts of interest. I just think it looks like a cool company.)
3) Tamales are sometimes served with a very spicy grain-and-vegetable salsa which looks unfortunately similar to soup.
1) There is no way to apply formatting to multiple series of data in Excell 2011 (with the possible exception of scripting, and frankly if I ever find myself scripting in Excell I'm probably doing something wrong).
2) A startup company called Blue River Technology is building a robot that identifies weeds by sight and kills them with an injection of fertilizer. They've also built a robotic farming system for lettuce which automatically thins lettuce crops for optimal yield (and, I think, gets rid of weeds while it's at it).
Blue River Technology is an interesting-looking company. It was supposedly founded "to make farming more sustainable through robotics and computer vision.". Thats a tall order. From their web page: "Based in Mountain View, California, Blue River Technology’s mission is simple: to deliver advanced technology for better agriculture. Our pioneering approach utilizes computer vision and robotics to build a future of plant-by-plant agriculture – where the needs of each plant are precisely measured and delivered, significantly reducing chemical use." They're also looking to hire a software developer and a computer vision engineer, with relatively light position requirements. If you're looking for a coding job involving machine learning and food sustainability, you might want to check them out.
Thanks to Mikas Kuprenas for pointing me to this one! (Also, the author of this post declares no conflicts of interest. I just think it looks like a cool company.)
3) Tamales are sometimes served with a very spicy grain-and-vegetable salsa which looks unfortunately similar to soup.
Monday, November 23, 2015
Dating the Hoover Dam, Diamond Conductivity, and Paint Thickness
Today I Learned:
1) The Hoover Dam has, near its base, a star chart of very high resolution and accuracy, which can be read to pinpoint the exact day the Hoover Dam was constructed. Why? Well, the Hoover Dam is expected to last about 10,000 years if left to nature... just in case our civilization collapses and somebody runs across it in a few thousand years, we'll have left behind a way they can date it.
Thanks to Mikas Kuprenas for pointing me to this one!
2) Diamonds are very poor electrical conductors, but excellent conductors of heat. This surprised me, but it makes a lot of sense -- the atomic lattice of diamond is very rigid, so vibration at one end is carried very efficiently to the other end.
3) A coat of paint is about 20-30 microns thick.
1) The Hoover Dam has, near its base, a star chart of very high resolution and accuracy, which can be read to pinpoint the exact day the Hoover Dam was constructed. Why? Well, the Hoover Dam is expected to last about 10,000 years if left to nature... just in case our civilization collapses and somebody runs across it in a few thousand years, we'll have left behind a way they can date it.
Thanks to Mikas Kuprenas for pointing me to this one!
2) Diamonds are very poor electrical conductors, but excellent conductors of heat. This surprised me, but it makes a lot of sense -- the atomic lattice of diamond is very rigid, so vibration at one end is carried very efficiently to the other end.
3) A coat of paint is about 20-30 microns thick.
Sunday, November 22, 2015
Radioactive Cookies, Hierarchical Parameter Estimation, and The Beta Distribution, Continued
Today I Learned:
1) Here's a nice little thought experiment to understand the properties of different kinds of dangerous radiation: You have three cookies. One emits alpha radiation, one emits beta radiation, and one emits gamma radiation. You have to put one in your shirt pocket, hold one in your hand, and eat one. Which do you put where?
The best answer: Hold the alpha cookie in your hand. Your skin will block alpha particles, but if they get in your body they're really bad. Put the beta cookie in your pocket -- it's a little stronger, but your clothes should block most of it. The gamma cookie, you eat -- it's going to hurt you, but nothing short of a sheet of lead is going to protect you at all anyway, so it doesn't matter where you put it.
2) Hierarchical parameter estimation is really cool, but it consistently requires more parameters than you might expect.... (Hierarchical parameter estimation, by the way, is a kind of parameter estimation where the parameter of interest takes on different values in different experiments.
My favorite example is in preference estimation, like when a company wants to know the most tastiest amount of salt to put in a jar of salsa is (call it O_salt, for Optimum Salt). You might imagine the company performing a bunch of experiments on people to figure out the true O_salt, and average the results of the experiments to find O_salt. The trouble is, different people have different preferences, which are distributed in some way around O_salt. The better model is that each person P has their own optimum salt concentration P_salt, where P_salt is distributed around some O_salt. )
3) ...a bit more about the Beta distribution. The Beta distribution is a probability distribution over the range [0,1], and it's often used to model probabilities of probabilities -- for example, the probability of a (real world) coin landing heads on a flip might be beta-distributed tightly around 0.5. The cool thing about the beta distribution is that it has two parameters, alpha and beta (sorry about the term overload!), which can be the number of successes and failures observed for a Bernoulli trial, respectively, giving the "correct" probability distribution over the success of that Bernoulli trial (for some sense of "correct" which I haven't bothered to learn).
For example, take the coin flip example. If you flip a coin 100 times and it comes up heads 44 times and tails 56 times, then the probability distribution over the possible probabilities of the coin coming up heads is beta-distributed with alpha = 44 and beta = 56.
If that didn't make sense, I direct you to the place I learned this, which has a more thorough explanation: http://ift.tt/1P1UGYy
1) Here's a nice little thought experiment to understand the properties of different kinds of dangerous radiation: You have three cookies. One emits alpha radiation, one emits beta radiation, and one emits gamma radiation. You have to put one in your shirt pocket, hold one in your hand, and eat one. Which do you put where?
The best answer: Hold the alpha cookie in your hand. Your skin will block alpha particles, but if they get in your body they're really bad. Put the beta cookie in your pocket -- it's a little stronger, but your clothes should block most of it. The gamma cookie, you eat -- it's going to hurt you, but nothing short of a sheet of lead is going to protect you at all anyway, so it doesn't matter where you put it.
2) Hierarchical parameter estimation is really cool, but it consistently requires more parameters than you might expect.... (Hierarchical parameter estimation, by the way, is a kind of parameter estimation where the parameter of interest takes on different values in different experiments.
My favorite example is in preference estimation, like when a company wants to know the most tastiest amount of salt to put in a jar of salsa is (call it O_salt, for Optimum Salt). You might imagine the company performing a bunch of experiments on people to figure out the true O_salt, and average the results of the experiments to find O_salt. The trouble is, different people have different preferences, which are distributed in some way around O_salt. The better model is that each person P has their own optimum salt concentration P_salt, where P_salt is distributed around some O_salt. )
3) ...a bit more about the Beta distribution. The Beta distribution is a probability distribution over the range [0,1], and it's often used to model probabilities of probabilities -- for example, the probability of a (real world) coin landing heads on a flip might be beta-distributed tightly around 0.5. The cool thing about the beta distribution is that it has two parameters, alpha and beta (sorry about the term overload!), which can be the number of successes and failures observed for a Bernoulli trial, respectively, giving the "correct" probability distribution over the success of that Bernoulli trial (for some sense of "correct" which I haven't bothered to learn).
For example, take the coin flip example. If you flip a coin 100 times and it comes up heads 44 times and tails 56 times, then the probability distribution over the possible probabilities of the coin coming up heads is beta-distributed with alpha = 44 and beta = 56.
If that didn't make sense, I direct you to the place I learned this, which has a more thorough explanation: http://ift.tt/1P1UGYy
Saturday, November 21, 2015
Insect Stomachs, An Unexpected Lubricant, and FRAP Normalization
Today I Learned:
1) Insects have alkaline stomachs, not acidic ones. This is what makes some insecticides insecticides and not generic poisons -- they're only active in alkaline conditions, like the guts of insects.
2) Canola oil (and other vegetable oils) can be safely used as sex lubricant (though NOT with condoms or anything else made of plastic), and appear to be less rough on sperm than commercial lubricants (http://ift.tt/1uJZ4fp).
3) ...a good, simple technique for dealing with unwanted*** photobleaching* in experiments like FRAP** -- just keep track of a non-FRAPed part of the cell while you FRAP, and normalize each time point against the non-FRAPed region.
* Photobleaching is an annoying feature of fluorescent microscopy where fluorophores tend to break down over time, leading to a loss of image signal over the course of an experiment.
** FRAP (Fluorescence Recovery After Photobleaching) is a kind of experiment that turns photobleaching into a feature! In FRAP, you quickly blast a small region of something (usually a cell) with a ton of laser exposure, which completely photobleaches all of the fluorophore in that region. You can then watch fluorophore from the surrounding area diffuse back in, which tells you how quickly the fluorescent molecule diffuses.
*** FRAP intentionally uses photobleaching to blast out a region of the cell; there's still background photobleaching on everything else, though, which corrupts the signal you get out.
1) Insects have alkaline stomachs, not acidic ones. This is what makes some insecticides insecticides and not generic poisons -- they're only active in alkaline conditions, like the guts of insects.
2) Canola oil (and other vegetable oils) can be safely used as sex lubricant (though NOT with condoms or anything else made of plastic), and appear to be less rough on sperm than commercial lubricants (http://ift.tt/1uJZ4fp).
3) ...a good, simple technique for dealing with unwanted*** photobleaching* in experiments like FRAP** -- just keep track of a non-FRAPed part of the cell while you FRAP, and normalize each time point against the non-FRAPed region.
* Photobleaching is an annoying feature of fluorescent microscopy where fluorophores tend to break down over time, leading to a loss of image signal over the course of an experiment.
** FRAP (Fluorescence Recovery After Photobleaching) is a kind of experiment that turns photobleaching into a feature! In FRAP, you quickly blast a small region of something (usually a cell) with a ton of laser exposure, which completely photobleaches all of the fluorophore in that region. You can then watch fluorophore from the surrounding area diffuse back in, which tells you how quickly the fluorescent molecule diffuses.
*** FRAP intentionally uses photobleaching to blast out a region of the cell; there's still background photobleaching on everything else, though, which corrupts the signal you get out.
Friday, November 20, 2015
Macarons, Gun Purchasing, and Refugees
Today I Learned:
1) ...what a macaron is. They're really cute little cookies!
2) ...what's required to buy a gun in California*. You have to have documentation proving that you are a US citizen and a resident of California. There's also a 10-day wait period between purchasing the gun and acquiring it, which I assume is to give very angry people a chance to simmer down after deciding they really need a gun?
* No, I didn't buy one.
3) ...what's required to move to the US as a refugee. Firstly, a refugee has to have "fled from his or her home country and cannot return because he or she has a well-founded fear of persecution based on religion, race, nationality, political opinion or membership in a particular social group". If you think you qualify, you can register with the United Nations High Commissioner for Refugees (UNHCR). If the UNHCR thinks a potential refugee meets the appropriate criteria, then they can refer him or her to the US Resettlement Program (USRP). The USRP maintains nine Resettlement Support Centers (RSCs) around the world. The RSCs receive and process refugee requests. Refugees awaiting approval undergo personal interviews, security and background checks, and a medical examination (so they don't bring contagious diseases into the country). The process typically takes 18 to 24 months. I also learned that of the refugees that are accepted worldwide, about half of them are accepted by the US. That's also a very small fraction of the total number of people who request refugee status.
1) ...what a macaron is. They're really cute little cookies!
2) ...what's required to buy a gun in California*. You have to have documentation proving that you are a US citizen and a resident of California. There's also a 10-day wait period between purchasing the gun and acquiring it, which I assume is to give very angry people a chance to simmer down after deciding they really need a gun?
* No, I didn't buy one.
3) ...what's required to move to the US as a refugee. Firstly, a refugee has to have "fled from his or her home country and cannot return because he or she has a well-founded fear of persecution based on religion, race, nationality, political opinion or membership in a particular social group". If you think you qualify, you can register with the United Nations High Commissioner for Refugees (UNHCR). If the UNHCR thinks a potential refugee meets the appropriate criteria, then they can refer him or her to the US Resettlement Program (USRP). The USRP maintains nine Resettlement Support Centers (RSCs) around the world. The RSCs receive and process refugee requests. Refugees awaiting approval undergo personal interviews, security and background checks, and a medical examination (so they don't bring contagious diseases into the country). The process typically takes 18 to 24 months. I also learned that of the refugees that are accepted worldwide, about half of them are accepted by the US. That's also a very small fraction of the total number of people who request refugee status.
Thursday, November 19, 2015
Ciprofloxacin, Drones, and Amino Acids... In Space!
Today I Learned:
1) Ciprofloxacin is one of the stronger, cheaper antibiotics on the market. It's a little unusual in its mechanism of action -- most antibiotics I know of work by either inhibiting synthesis of the bacterial cell wall or by blocking bacterial ribosomes, but ciprofloxacin works by inhibiting several bacterial topoisomerases and gyrases, which are important for DNA replication (they help unwind DNA and relieve torsional stress from the unwinding).
Ciprofloxacin also, rarely, has a couple of nasty side effects. In addition to the usual sort of stuff (nausea, abnormal liver function, muscle weakness, etc), ciprofloxacin is associated with an increased risk of tendon rupture. It apparently weakens several kinds of connective tissue important for holding tendons together. It's a rare side effect, so it's still used pretty commonly, but it's not supposed to be given to anyone with known tendon problems or to the elderly.
Ciprofloxacin may also cause retinal detachment, which is just as nasty as it sounds (evidence of retinal detachment caused by ciprofloxacin: http://ift.tt/1MYk1vR). However, a Danish study tried to replicate the finding and failed: http://ift.tt/217bwt0. The authors claim that they can rule out any more than a 3-fold increase in risk of retinal detachment due to small sample size (they looked at about 500 cases of retinal detachment, out of a total of around 660,000 cases of ciprofloxacin use), which corresponds to "in the worst-case scenario [...] no more than 11 additional cases of retinal detachment per 1,000,000 treatment episodes". So if it does cause retinal detachment, it's *quite* rare.
2) ...a little bit about drone design. For one thing, there are tricopters as well as quadcopters. Also, off-the-shelf drones primarily use PID controllers. Also, control sticks for flying off-the-shelf drones (and probably other remote-control aircraft) typically use something called "expo", which is an exponential mapping between distance-from-the-center-of-the-control-pad-to-the-stick to the size of the effect on the drone. This is so you can make fine adjustments near the center of the stick-range while still allowing large changes with big stick movements.
3) ...a bit about how we know about amino acids* in space. Incidentally, there are amino acids in space, in surprising abundance. We know this from at least two independent sources. Firstly, astronomers in 1994 found spectral lines for the amino acid glycine in three nebulae, and I believe other experiments have found similar spectral data in other gas clouds.
Secondly, we've found complex amino acid mixtures inside fresh meteorites, which includes many amino acids not found on Earth. Moreover, in 2009 NASA's Stardust mission brought home dust samples from the comet Wild 2, which contained detectable amounts of glycine (contamination was ruled out by the glycine's radiological signature -- it had more Carbon 13 than Earth glycine).
*Amino acids == the monomers that make up proteins, which are the complex molecules that perform most biological functions.
1) Ciprofloxacin is one of the stronger, cheaper antibiotics on the market. It's a little unusual in its mechanism of action -- most antibiotics I know of work by either inhibiting synthesis of the bacterial cell wall or by blocking bacterial ribosomes, but ciprofloxacin works by inhibiting several bacterial topoisomerases and gyrases, which are important for DNA replication (they help unwind DNA and relieve torsional stress from the unwinding).
Ciprofloxacin also, rarely, has a couple of nasty side effects. In addition to the usual sort of stuff (nausea, abnormal liver function, muscle weakness, etc), ciprofloxacin is associated with an increased risk of tendon rupture. It apparently weakens several kinds of connective tissue important for holding tendons together. It's a rare side effect, so it's still used pretty commonly, but it's not supposed to be given to anyone with known tendon problems or to the elderly.
Ciprofloxacin may also cause retinal detachment, which is just as nasty as it sounds (evidence of retinal detachment caused by ciprofloxacin: http://ift.tt/1MYk1vR). However, a Danish study tried to replicate the finding and failed: http://ift.tt/217bwt0. The authors claim that they can rule out any more than a 3-fold increase in risk of retinal detachment due to small sample size (they looked at about 500 cases of retinal detachment, out of a total of around 660,000 cases of ciprofloxacin use), which corresponds to "in the worst-case scenario [...] no more than 11 additional cases of retinal detachment per 1,000,000 treatment episodes". So if it does cause retinal detachment, it's *quite* rare.
2) ...a little bit about drone design. For one thing, there are tricopters as well as quadcopters. Also, off-the-shelf drones primarily use PID controllers. Also, control sticks for flying off-the-shelf drones (and probably other remote-control aircraft) typically use something called "expo", which is an exponential mapping between distance-from-the-center-of-the-control-pad-to-the-stick to the size of the effect on the drone. This is so you can make fine adjustments near the center of the stick-range while still allowing large changes with big stick movements.
3) ...a bit about how we know about amino acids* in space. Incidentally, there are amino acids in space, in surprising abundance. We know this from at least two independent sources. Firstly, astronomers in 1994 found spectral lines for the amino acid glycine in three nebulae, and I believe other experiments have found similar spectral data in other gas clouds.
Secondly, we've found complex amino acid mixtures inside fresh meteorites, which includes many amino acids not found on Earth. Moreover, in 2009 NASA's Stardust mission brought home dust samples from the comet Wild 2, which contained detectable amounts of glycine (contamination was ruled out by the glycine's radiological signature -- it had more Carbon 13 than Earth glycine).
*Amino acids == the monomers that make up proteins, which are the complex molecules that perform most biological functions.
A Caste System, Green's Functions, and The Beta Distribution
Today I Learned:
1) There's a species of ant with a really strange caste system. They have queens and workers, just like most ant species, but they are maintained in separate genetic lineages. Queens can produce either queen or worker offspring, but only if they mate with a male of the appropriate line. If the queen only mates with worker-line males, then all of her children are workers or queen-line males. If she only mates with queen-line males, then all of her offspring are queens (and the colony usually dies). How this system came to be is of some debate right now.
2) A Green's function is the impulse response of a bounded linear dynamical system with specified boundary conditions.
Let me break that down a bit. First, an "impulse", in this particular mathematical context, is a function that is zero everywhere except one value, at which it is one. If you think about a digital time signal, an impulse is a flat zero signal with a single spike at one time. There are a couple of cool things about impulses. Firstly, they're simple. They're, like, as simple as a function can get without being uniform. Secondly, they can often by produced experimentally, at least to an approximation, relatively easily. This is especially true in signal processing, where impulses are used all the time. Finally, you can define any function in terms of some number of impulses with various locations and strengths.
A dynamical system is a set of differential equations -- that means it's a system where you can define how quickly each variable changes in terms of the values of each variable at that time. Being bounded and linear and having specified boundary conditions means the system is "nice" in some way.
So, a Green's function is simply what a function does when you spike in an impulse. For instance, you could imagine taking a pool of perfectly still water and instantaneously pulling the surface up by a foot at one spot. The resulting pattern of waves and ripples and splashes would be the Green function for that pool. The nice thing about a Green function is that if you know the Green function for a system, you can add together those functions just like you can add together impulses -- the Green function for two impulses is just the sum of the two impulses' Green function. So once you know the Green function for a system, you know the behavior of the system for all possible starting conditions (with whatever *boundary* conditions the Green function is defined for).
3) The beta distribution, with properly chosen parameters, is a good stand-in for a Gaussian when you only have probabilities defined on the range [0,1].
1) There's a species of ant with a really strange caste system. They have queens and workers, just like most ant species, but they are maintained in separate genetic lineages. Queens can produce either queen or worker offspring, but only if they mate with a male of the appropriate line. If the queen only mates with worker-line males, then all of her children are workers or queen-line males. If she only mates with queen-line males, then all of her offspring are queens (and the colony usually dies). How this system came to be is of some debate right now.
2) A Green's function is the impulse response of a bounded linear dynamical system with specified boundary conditions.
Let me break that down a bit. First, an "impulse", in this particular mathematical context, is a function that is zero everywhere except one value, at which it is one. If you think about a digital time signal, an impulse is a flat zero signal with a single spike at one time. There are a couple of cool things about impulses. Firstly, they're simple. They're, like, as simple as a function can get without being uniform. Secondly, they can often by produced experimentally, at least to an approximation, relatively easily. This is especially true in signal processing, where impulses are used all the time. Finally, you can define any function in terms of some number of impulses with various locations and strengths.
A dynamical system is a set of differential equations -- that means it's a system where you can define how quickly each variable changes in terms of the values of each variable at that time. Being bounded and linear and having specified boundary conditions means the system is "nice" in some way.
So, a Green's function is simply what a function does when you spike in an impulse. For instance, you could imagine taking a pool of perfectly still water and instantaneously pulling the surface up by a foot at one spot. The resulting pattern of waves and ripples and splashes would be the Green function for that pool. The nice thing about a Green function is that if you know the Green function for a system, you can add together those functions just like you can add together impulses -- the Green function for two impulses is just the sum of the two impulses' Green function. So once you know the Green function for a system, you know the behavior of the system for all possible starting conditions (with whatever *boundary* conditions the Green function is defined for).
3) The beta distribution, with properly chosen parameters, is a good stand-in for a Gaussian when you only have probabilities defined on the range [0,1].
Tuesday, November 17, 2015
Noise Filters, English Weirdness, and Forking Ice Cream
Today I Learned:
1) Something to watch out for when filtering noise in time series data using a bandpass filter -- if you put data through a Fourier transform, cut off high or low frequencies, then transform it back, if you don't use phase information in the inverse transform, you force the signal to start at 0, which can shift or distort your data a bit. This is particularly noticeable if your total time isn't much bigger than the wavelength of the dominant frequency in your data.
2) English is the only language whose present-tense verbs only require a special ending in the third-person singular -- I fish, you fish, they fish, but he/she fishes. English is also highly unusual in its use of the word "do", and is the only Indo-European language that doesn't use gendered nouns. I've known English was weird for a long time, but I didn't really notice *how* weird.
3) It is very much possible to eat ice cream with a fork. I'm about to find out what happens when you get to the end of the ice cream. I imagine you start drinking.
1) Something to watch out for when filtering noise in time series data using a bandpass filter -- if you put data through a Fourier transform, cut off high or low frequencies, then transform it back, if you don't use phase information in the inverse transform, you force the signal to start at 0, which can shift or distort your data a bit. This is particularly noticeable if your total time isn't much bigger than the wavelength of the dominant frequency in your data.
2) English is the only language whose present-tense verbs only require a special ending in the third-person singular -- I fish, you fish, they fish, but he/she fishes. English is also highly unusual in its use of the word "do", and is the only Indo-European language that doesn't use gendered nouns. I've known English was weird for a long time, but I didn't really notice *how* weird.
3) It is very much possible to eat ice cream with a fork. I'm about to find out what happens when you get to the end of the ice cream. I imagine you start drinking.
Toxic 3D Prints, Old-School Graphics, and Mud Microbes
Today I Learned:
1) 3D printed parts made using stereolithography may be toxic. They're certainly toxic to zebrafish embryos. Embryos are pretty sensitive, though....
Stereolithographic 3D printing is the version of 3D printing that draws a piece out of a bath of liquid plastic monomer, using some sort of light to cure (polymerize) the monomers into hard plastic. The problem seems to be that the monomer solution is toxic (this has been known for a while) and the printing process doesn't completely polymerize the plastic -- additional curing of a piece for a while with UV light removes the toxicity effect.
Deposition-based 3D printing, which as far as I know is more common (it's what we have in our apartment), uses pre-polymerized plastic that's heated and cooled, so it's not toxic by this mechanism.
2) ...some of the tricks used in old-school (1970s and 1980s) gaming computers to make the graphics work. I had no idea how crunched those old graphics systems were. A typical screen resolution at the time was 320x200. Paltry, I know, but that adds up to 64k pixels. That was at a time when most computers had 16kb or 32kb of RAM -- and no dedicated video RAM! So storing a byte's worth of data for each pixel was totally out of the question. Even black-and-white graphics, with one bit per pixel, would chew up beetween half and a quarter of the RAM on most systems. That's pretty intense.
I won't go into the details of how to get around this issue here, but you can learn more in this guy's video: https://www.youtube.com/watch?v=Tfh0ytz8S0k.
Thanks to Chris Lennox for linking me to this!
3) ...about some really cool mud microbes! Seriously, really cool stuff. I heard a lecture by a guy who studies microbial communities in the surface layers of mud. A lot of the microbiota of mud surfaces are sulfur-metabolizing microbes. Instead of burning metabolizing complex organic compounds like glucose for energy, they do this awesome thing where they store elemental sulfur in solid chunks inside their cells, then burn it with oxygen to generate ATP. Because of this, sulfur and oxygen are really important for these microbes.
Mud has this interesting property where oxygen diffuses in from the top, forming an oxygen gradient, while there's usually a sulfur source near the bottom, which diffuses up to form an opposing gradient. The guy I heard talk today studies microbes that live at a sort of boundary layer where there's a good balance of oxygen and sulfur.
The lecturer talked specifically about two species, a bacteria called Thiovulum majus and a cilliate called Uronemella. Both species build sheets of sticky polysaccharides called "veils", to which they tether themselves with a similar substance in large colonies. Both species also have a ton of flagella, which they use to push themselves out until they strain against their tether. Once at their tethers' ends, the microbes use their flagella to flow water past themselves, drawing in oxygen-rich water from above, kind of like the way rotifers and some hydra stream food-rich water to filter-feed more efficiently.
Uronemella isn't particularly unusual as far as Eukaryotes go. T. majus is a different story. First off, it's a massive bacteria at about 10 microns long (that's closer to a human skin cell than to a typical bacterial cell; there are other microbes which the lecturer mentioned in passing that grow to hundreds of microns long(!), which lets them have one end in oxygen-rich mud and the other in sulfur-rich mud). It also has *way* more flagella than a typical bacteria, averaging around 50 flagella per cell. These flagella are chemically and structurally identical to a typical bacterial flagella, but their sheer quantity lets T. majus exert 40 pN of force on the surrounding water -- much more than most bacteria can exert, and comparable to Uronemella.
T. majus also has a highly unusual chemotaxis system (that is, control that lets it move towards desirable chemicals). Most bacteria use a variant of run-and-tumble chemotaxis, where the bacteria switch between spinning in circles and swimming in a straight line, and spend more time spinning when they're in a high concentration of something they like. T. majus doesn't do this. Instead, it turns smoothly to move up desirable gradients. We don't know how. The speaker speculated that T. majus might be big enough to simply sample the chemical at either end of the cell and determine the direction of the gradient, but it was only mentioned in passing.
Anyway, both Uronemella and T. majus form these big (visible to the naked eye) veils and, as a community, pull in oxygen-rich water from above and consume the oxygen. In a test-tube environment with oxygenated air at the top and a sulfur source at the bottom, they will form a veil, then move their way up the test tube, depleting oxygen as they go. It's kind of like lighting a match at one end of a tube filled with propane -- you get a traveling wave of flame, consuming the propane as it goes. Except instead of converting propane to CO2 and H2O, the microbes convert O2 and sulfur (which they seem to have in excess) into more microbes.
There were more interesting things about T. majus and Uronemella, but this post is getting rather lengthy. Perhaps the most important thing I learned from this lecture was the following general principle: whenever you see life building sheets or films, especially in water, it may be forming sheets at a gradient boundary of something important. I'll have to keep an eye out for more examples (or counterexamples) of this.
You can read more about T. majus and Uronemella here: http://tinyurl.com/pasuobp. I recommend looking through the figures and table if you can get access; don't skip Figure 9, which shows dimples in the veils caused by turbulent forces.
1) 3D printed parts made using stereolithography may be toxic. They're certainly toxic to zebrafish embryos. Embryos are pretty sensitive, though....
Stereolithographic 3D printing is the version of 3D printing that draws a piece out of a bath of liquid plastic monomer, using some sort of light to cure (polymerize) the monomers into hard plastic. The problem seems to be that the monomer solution is toxic (this has been known for a while) and the printing process doesn't completely polymerize the plastic -- additional curing of a piece for a while with UV light removes the toxicity effect.
Deposition-based 3D printing, which as far as I know is more common (it's what we have in our apartment), uses pre-polymerized plastic that's heated and cooled, so it's not toxic by this mechanism.
2) ...some of the tricks used in old-school (1970s and 1980s) gaming computers to make the graphics work. I had no idea how crunched those old graphics systems were. A typical screen resolution at the time was 320x200. Paltry, I know, but that adds up to 64k pixels. That was at a time when most computers had 16kb or 32kb of RAM -- and no dedicated video RAM! So storing a byte's worth of data for each pixel was totally out of the question. Even black-and-white graphics, with one bit per pixel, would chew up beetween half and a quarter of the RAM on most systems. That's pretty intense.
I won't go into the details of how to get around this issue here, but you can learn more in this guy's video: https://www.youtube.com/watch?v=Tfh0ytz8S0k.
Thanks to Chris Lennox for linking me to this!
3) ...about some really cool mud microbes! Seriously, really cool stuff. I heard a lecture by a guy who studies microbial communities in the surface layers of mud. A lot of the microbiota of mud surfaces are sulfur-metabolizing microbes. Instead of burning metabolizing complex organic compounds like glucose for energy, they do this awesome thing where they store elemental sulfur in solid chunks inside their cells, then burn it with oxygen to generate ATP. Because of this, sulfur and oxygen are really important for these microbes.
Mud has this interesting property where oxygen diffuses in from the top, forming an oxygen gradient, while there's usually a sulfur source near the bottom, which diffuses up to form an opposing gradient. The guy I heard talk today studies microbes that live at a sort of boundary layer where there's a good balance of oxygen and sulfur.
The lecturer talked specifically about two species, a bacteria called Thiovulum majus and a cilliate called Uronemella. Both species build sheets of sticky polysaccharides called "veils", to which they tether themselves with a similar substance in large colonies. Both species also have a ton of flagella, which they use to push themselves out until they strain against their tether. Once at their tethers' ends, the microbes use their flagella to flow water past themselves, drawing in oxygen-rich water from above, kind of like the way rotifers and some hydra stream food-rich water to filter-feed more efficiently.
Uronemella isn't particularly unusual as far as Eukaryotes go. T. majus is a different story. First off, it's a massive bacteria at about 10 microns long (that's closer to a human skin cell than to a typical bacterial cell; there are other microbes which the lecturer mentioned in passing that grow to hundreds of microns long(!), which lets them have one end in oxygen-rich mud and the other in sulfur-rich mud). It also has *way* more flagella than a typical bacteria, averaging around 50 flagella per cell. These flagella are chemically and structurally identical to a typical bacterial flagella, but their sheer quantity lets T. majus exert 40 pN of force on the surrounding water -- much more than most bacteria can exert, and comparable to Uronemella.
T. majus also has a highly unusual chemotaxis system (that is, control that lets it move towards desirable chemicals). Most bacteria use a variant of run-and-tumble chemotaxis, where the bacteria switch between spinning in circles and swimming in a straight line, and spend more time spinning when they're in a high concentration of something they like. T. majus doesn't do this. Instead, it turns smoothly to move up desirable gradients. We don't know how. The speaker speculated that T. majus might be big enough to simply sample the chemical at either end of the cell and determine the direction of the gradient, but it was only mentioned in passing.
Anyway, both Uronemella and T. majus form these big (visible to the naked eye) veils and, as a community, pull in oxygen-rich water from above and consume the oxygen. In a test-tube environment with oxygenated air at the top and a sulfur source at the bottom, they will form a veil, then move their way up the test tube, depleting oxygen as they go. It's kind of like lighting a match at one end of a tube filled with propane -- you get a traveling wave of flame, consuming the propane as it goes. Except instead of converting propane to CO2 and H2O, the microbes convert O2 and sulfur (which they seem to have in excess) into more microbes.
There were more interesting things about T. majus and Uronemella, but this post is getting rather lengthy. Perhaps the most important thing I learned from this lecture was the following general principle: whenever you see life building sheets or films, especially in water, it may be forming sheets at a gradient boundary of something important. I'll have to keep an eye out for more examples (or counterexamples) of this.
You can read more about T. majus and Uronemella here: http://tinyurl.com/pasuobp. I recommend looking through the figures and table if you can get access; don't skip Figure 9, which shows dimples in the veils caused by turbulent forces.
Monday, November 16, 2015
A Game Of Pills, Shoestring Fries, and Land Clumps
Today I Learned:
1) The answer to the following riddle:
A Very Important Man goes to the doctor one day. He discovers he has a deadly terminal illness that will kill him soon. Luckily, the doctor has a medicine that will keep him alive as long as he eats *exactly* one pill of type A and one pill of type B every day. The doctor gives him a bunch of A and a smaller supply of B, and tells him to pick up more B when it's about to run out.
The man then does something remarkably stupid and goes out to his isolated cabin in the woods for a week, with exactly 7 B pills remaining. He tells his friend to bring him more B pills at the end of 7 weeks, so that he won't die on the 8th day, but he otherwise has no way of contacting the outside world or getting more B pills. On the first day, the man drops two B pills and an A pill on the ground, and he loses track of which one is which. The two types of pills look identical and cannot be distinguished by experiment (except by trying a pair of pills and seeing if he dies or not...). Again, the man has a large supply of A pills, 5 B pills that he knows are B pills, and 3 pills of which exactly two are B pills. How can he survive the week with 100% probability?
As usual with these riddles, it may appear at first that this is an unsolvable problem. It is not. The answer is not ridiculously complex. See if you can figure it out. (Please don't spoil the answer in the comments!)
Kudos to Clare Hayes for telling me the riddle; kudos to Robert Johnson for solving it.
2) Shoestring fries are surprisingly close to actual shoe strings in diameter.
3) In a typical Magic: The Gathering* deck with 23 lands, if you shuffle well, on average, the largest clump of lands you'll see is about 4, according to Monte Carlo simulations. Here's some code that you can try, as long as you have numpy and matplotlib (or Seaborn, if you have it and comment in the appropriate lines). This is also a nice little coding challenge -- if you want a 10-20 minute code practice run, try writing one yourself! (Bonus points if you write it in Haskell)
import numpy as np
from matplotlib import pyplot as plt
#import seaborn as sns
n_trials = 10000
max_clump_sizes = -1*np.ones(n_trials)
# Run a bunch of trials
for i in range(n_trials):
n_lands = 23
n_nonlands = 37
# Lands will be represented as ones, non-lands as zero. Luckily,
# Numpy has a function for shuffling.
cards = np.concatenate([np.ones(n_lands), np.zeros(n_nonlands)])
np.random.shuffle(cards)
# To find clumps, split the array at every zero element. Yeah, this
# probably isn't efficient, but I'm trusting in Numpy to do the
# right thing. Besides, this is a Facebook post, I'm trying to keep the
# code short.
clumps = np.split(cards, np.where(cards == 0)[0])
max_clump = max(map(len, clumps))
max_clump_sizes[i] = max_clump - 1 # Split leaves a 0 in each stack.
plt.cla()
# To visualize with seaborn
#sns.distplot(max_clump_sizes, kde=False)
# To visualize with matplotlib
plt.hist(max_clump_sizes, bins=max(max_clump_sizes)-1)
plt.xlim([0, max(max_clump_sizes)])
plt.show()
print("Average maximum land clump size: " + str(np.mean(max_clump_sizes)))
(Note: the whitespace formatting on this blog is kind of weird -- you may have to re-write the tabbing on the for loop to get this to work)
*for the uninitiated, in Magic: The Gathering, players build a deck of 60 cards, which they bring to games to play with. Land cards are a special type of card that produce resources which are used to play other (non-land) cards. As such, they are critical to gameplay, and it's very important how many lands vs non-lands a player draws during the course of a game. Thus, distributions of land clumpiness are of interest to a Magic player.
1) The answer to the following riddle:
A Very Important Man goes to the doctor one day. He discovers he has a deadly terminal illness that will kill him soon. Luckily, the doctor has a medicine that will keep him alive as long as he eats *exactly* one pill of type A and one pill of type B every day. The doctor gives him a bunch of A and a smaller supply of B, and tells him to pick up more B when it's about to run out.
The man then does something remarkably stupid and goes out to his isolated cabin in the woods for a week, with exactly 7 B pills remaining. He tells his friend to bring him more B pills at the end of 7 weeks, so that he won't die on the 8th day, but he otherwise has no way of contacting the outside world or getting more B pills. On the first day, the man drops two B pills and an A pill on the ground, and he loses track of which one is which. The two types of pills look identical and cannot be distinguished by experiment (except by trying a pair of pills and seeing if he dies or not...). Again, the man has a large supply of A pills, 5 B pills that he knows are B pills, and 3 pills of which exactly two are B pills. How can he survive the week with 100% probability?
As usual with these riddles, it may appear at first that this is an unsolvable problem. It is not. The answer is not ridiculously complex. See if you can figure it out. (Please don't spoil the answer in the comments!)
Kudos to Clare Hayes for telling me the riddle; kudos to Robert Johnson for solving it.
2) Shoestring fries are surprisingly close to actual shoe strings in diameter.
3) In a typical Magic: The Gathering* deck with 23 lands, if you shuffle well, on average, the largest clump of lands you'll see is about 4, according to Monte Carlo simulations. Here's some code that you can try, as long as you have numpy and matplotlib (or Seaborn, if you have it and comment in the appropriate lines). This is also a nice little coding challenge -- if you want a 10-20 minute code practice run, try writing one yourself! (Bonus points if you write it in Haskell)
import numpy as np
from matplotlib import pyplot as plt
#import seaborn as sns
n_trials = 10000
max_clump_sizes = -1*np.ones(n_trials)
# Run a bunch of trials
for i in range(n_trials):
n_lands = 23
n_nonlands = 37
# Lands will be represented as ones, non-lands as zero. Luckily,
# Numpy has a function for shuffling.
cards = np.concatenate([np.ones(n_lands), np.zeros(n_nonlands)])
np.random.shuffle(cards)
# To find clumps, split the array at every zero element. Yeah, this
# probably isn't efficient, but I'm trusting in Numpy to do the
# right thing. Besides, this is a Facebook post, I'm trying to keep the
# code short.
clumps = np.split(cards, np.where(cards == 0)[0])
max_clump = max(map(len, clumps))
max_clump_sizes[i] = max_clump - 1 # Split leaves a 0 in each stack.
plt.cla()
# To visualize with seaborn
#sns.distplot(max_clump_sizes, kde=False)
# To visualize with matplotlib
plt.hist(max_clump_sizes, bins=max(max_clump_sizes)-1)
plt.xlim([0, max(max_clump_sizes)])
plt.show()
print("Average maximum land clump size: " + str(np.mean(max_clump_sizes)))
(Note: the whitespace formatting on this blog is kind of weird -- you may have to re-write the tabbing on the for loop to get this to work)
*for the uninitiated, in Magic: The Gathering, players build a deck of 60 cards, which they bring to games to play with. Land cards are a special type of card that produce resources which are used to play other (non-land) cards. As such, they are critical to gameplay, and it's very important how many lands vs non-lands a player draws during the course of a game. Thus, distributions of land clumpiness are of interest to a Magic player.
Sunday, November 15, 2015
Sumlogexp, Sushi Cutting, and PTMCMC Performance
Today I Learned:
1) Numpy has a special function for calculating the log of the sum of exponentials, which is a quite numerically unstable algorithm if done naively.
2) When cutting sushi, it does indeed seem to help if you wet the blade first.
3) Parallel Tempered MCMC takes a *really* long time to run... much longer than I would have expected from a simple description of the algorithm. Specifically, it calls the objective function about an order of magnitude more frequently than I expected. =\
1) Numpy has a special function for calculating the log of the sum of exponentials, which is a quite numerically unstable algorithm if done naively.
2) When cutting sushi, it does indeed seem to help if you wet the blade first.
3) Parallel Tempered MCMC takes a *really* long time to run... much longer than I would have expected from a simple description of the algorithm. Specifically, it calls the objective function about an order of magnitude more frequently than I expected. =\
Friday, November 13, 2015
Unicode, RNAse and DNA, and the Mac OS 9 Graphing Calculator
Today I Learned:
1) ...so I was thinking about unicode, and how big it is, and I did some back-of-the-envelope calculations to see just how big the standard really is. With some estimation, guesswork, and order-of-magnitude roundoffs, I determined that if every star in our galaxy was inhabited by a species with human-like intelligence, and every single one of those species used symbols with similar complexity and diversity to humans, then a 64-bit unicode standard would comfortably hold every single symbol in the galaxy.
...then I read up on Unicode, and discovered I was totally wrong. For one thing, there is no 64-bit Unicode -- UTF-32 is the biggest standard, and it's rarely used because it's bulky and inefficient compared to UTF-8 and UTF-16. Also, Unicode isn't a... simple mapping of binary to characters. The standard is organized into 17 planes (0 is the Basic Multilingual Plane, and 1-16 are the Supplemental Planes or "astral planes"), each of which defines 65,536 symbols. After subtracting out surrogates, non-characters, and code points reserved for private use, that leaves 974,530 possible points, of which about 10% are currently defined. That 10% very comfortably includes all modern languages, and some ancient heiroglyphics and cuniform languages as well. The majority of defined Unicode is taken up by Chinese (technically "CJK Unified Ideographs"), which actually surprised me -- I assumed there would be at least five or ten more languages of similar symbolic complexity. I was wrong.
(Another fun fact: Chinese has something over 50,000 characters, with about 20,000 in modern use. That's surprisingly close to my original back-of-the-envelope 70,000-character estimate (definitely more than 5,000 characters; definitely less than a million characters; roughly sqrt{5,000 * 1,000,000} ~ 70,000))
2) RNase also digesting DNA isn't just a story people tell on the internet. It happens. Confirmed with plasmid DNA with all the adequate controls.
3) ...about the story of Mac OS 9's Graphing Calculator program. You can read about it here: http://ift.tt/s4Nt2U. It's a great story, but I'm really unsure what I think about it. Or what I feel about it. How do *you* feel about it?
1) ...so I was thinking about unicode, and how big it is, and I did some back-of-the-envelope calculations to see just how big the standard really is. With some estimation, guesswork, and order-of-magnitude roundoffs, I determined that if every star in our galaxy was inhabited by a species with human-like intelligence, and every single one of those species used symbols with similar complexity and diversity to humans, then a 64-bit unicode standard would comfortably hold every single symbol in the galaxy.
...then I read up on Unicode, and discovered I was totally wrong. For one thing, there is no 64-bit Unicode -- UTF-32 is the biggest standard, and it's rarely used because it's bulky and inefficient compared to UTF-8 and UTF-16. Also, Unicode isn't a... simple mapping of binary to characters. The standard is organized into 17 planes (0 is the Basic Multilingual Plane, and 1-16 are the Supplemental Planes or "astral planes"), each of which defines 65,536 symbols. After subtracting out surrogates, non-characters, and code points reserved for private use, that leaves 974,530 possible points, of which about 10% are currently defined. That 10% very comfortably includes all modern languages, and some ancient heiroglyphics and cuniform languages as well. The majority of defined Unicode is taken up by Chinese (technically "CJK Unified Ideographs"), which actually surprised me -- I assumed there would be at least five or ten more languages of similar symbolic complexity. I was wrong.
(Another fun fact: Chinese has something over 50,000 characters, with about 20,000 in modern use. That's surprisingly close to my original back-of-the-envelope 70,000-character estimate (definitely more than 5,000 characters; definitely less than a million characters; roughly sqrt{5,000 * 1,000,000} ~ 70,000))
2) RNase also digesting DNA isn't just a story people tell on the internet. It happens. Confirmed with plasmid DNA with all the adequate controls.
3) ...about the story of Mac OS 9's Graphing Calculator program. You can read about it here: http://ift.tt/s4Nt2U. It's a great story, but I'm really unsure what I think about it. Or what I feel about it. How do *you* feel about it?
Thursday, November 12, 2015
Cool Case, RNases, and Indian Food
Today I Learned:
1) ...what the inside of a Dell Precision 470 looks like. One of the lab computers stopped working and gave a hardware error, so I and a colleague took it apart. It has a really cool case -- it's held closed by a latch, so there're no screws involved, and the whole front and side hinge out (http://ift.tt/1WVyePS). The big green box is an assembly that shunts air off the processor heatsink and out the back. The power supply sits *under* the rest of the computer, which makes it nicely balanced and keeps it out of the way. It was also the most remarkably clean desktop I've seen after multiple years of operation.
(incidentally, we think we traced the problem to one of the RAM slots. If we take out the second of two RAM sticks, it boots; if we move the second RAM to the first slot and keep the first RAM out, it boots; no other configurations seem to boot.)
2) ...the difference between RNase I and RNase A. Both are enzymes that specifically degrade single-stranded RNA. RNase A cleaves the RNA backbone at specific bases (I don't recall which), so it leaves behind small RNA fragments. It's also the one that's demonically difficult to inactivate -- it's the one that can be autoclaved and happily keep chewing up RNA. As far as I know, the only way to deal with it, short of ridiculous things like fire, is to extract it out with phenol-chloroform.
RNase I, on the other hand, chews up any ribonucleotide backbone bond, so it leaves only ribonucleotides as long as you let it digest for long enough. It's also inactivated by incubation at 70 C, which is nice for downstream applications.
3) Apparently the Indian food served in restaurants in the US is very much rich people food, traditionally speaking. Small sample size here, and India's a big place, so I'm sure this is massively overgeneralizing, BUT a friend of mine from India tells me that day-to-day Indian food is much more rice and beans, eaten for sustinance rather than enjoyment. Though that's changing recently? This is all very second-hand.
1) ...what the inside of a Dell Precision 470 looks like. One of the lab computers stopped working and gave a hardware error, so I and a colleague took it apart. It has a really cool case -- it's held closed by a latch, so there're no screws involved, and the whole front and side hinge out (http://ift.tt/1WVyePS). The big green box is an assembly that shunts air off the processor heatsink and out the back. The power supply sits *under* the rest of the computer, which makes it nicely balanced and keeps it out of the way. It was also the most remarkably clean desktop I've seen after multiple years of operation.
(incidentally, we think we traced the problem to one of the RAM slots. If we take out the second of two RAM sticks, it boots; if we move the second RAM to the first slot and keep the first RAM out, it boots; no other configurations seem to boot.)
2) ...the difference between RNase I and RNase A. Both are enzymes that specifically degrade single-stranded RNA. RNase A cleaves the RNA backbone at specific bases (I don't recall which), so it leaves behind small RNA fragments. It's also the one that's demonically difficult to inactivate -- it's the one that can be autoclaved and happily keep chewing up RNA. As far as I know, the only way to deal with it, short of ridiculous things like fire, is to extract it out with phenol-chloroform.
RNase I, on the other hand, chews up any ribonucleotide backbone bond, so it leaves only ribonucleotides as long as you let it digest for long enough. It's also inactivated by incubation at 70 C, which is nice for downstream applications.
3) Apparently the Indian food served in restaurants in the US is very much rich people food, traditionally speaking. Small sample size here, and India's a big place, so I'm sure this is massively overgeneralizing, BUT a friend of mine from India tells me that day-to-day Indian food is much more rice and beans, eaten for sustinance rather than enjoyment. Though that's changing recently? This is all very second-hand.
Wednesday, November 11, 2015
Cancer-Killing Diatoms, Slug, and Manipulate
Today I Learned:
1) ...about an article from this month's issue of Nature in which the authors genetically engineered diatoms to selectively deliver chemotheraputic drugs to cancer cells. The diatoms carry vesicles filled with the drugs, and they've been engineered to express an antibody to some cancer-specific membrane marker on their own membranes, causing them to localize to cancer cells and deliver the drugs pretty specifically. In an immune-compromised mouse model, they reduced cancer volumes by about half.
This is *decidedly not a game-changer* when it comes to cancer, but it does seem like a potentially useful incremental advance. It's not hard to imagine adding a diatom delivery vehicle on top of just about every existing chemotheraputic to make them more specific and, hopefully, more effective. Plus, it's a pretty creative use of diatoms, and I'm a sucker for anything with diatoms.
2) ...how the gene Slug got its name.
Our story begins with the genes Snai1 and Snai2. These are closely-related transcription factors important for early embryonic development in Drosophila and probably most elsewhere. The names are derived from some kind of structural information -- to be honest, I can't find the original etymology of the names, but "SNAI" stood for something related to the structure of the proteins. Then someone either noticed that "Snai1" looks a lot like "Snail" or misread it, published a paper about the "Snail" genes, and the name stuck.
What to call Snai2? Snaiz? It just doesn't have the same ring. Snai2, it turns out, is more or less Snai1 without a certain degradation tag. So kind of like a snail without a shell... call it Slug!
(For the record, yes, there's a Snai3, and it's called "Smuc". No, I don't know why.)
3) ...how to use Mathematica's "Manipulate" function! It's a pretty nifty function -- you can give it a statement (which can be a graph!!!), some variables, and ranges for those variables, and Mathematica spits out an interactive graphic with a slider for each variable. You can slide the slider around to whatever values you want, and it will show you how your statement changes in response!
1) ...about an article from this month's issue of Nature in which the authors genetically engineered diatoms to selectively deliver chemotheraputic drugs to cancer cells. The diatoms carry vesicles filled with the drugs, and they've been engineered to express an antibody to some cancer-specific membrane marker on their own membranes, causing them to localize to cancer cells and deliver the drugs pretty specifically. In an immune-compromised mouse model, they reduced cancer volumes by about half.
This is *decidedly not a game-changer* when it comes to cancer, but it does seem like a potentially useful incremental advance. It's not hard to imagine adding a diatom delivery vehicle on top of just about every existing chemotheraputic to make them more specific and, hopefully, more effective. Plus, it's a pretty creative use of diatoms, and I'm a sucker for anything with diatoms.
2) ...how the gene Slug got its name.
Our story begins with the genes Snai1 and Snai2. These are closely-related transcription factors important for early embryonic development in Drosophila and probably most elsewhere. The names are derived from some kind of structural information -- to be honest, I can't find the original etymology of the names, but "SNAI" stood for something related to the structure of the proteins. Then someone either noticed that "Snai1" looks a lot like "Snail" or misread it, published a paper about the "Snail" genes, and the name stuck.
What to call Snai2? Snaiz? It just doesn't have the same ring. Snai2, it turns out, is more or less Snai1 without a certain degradation tag. So kind of like a snail without a shell... call it Slug!
(For the record, yes, there's a Snai3, and it's called "Smuc". No, I don't know why.)
3) ...how to use Mathematica's "Manipulate" function! It's a pretty nifty function -- you can give it a statement (which can be a graph!!!), some variables, and ranges for those variables, and Mathematica spits out an interactive graphic with a slider for each variable. You can slide the slider around to whatever values you want, and it will show you how your statement changes in response!
Tuesday, November 10, 2015
Incinerators, Lily Crossbreeds, and Mystery Nucleic Acids
Today I Learned:
1) Trash incinerators are kind of awesome. Modern incinerators burn hot enough to reduce plastics and similar trash almost entirely into water and carbon dioxide, with trace amounts of NO2 and similar small molecules. Moreover, the heat is usually recaptured and used either directly for municipal heating or to produce electricity, and many incinerators are energy-positive.
In fact, a few places in the US and central Europe have a weird problem where their public waste system has quotas of trash they *have to produce* in order to generate electricity. This makes it rather difficult to recycle in these areas -- there's a lot of incentive to burn the recyclable materials instead.
2) Lily crossbreeding is apparently a big deal in the herbological community, and has been for thousands of years. There are, however, several varieties of lilies that have never been cross-breedable (sorry, I don't have their names). No matter what you do, the crossed seeds won't take.
Until now! Turns out that you *can* grow them, if you grow them on agar plates with the right hormones. Score one for science!
(Bonus plant-cross fact: You can buy a plant called a TomTato, which is a splice between a tomato plant and a potato plant. It grows tomatos on its stalks and potatos in its roots. It costs about 10£ (also learned how to type "£" on an American keyboard!).)
3) If you run a TX-TL reaction on a gel diluted about 100-fold, you can see clear bands at about 1.5 kb and 3 kb, plus a messy blob in the 0-500 bp range. My tentative hypothesis is that these are rRNA bands, though this begs the question of how those rRNAs get dissociated on a gel, or alternatively where the full ribosome falls....
1) Trash incinerators are kind of awesome. Modern incinerators burn hot enough to reduce plastics and similar trash almost entirely into water and carbon dioxide, with trace amounts of NO2 and similar small molecules. Moreover, the heat is usually recaptured and used either directly for municipal heating or to produce electricity, and many incinerators are energy-positive.
In fact, a few places in the US and central Europe have a weird problem where their public waste system has quotas of trash they *have to produce* in order to generate electricity. This makes it rather difficult to recycle in these areas -- there's a lot of incentive to burn the recyclable materials instead.
2) Lily crossbreeding is apparently a big deal in the herbological community, and has been for thousands of years. There are, however, several varieties of lilies that have never been cross-breedable (sorry, I don't have their names). No matter what you do, the crossed seeds won't take.
Until now! Turns out that you *can* grow them, if you grow them on agar plates with the right hormones. Score one for science!
(Bonus plant-cross fact: You can buy a plant called a TomTato, which is a splice between a tomato plant and a potato plant. It grows tomatos on its stalks and potatos in its roots. It costs about 10£ (also learned how to type "£" on an American keyboard!).)
3) If you run a TX-TL reaction on a gel diluted about 100-fold, you can see clear bands at about 1.5 kb and 3 kb, plus a messy blob in the 0-500 bp range. My tentative hypothesis is that these are rRNA bands, though this begs the question of how those rRNAs get dissociated on a gel, or alternatively where the full ribosome falls....
Monday, November 9, 2015
Temporal Divisions of Labor, Roman Beatniks, and Facebook Notifications
Today I Learned:
1) Many ants and other social insects (I'm going to just say "ant" as shorthand for "social insect") have something called a temporal division of labor. What that means is that over time, an individual ant will change what jobs they do.
Specifically, in almost every case, young ants perform tasks close to the eggs, near the center of the nest, and as they age they take on tasks farther and farther from the center of the nest. The oldest ants take on foraging rolls and spend most of their time completely outside the nest. One rather elegant theory to explain the temporal division of labor is the "centrifugal theory", which says that ants start doing tasks wherever they're hatched, and sort of diffuse away as they age by random motion. Ants switch behaviors rather readily, so the idea is that they get bumped around from task to task, and the net bumping moves them farther and farther from their place of birth in more or less the same way molecular diffusion makes dye spread in water.
It's an elegant theory, but one that is falsified by a number of observations and experimental findings (for instance, there's at least one species of ant where the ants pupate and hatch far from the eggs, but still begin life by heading straight for the egg chambers and taking care of the eggs there). Indeed, in honeybees, there is a known program of hormone-controlled aging that causes bees to switch tasks over time (another little TIL: mankind has known that bees age, and that foraging bees are the eldest bees, since at least Aristotle). So for whatever reason, it seems that social insects are genetically programmed to take on tasks farther and farther from the center of the nest as they age.
2) Julius Ceasar, the first Emperor of Rome, was something of a counterculture figure of his time. Espeically early in his political career, Ceasar wore very unusual clothes -- for instance, he wore his toga loose-belted, with long sleeves. He was kind of the popular spearhead of a whole movement of antitraditionalism in the Republic.
Others of his generation did strange things like wearing goatees and togas made of gauze-like fabric, or holding parties where attendees would dance naked on the tables. They wrote poetry and literature that didn't fit old Grecian forms, and they espoused living for the moment rather than for service to the community. It was quite an interesting time to be a Roman, from the sound of it.
3) Facebook will not notify you if a post appears with your name in it, but not tagged. Thanks to Meaghan Sullivan for unwittingly testing this for me!
1) Many ants and other social insects (I'm going to just say "ant" as shorthand for "social insect") have something called a temporal division of labor. What that means is that over time, an individual ant will change what jobs they do.
Specifically, in almost every case, young ants perform tasks close to the eggs, near the center of the nest, and as they age they take on tasks farther and farther from the center of the nest. The oldest ants take on foraging rolls and spend most of their time completely outside the nest. One rather elegant theory to explain the temporal division of labor is the "centrifugal theory", which says that ants start doing tasks wherever they're hatched, and sort of diffuse away as they age by random motion. Ants switch behaviors rather readily, so the idea is that they get bumped around from task to task, and the net bumping moves them farther and farther from their place of birth in more or less the same way molecular diffusion makes dye spread in water.
It's an elegant theory, but one that is falsified by a number of observations and experimental findings (for instance, there's at least one species of ant where the ants pupate and hatch far from the eggs, but still begin life by heading straight for the egg chambers and taking care of the eggs there). Indeed, in honeybees, there is a known program of hormone-controlled aging that causes bees to switch tasks over time (another little TIL: mankind has known that bees age, and that foraging bees are the eldest bees, since at least Aristotle). So for whatever reason, it seems that social insects are genetically programmed to take on tasks farther and farther from the center of the nest as they age.
2) Julius Ceasar, the first Emperor of Rome, was something of a counterculture figure of his time. Espeically early in his political career, Ceasar wore very unusual clothes -- for instance, he wore his toga loose-belted, with long sleeves. He was kind of the popular spearhead of a whole movement of antitraditionalism in the Republic.
Others of his generation did strange things like wearing goatees and togas made of gauze-like fabric, or holding parties where attendees would dance naked on the tables. They wrote poetry and literature that didn't fit old Grecian forms, and they espoused living for the moment rather than for service to the community. It was quite an interesting time to be a Roman, from the sound of it.
3) Facebook will not notify you if a post appears with your name in it, but not tagged. Thanks to Meaghan Sullivan for unwittingly testing this for me!
Sunday, November 8, 2015
Opt...ists, Stir Fry Cook Time, and Andromeda vs The Moon
Today I Learned:
1) ...the differences between an optician, an optometrist, and an ophthalmologist.
An optician is a technician trained for fitting and prescribing eyeglasses and contact lenses. And that's about it.
An optometrist is an eye-care person who can also administer vision tests, perform vision research, and diagnose (some?) eye-related diseases. Optometrists go through a 4-year eye-specialized version of MD training, making them very qualified with respect to eyes and not particularly in other fields.
An ophthalmologist is an MD specializing in eye care. Opthalmologists are qualified to do pretty much anything related to the eye, up to and including eye surgery.
Thanks to Meaghan Sullivan for (inadvertently) teaching me these!
2) I can cook stir-fry for about half as much time as I thought I needed to and it still comes out fine!
3) The Andromeda galaxy, as viewed from Earth, looks approximately ten times bigger than the moon by radius. It's just very dim, and thus hard to see. There's a nice false-color composite to show scale here: http://ift.tt/1iMXw57
1) ...the differences between an optician, an optometrist, and an ophthalmologist.
An optician is a technician trained for fitting and prescribing eyeglasses and contact lenses. And that's about it.
An optometrist is an eye-care person who can also administer vision tests, perform vision research, and diagnose (some?) eye-related diseases. Optometrists go through a 4-year eye-specialized version of MD training, making them very qualified with respect to eyes and not particularly in other fields.
An ophthalmologist is an MD specializing in eye care. Opthalmologists are qualified to do pretty much anything related to the eye, up to and including eye surgery.
Thanks to Meaghan Sullivan for (inadvertently) teaching me these!
2) I can cook stir-fry for about half as much time as I thought I needed to and it still comes out fine!
3) The Andromeda galaxy, as viewed from Earth, looks approximately ten times bigger than the moon by radius. It's just very dim, and thus hard to see. There's a nice false-color composite to show scale here: http://ift.tt/1iMXw57
Germ-Free Mice, Coywolves, and One Less Ebola Outbreak
Today I Learned:
1) More about germ-free mice! For those not in the know, germ-free mice are mice, well, without germs. They're raised from birth in sterile environments, so they have no bacteria, archaea, or protists in them (some have intestinal worms, interestingly, which must have been transmitted in the womb!).
Germ-free mice were first made in the 1950s to test whether such animals could live. The hypothesis at the time was that they wouldn't; it was thought that bacterial symbionts, particularly in the gut, would be critical for survival. That turns out not to be the case.
I find it interesting that in the last decade, there's been a ton of research suggesting that gut biota are more important than we ever thought... except it's not more important than we ever thought, because we used to think gut biota were indespensible!
How do you make a germ-free mouse? Luckily, I learned this today too! The womb turns out to already be sterile, which is convenient. Then you birth the mouse by C-section in a sterile environment, to avoid bacterial contamination durin birth. Then you wean the mouse using a germ-free surrogate mother. If you don't have a germ-free surrogate mother available, you just... don't wean the pup. You just feed it by hand, I guess (again, sterilly).
Germ-free mice live just fine, although they have some dietary problems. For one thing, they suffer chronic diarrhea, so they drink a lot. They're also not the best at digesting proteins. Coming up with food they can eat is also pretty tricky. Most food, after all, has bacteria in it, which would contaminate the mice. Worse, since they have no experience with bacteria, they have pretty strong immune reactions even to bacteria that would normally be harmless, so you can't just autoclave the food (the bacterial antigens would still be present). From what I gather, germ-free mice are fed a diet not dissimilar from bacterial broth.
Thanks to Chigozie for digging up a ton of info on germ-free mice!
2) There's a species of canine called a coywolf that's a recent natural cross-breed between wolves, coyotes, and domestic dogs. They arose sometime in the last century, and have been shockingly successful, especially at hunting deer.
3) As of today, or sometime very recently, Sierre Leone is officially Ebola-free. Go modern medicine!
1) More about germ-free mice! For those not in the know, germ-free mice are mice, well, without germs. They're raised from birth in sterile environments, so they have no bacteria, archaea, or protists in them (some have intestinal worms, interestingly, which must have been transmitted in the womb!).
Germ-free mice were first made in the 1950s to test whether such animals could live. The hypothesis at the time was that they wouldn't; it was thought that bacterial symbionts, particularly in the gut, would be critical for survival. That turns out not to be the case.
I find it interesting that in the last decade, there's been a ton of research suggesting that gut biota are more important than we ever thought... except it's not more important than we ever thought, because we used to think gut biota were indespensible!
How do you make a germ-free mouse? Luckily, I learned this today too! The womb turns out to already be sterile, which is convenient. Then you birth the mouse by C-section in a sterile environment, to avoid bacterial contamination durin birth. Then you wean the mouse using a germ-free surrogate mother. If you don't have a germ-free surrogate mother available, you just... don't wean the pup. You just feed it by hand, I guess (again, sterilly).
Germ-free mice live just fine, although they have some dietary problems. For one thing, they suffer chronic diarrhea, so they drink a lot. They're also not the best at digesting proteins. Coming up with food they can eat is also pretty tricky. Most food, after all, has bacteria in it, which would contaminate the mice. Worse, since they have no experience with bacteria, they have pretty strong immune reactions even to bacteria that would normally be harmless, so you can't just autoclave the food (the bacterial antigens would still be present). From what I gather, germ-free mice are fed a diet not dissimilar from bacterial broth.
Thanks to Chigozie for digging up a ton of info on germ-free mice!
2) There's a species of canine called a coywolf that's a recent natural cross-breed between wolves, coyotes, and domestic dogs. They arose sometime in the last century, and have been shockingly successful, especially at hunting deer.
3) As of today, or sometime very recently, Sierre Leone is officially Ebola-free. Go modern medicine!
Saturday, November 7, 2015
Basil Leaves, Fungal Contamination, and agar.io Joining
Today I Learned:
1) Basil leaves are a convenient non-stick lining for steamed buns. They also smell nice when steamed. They left no noticeable taste in the buns they lined, sadly.
2) Fungal contamination is a serious problem for plant science, because molds will grow on plates much more rapidly and efficiently than most plants you'd be interested in studying, using up all their nutrients and generally messing up the experiment.
3) For those who play agar.io: today I learned that back in June or July, the devs of agar.io removed the ability to hackishly join into games by IP, probably intentionally. This explains why there are tons of guides online for how to join your buddies in agar.io, yet none of them seem to work.
1) Basil leaves are a convenient non-stick lining for steamed buns. They also smell nice when steamed. They left no noticeable taste in the buns they lined, sadly.
2) Fungal contamination is a serious problem for plant science, because molds will grow on plates much more rapidly and efficiently than most plants you'd be interested in studying, using up all their nutrients and generally messing up the experiment.
3) For those who play agar.io: today I learned that back in June or July, the devs of agar.io removed the ability to hackishly join into games by IP, probably intentionally. This explains why there are tons of guides online for how to join your buddies in agar.io, yet none of them seem to work.
Friday, November 6, 2015
Turbo-Redux, Turning On/Off, and CRN Trivia
Today I Learned:
1) ...the actual difference between a turbojet, a turboprop, and a turbofan. A turbojet is pretty much just as I described in yesterday's post. A turboprop is basically a turbojet where the burned fuel powers a propeller instead of directly producing thrust (though it does also produce some thrust). A turbofan is somewhere between the two -- it spends more of its burnt fuel directly producing thrust than a turboprop, but gets more of its thrust from its propellers than a turbojet.
What I don't understand is why a turboprop would ever be efficient. Why isn't it always better to turn hot air directly into thrust via a rocket-like mechanism than to use it to turn a propeller?
2) The reason we "turn on" or "turn off" electronic equipment is because old electronic equipment used turnable knobs to regulate power.
3) In a stochastic chemical reaction network satisfying detailed balance (roughly meaning that all of the reactions in the network are reversible and is balanced by the reverse process exactly at equilibrium) at steady state, the (probabalistic) number of each species in the network is Poisson-distributed. Why would this be?
1) ...the actual difference between a turbojet, a turboprop, and a turbofan. A turbojet is pretty much just as I described in yesterday's post. A turboprop is basically a turbojet where the burned fuel powers a propeller instead of directly producing thrust (though it does also produce some thrust). A turbofan is somewhere between the two -- it spends more of its burnt fuel directly producing thrust than a turboprop, but gets more of its thrust from its propellers than a turbojet.
What I don't understand is why a turboprop would ever be efficient. Why isn't it always better to turn hot air directly into thrust via a rocket-like mechanism than to use it to turn a propeller?
2) The reason we "turn on" or "turn off" electronic equipment is because old electronic equipment used turnable knobs to regulate power.
3) In a stochastic chemical reaction network satisfying detailed balance (roughly meaning that all of the reactions in the network are reversible and is balanced by the reverse process exactly at equilibrium) at steady state, the (probabalistic) number of each species in the network is Poisson-distributed. Why would this be?
Wednesday, November 4, 2015
Jet Engines, PTMCMC, and Solution Buffering
EDIT: I was wrong abuot turboprops and turbofans. If I understand correctly, turboprops actually use a turbojet-like engine to *power* a propeller, which is what provides the thrust. Turbofans fall somewhere in between a turboprop and a turbojet.
Today I Learned:
1) How jet engines work! Also, the difference between a turbojet, a ramjet, and a scramjet. First, what's a jet engine? A jet engine is, most simply put, a variant on a rocket. Rockets burn a fuel and an oxidizer, which makes a bunch of really hot gas, which is in turn funnelled out of the back to generate thrust. Jet engines also burn a fuel and an oxidizer, which makes a bunch of really hot gas, which in turn is funnelled out of the back to generate thrust. The difference is that jet engines don't carry their oxidizer. Instead they use the oxidizer that most of us use when we burn stuff -- air. That way, they don't have to carry giant tanks of oxidizer around, which would be heavy, expensive, and dangerous.
The catch is that the ratio of fuel to oxidizer (air) required to burn properly and generate thrust are fairly specific. In particular, you need oxygen at higher concentrations than is normally found in the atmosphere. Turbojets, ramjets, and scramjets attack the problem of compressing air in slightly different ways, all with the aim of burning fuel to produce thrust.
Turbojets are the most common form of jet engine. Any jet-looking engine with a propeller-looking spinning thing is a turbojet (actually, technically a turboprop or turbofan, but as far as I can tell they all operate under the same principle (see EDIT above)). Turbojets compress their air using, well, turbines. The propeller-looking thing in a jet engine isn't actually producing thrust -- it's actually jamming as much air as it can into the interior of the jet engine, where it can be burned with fuel to rocket the engine forward. Turbojets are very efficient in the regimes at which most commercial aircraft fly, and we're pretty darned good at building them.
Ramjets don't use a turbine to compress their air supply. In fact, ramjets have few or no moving parts -- they compress air by *moving really freaking fast*. Ramjets are basically double-sided funnels with complex fuel injectors in the middle. The funnel on the front collects air as the engine screams through it, causing the air to slow down, compress, and heat up significantly. The injector puts just enough fuel into it to keep it burning at the right rate, and the funnel on the back end directs the rocket flames backward to produce forward thrust.
This works great as long as you're already moving quite quickly, but is useless if you're standing still. Thus, ramjets are only useful on planes as supplementary engines for high operating speeds. Ramjets are also, ridiculously enough, used on some missiles and *artillery shells*. That's right. There are mortar shells with ramjets. Ramjets also don't work very well at extremely high speeds (several Machs). The reason is that the faster the ramjet moves, the hotter the incoming air gets as it's compressed. If the heat of the compressed air coming in becomes comparable to the heat of the burned fuel being used as propellant, the engine stops producing much in the way of thrust.
Enter the scramjet. The scramjet (for "supersonic combusting ramjet") is a variant of the ramjet that doesn't slow down incoming air to compress it. The scramjet features a more or less clear line of sight from the front to the back, with the aim of keeping the air flowing very quickly (faster than sound) while compressing it enough to burn well with injected fuel. This requires some absurdly fast (millisecond-level) injection control, which is technically quite challenging.
Scramjets also suffer the same speed limitations as ramjets, but much worse -- they only operate at all at multiple-Mach speeds, which limits their use to things that can get that fast using other methods. This and other design challenges have kept scramjets from seeing practical application... anywhere. Nevertheless, scramjets have technically existed since the 50s, and are currently being incorporated into several next-generation airplanes.
Thanks to JD for unknowingly pointing me to some good Wiki articles on jet tech.
2) There's a variant of Markov-Chain Monte Carlo called Parallel Tempering MCMC (PTMCMC) which lets you, among other things, relatively efficiently compute normalization constants when comparing alternate hypotheses, which lets you compute odds ratios exactly (and calculate exact probabilities of hypotheses).
3) Buffered solutions really are pretty robust -- I buffered some aqueous solution to pH 8.2 with TRIS today, then increased its volume by a good 25% by adding water, and it apparently didn't affect the pH at all.
Today I Learned:
1) How jet engines work! Also, the difference between a turbojet, a ramjet, and a scramjet. First, what's a jet engine? A jet engine is, most simply put, a variant on a rocket. Rockets burn a fuel and an oxidizer, which makes a bunch of really hot gas, which is in turn funnelled out of the back to generate thrust. Jet engines also burn a fuel and an oxidizer, which makes a bunch of really hot gas, which in turn is funnelled out of the back to generate thrust. The difference is that jet engines don't carry their oxidizer. Instead they use the oxidizer that most of us use when we burn stuff -- air. That way, they don't have to carry giant tanks of oxidizer around, which would be heavy, expensive, and dangerous.
The catch is that the ratio of fuel to oxidizer (air) required to burn properly and generate thrust are fairly specific. In particular, you need oxygen at higher concentrations than is normally found in the atmosphere. Turbojets, ramjets, and scramjets attack the problem of compressing air in slightly different ways, all with the aim of burning fuel to produce thrust.
Turbojets are the most common form of jet engine. Any jet-looking engine with a propeller-looking spinning thing is a turbojet (actually, technically a turboprop or turbofan, but as far as I can tell they all operate under the same principle (see EDIT above)). Turbojets compress their air using, well, turbines. The propeller-looking thing in a jet engine isn't actually producing thrust -- it's actually jamming as much air as it can into the interior of the jet engine, where it can be burned with fuel to rocket the engine forward. Turbojets are very efficient in the regimes at which most commercial aircraft fly, and we're pretty darned good at building them.
Ramjets don't use a turbine to compress their air supply. In fact, ramjets have few or no moving parts -- they compress air by *moving really freaking fast*. Ramjets are basically double-sided funnels with complex fuel injectors in the middle. The funnel on the front collects air as the engine screams through it, causing the air to slow down, compress, and heat up significantly. The injector puts just enough fuel into it to keep it burning at the right rate, and the funnel on the back end directs the rocket flames backward to produce forward thrust.
This works great as long as you're already moving quite quickly, but is useless if you're standing still. Thus, ramjets are only useful on planes as supplementary engines for high operating speeds. Ramjets are also, ridiculously enough, used on some missiles and *artillery shells*. That's right. There are mortar shells with ramjets. Ramjets also don't work very well at extremely high speeds (several Machs). The reason is that the faster the ramjet moves, the hotter the incoming air gets as it's compressed. If the heat of the compressed air coming in becomes comparable to the heat of the burned fuel being used as propellant, the engine stops producing much in the way of thrust.
Enter the scramjet. The scramjet (for "supersonic combusting ramjet") is a variant of the ramjet that doesn't slow down incoming air to compress it. The scramjet features a more or less clear line of sight from the front to the back, with the aim of keeping the air flowing very quickly (faster than sound) while compressing it enough to burn well with injected fuel. This requires some absurdly fast (millisecond-level) injection control, which is technically quite challenging.
Scramjets also suffer the same speed limitations as ramjets, but much worse -- they only operate at all at multiple-Mach speeds, which limits their use to things that can get that fast using other methods. This and other design challenges have kept scramjets from seeing practical application... anywhere. Nevertheless, scramjets have technically existed since the 50s, and are currently being incorporated into several next-generation airplanes.
Thanks to JD for unknowingly pointing me to some good Wiki articles on jet tech.
2) There's a variant of Markov-Chain Monte Carlo called Parallel Tempering MCMC (PTMCMC) which lets you, among other things, relatively efficiently compute normalization constants when comparing alternate hypotheses, which lets you compute odds ratios exactly (and calculate exact probabilities of hypotheses).
3) Buffered solutions really are pretty robust -- I buffered some aqueous solution to pH 8.2 with TRIS today, then increased its volume by a good 25% by adding water, and it apparently didn't affect the pH at all.
Tuesday, November 3, 2015
Hibernating Squirrels, SVD, and Fire Ant Genetics
Today I Learned:
1) When squirrels hibernate, they lose a significant amount of neurons and synapses. When they awake from hibernation, they very quickly -- within two hours -- start growing a whole lot of new neurons and make a ton of connections, then start pruning them back down, just like a young mammal. Neurologically, then, squirrels go through teenagehood every time they hibernate.
2) ...a nice trick for reducing the dimensionality of very large data sets called Singular Value Decomposition (SVD). The idea is rather similar to PCA, if you know that. The basic idea is to change the basis in which you are looking at your data so that your data fall "more cleanly" on the axes (and no, I'm not going to define what "more cleanly" is here because I don't really understand it yet). The idea is that often there are bases with smaller dimension than your full data on which you can project your data without losing much information. If you can find them, then you can represent your data in that basis and drop some of the dimensions, making them (computationally) easier to work with.
You start by putting all of your data in a matrix M, where the rows are vectors of single datums (say, points in a time series, or positions of a particle in a box) and the columns are dimensions (say, specific times in the time series, or spatial axes in the box). Then you use some fancy math to factor M into some more matrices U, S, and V with M = USV*, where V* is the complex conjugate of V (basically its inverse) and S is a diagonal matrix (that is, all of its elements are 0 except the ones on the diagonal). There's a theorem that says that you can always do this.
Now, the cool thing about U, S, and V is that U and V describe the bases I was talking about earlier, while the elements of S (remember, there are only elements on the diagonal) describe the "scales" of each of those basis elements. Those elements are called the "singular values" of M, and they tell you which bases can be dropped without losing much information.
3) Red fire ants, the invasive and painful species found in the Southern US, China, Hong Kong, and South America, have multi-queen colonies with mixed non-sister worker populations, at least in the US. This condition is called polygeny.
This didn't used to be the case. It used to be that fire ants had distinct colonies, with well-demarcated, fiercely-defended borders (monogeny, the usual situation for ants of most species). Then, one day, there arose a mutation in the Gp-9 gene in one of the colonies. Gp-9 (I don't know what it stands for but I'm guessing "gene product 9") is involved in recognition of self-colony vs non-self-colony. The new polygenious variant a) causes affected workers to not care about defending territories, and b) causes affected workers to hunt down and kill monogenious queens in the nest. Don't ask me how. In any case, because the polygenious variant is so self-selective, it quickly spread through the fire ant population.
1) When squirrels hibernate, they lose a significant amount of neurons and synapses. When they awake from hibernation, they very quickly -- within two hours -- start growing a whole lot of new neurons and make a ton of connections, then start pruning them back down, just like a young mammal. Neurologically, then, squirrels go through teenagehood every time they hibernate.
2) ...a nice trick for reducing the dimensionality of very large data sets called Singular Value Decomposition (SVD). The idea is rather similar to PCA, if you know that. The basic idea is to change the basis in which you are looking at your data so that your data fall "more cleanly" on the axes (and no, I'm not going to define what "more cleanly" is here because I don't really understand it yet). The idea is that often there are bases with smaller dimension than your full data on which you can project your data without losing much information. If you can find them, then you can represent your data in that basis and drop some of the dimensions, making them (computationally) easier to work with.
You start by putting all of your data in a matrix M, where the rows are vectors of single datums (say, points in a time series, or positions of a particle in a box) and the columns are dimensions (say, specific times in the time series, or spatial axes in the box). Then you use some fancy math to factor M into some more matrices U, S, and V with M = USV*, where V* is the complex conjugate of V (basically its inverse) and S is a diagonal matrix (that is, all of its elements are 0 except the ones on the diagonal). There's a theorem that says that you can always do this.
Now, the cool thing about U, S, and V is that U and V describe the bases I was talking about earlier, while the elements of S (remember, there are only elements on the diagonal) describe the "scales" of each of those basis elements. Those elements are called the "singular values" of M, and they tell you which bases can be dropped without losing much information.
3) Red fire ants, the invasive and painful species found in the Southern US, China, Hong Kong, and South America, have multi-queen colonies with mixed non-sister worker populations, at least in the US. This condition is called polygeny.
This didn't used to be the case. It used to be that fire ants had distinct colonies, with well-demarcated, fiercely-defended borders (monogeny, the usual situation for ants of most species). Then, one day, there arose a mutation in the Gp-9 gene in one of the colonies. Gp-9 (I don't know what it stands for but I'm guessing "gene product 9") is involved in recognition of self-colony vs non-self-colony. The new polygenious variant a) causes affected workers to not care about defending territories, and b) causes affected workers to hunt down and kill monogenious queens in the nest. Don't ask me how. In any case, because the polygenious variant is so self-selective, it quickly spread through the fire ant population.
Sunday, November 1, 2015
The Ergodic Hypothesis, Rice Noodles, and Frozen Bubbles
Today I Learned:
1) The ergodic hypothesis in statistical mechanics states that, roughly, all of the microstates of a system with the same energy are equally probable over a long enough time span. It also seems to say that the average of a measurement of the system (say, its temperature or its pressure) is the same over time as it is for the states. I'm not sure the relationship between these two statements.
2) Rice noodles perform pretty strangely when reheated in a hot pan. When I tried with some soy sauce, I ended up with a solid sheet of slightly pasty crisp lining the pan, though the rest turned out fine.
3) In some of the colder places on the planet, you can freeze bubbles. It's quite beautiful: http://ift.tt/1T6tpkS Also http://ift.tt/1Mba42h
1) The ergodic hypothesis in statistical mechanics states that, roughly, all of the microstates of a system with the same energy are equally probable over a long enough time span. It also seems to say that the average of a measurement of the system (say, its temperature or its pressure) is the same over time as it is for the states. I'm not sure the relationship between these two statements.
2) Rice noodles perform pretty strangely when reheated in a hot pan. When I tried with some soy sauce, I ended up with a solid sheet of slightly pasty crisp lining the pan, though the rest turned out fine.
3) In some of the colder places on the planet, you can freeze bubbles. It's quite beautiful: http://ift.tt/1T6tpkS Also http://ift.tt/1Mba42h
Subscribe to:
Posts (Atom)