Here is some R code and detailed explanation on how to thoroughly explore keywords within an academic field, in this case ecology.

Here is some R code and detailed explanation on how to thoroughly explore keywords within an academic field, in this case ecology.

This is just a random science tidbit. Two bodies with mass will always interact just a little bit, but in the case of the Earth our effect on the Sun is so small as to be negligible. In the case of Jupiter, it is not. Jupiter is so massive that it moves the Sun just a little bit, so they are actually technically orbiting each other. As for exactly what gravity is and where it came from, I can’t tell you, but I am grateful for it.
Highlights of things that caught my eye from this Smithsonian article:
Troy McClure was Phil Hartman. Rest in peace, Phil Hartman.
So-called heat lightning is a thunderstorm that is very tall and very far away. According to this article, sound from thunder will only travel about 15 miles, but if lightning is high enough you can see it 100-200 miles away. So this suggests to me that if you hear thunder, the storm is probably close enough you should go inside to be safe, but if you only see lightning and don’t hear thunder (assuming you are in a reasonably quiet location), it might be okay to stay outside.
There is a clear consensus that everybody hates setting the clocks ahead and losing sleep. There seems to be movement toward doing away with this dumb tradition and going towards all daylight savings time all year. But at least one scientist says the evidence points toward going all standard time all year.
I would add that the time shift causes trouble in science and other technical fields, where we try to measure stuff over time and make sense of it. It also causes practical problems for people who have to travel or collaborate with colleagues across time zones (which is already challenging). Once I got a roomful of people together at 7 a.m. in Singapore for a meeting led by U.S. staff, only to find that the U.S. had changed its clocks the night before and the meeting was over. Those people were a little mad at me. I bought them doughnuts. A lesson learned there is to let your calendar software handle time zones and not try to do the math yourself. The U.S. is not even the worst – Australia has half-hour time shifts that are different in different cities not that far apart. The time shift is dumb, let’s just stop doing it.
This Science article (which seems to be discussing a Nature article) has an interesting discussion of how scientific and technological research has a lot of twists and turns and dead ends.
That Nature piece will also give non-scientists a realistic picture of what development of a new technology is like in this field. Everyone builds on everyone else’s work, and when a big discovery is finally clear to everyone, you’ll find that you can leaf back through the history, turning over page after page until you get to experiments from years (decades) before that in hindsight were the earliest signs of the Big Thing. You might wonder how come no one noticed these at the time, or put more resources behind them, but the truth is that at any given time there are a lot of experiments and ideas floating around that have the potential to turn into something big, some day. Looking back from the ones that finally worked out brings massive amounts of survivorship bias into your thinking. Most big things don’t work out – every experienced scientist can look back and wonder at all the time they spent on various things that (in retrospect) bore no fruit and were (in retrospect!) never going to. But you don’t see that at the time.
Science
So how could technological progress be accelerated? I suspect we will always need human brains to formulate experiments and make the final call on interpreting results. But it seems as though computers/robots should be able to perform experiments. If they can perform a lot more iterations/permutations of experiments in a fraction of the time that humans could, the cost of dead ends should be much lower. The humans won’t have to worry as much about which experiments they think are most promising, they can just tell the computer to perform them all. If we have really good computer models of how the physical world works, the need for physical experiments should be reduced. That seems like the model to me – first a round of automated numerical/computational experiments on a huge number of permutations, then a round of automated physical experiments on a subset of promising alternatives, then rounds of human-guided and/or human-performed experiments on additional subsets until you hone in on a new solution.
Of course, for this to work, you have to do the basic research to build the accurate conceptual models followed by the computer models, and you have to design the experiments. And you have to be able to measure and accurately distinguish the more promising results from the less promising. There will still be false positives leading to dead ends after much effort, and false negatives where a game-changing breakthrough is left in the dustbin because it was not identified.
That is another idea though – commit resources and brains to making additional passes through the dustbin of rejected results periodically, especially as computers continue to improve and conceptual breakthroughs continue to be made.
I doubt I am the first to think of anything above, and I bet much of it is being applied. To things like nuclear weapons, depressingly. But it seems like a framework for bumping up the pace of progress. The other half of the equation, of course, is throwing more brains and money into the mix. Then there is the long game of educating the next generation of brains now so they are online 20 years from now when you need them to take over.
This article talks about machine learning/AI helping to make sense of the data from fusion experiments, and maybe eventually designing and even running the experiments. It’s interesting to think about computers speeding up progress by being able to design and run experiments orders of magnitude faster than humans could. If it works well, they could fail a million or a billion times in short order and there would still be value in a single success. You could also imagine a computer going down a rabbit hole and coming up with a result that humans are not able to explain or replicate, and then you would have to think about what to do with that result. There’s also the question of whether a computer can ever truly “understand” a system, but I guess constructed a model, whether mental or mathematical, testing it against observation, tweaking it, and then testing it against more observation is basically how we do it.
The bulk of the Brood X cicadas are likely to come out in May (if 2004 is a good guide to what to expect) and be centered around D.C. and Baltimore. The edge of the blob just touches Philadelphia, and there are scatterings in southern and Central Pennsylvania, Ohio, Indiana, Tennessee and Georgia. I wonder how they get scattered the way they do – do they start out everywhere and then local populations gradually go extinct over time? Besides a clear map and an empirical probability density function (but they don’t call it that, not wanting to scare readers!), this Washington Post article reminded me that the Cicada swarm is actually made up of three similar but different species. That also is weird and interesting.
Also, here is a cicada cookbook from the University of Maryland. I have tried fried crickets in Asia but I don’t think I can bring myself to try Cicadas. As the into to the cookbook points out though, shrimp and crayfish are basically bugs that we westerners eat, so your ick factor is mostly just a matter of cultural conditioning. The cookbook also has this interesting comparison of protein in insects vs. other animals we humans like to eat:
Many people all over the world eat insects and other arthropods both as a delicacy and staple. This is sensible because insects are nutritious. Insects provide as much protein pound per pound as lean beef. For example, every 100 gram serving of each, termites provide 617 calories of energy while lean ground beef gives 219 and cod gives 170 (3). Although their amino acid content is not as well-balanced for human nutrition, this can be easily corrected by including fiber and other plant proteins into your diet. Insects are also a good source of minerals and some vitamins, especially for people who have limited access to other animal proteins.
University of Maryland
So termites sound like a pretty good survival food. Even if you live in some wasteland where nothing else will grow, there is likely some wood around that you could feed to them. You can then feed them to chickens or rats if you want, but it may be most efficient to just eat them if you can handle it. I don’t think I handle it – termites are in the cockroach family, I while I can handle the crickets for sale in Asian street markets, I cannot handle the “water bugs” which are basically cockroaches. But maybe if someone can grind them into a flour or paste I can use to thicken my soup, it could be a nutritious supplement and I might not have to think about it so much.
I’m still on the topic of innovation. Slate has an article on what an “innovation driven industrial policy” would look like.
It is not—and has never been—that the U.S. does not have a de facto industrial policy. Through regulation, foreign investment rules, trade barriers, and even subsidies (think ethanol), the federal government has found ways to support U.S. industry. And even the most ideological appropriators have not succeeded in removing millions of dollars of research funding channeled through the long-standing research agencies like the National Science Foundation, the National Institutes of Health, and the Defense Advanced Research Projects Agency or through programs established to support development of that research, such as the Small Business Research Innovation program (now branded as “America’s Seed Fund”).
Slate
So the idea is that an industrial policy would take all this and put it under some kind of central management intended to spur progress in key areas. Then it would pump out more funding and encourage private industry to do the same.
I’ve always thought that teeth might be the weakest point of the human body. Why did our teeth evolve to be made of calcium, which dissolves in acid, when pretty much all our food is acidic? Why do we have to strap metal torture devices to children’s teeth for years just for them to be reasonably straight? Why don’t animals seem to have these problems?
This article in Scientific American sings the praises of teeth. It argues that, like many of our other organs and systems, our modern lives just aren’t what they evolved to deal with. It basically comes down to the idea that our food is too sweet and too soft.
The evolutionary history of our teeth explains not only why they are so strong but also why they fall short today. The basic idea is that structures evolve to operate within a specific range of environmental conditions, which in the case of our teeth include the chemicals and bacteria in the mouth, as well as strain and abrasion. It follows that changes to the oral environment can catch our teeth off guard. Such is the case with our modern diets, which are unlike any in the history of life on our planet. The resulting mismatch between our biology and our behavior explains the dental caries (cavities), impacted wisdom teeth and other orthodontic problems that afflict us.
Scientific American
I admit, I don’t like working for my food – I like boneless, seedless, shell-less everything. My teeth may have paid the price.