Interstellar delivers truth bombs

Early on in the movie Interstellar there are two important lessons about what makes a society fail (or succeed), both delivered in the parent-teacher conference that Cooper attends.

Lesson one: don't underestimate the power of engineering (and science)

Lesson two: beware of those who would rewrite the truth

(Excerpts from the novelization of the movie by Greg Keyes. No, I'm not a nerd. Ok, I am.)

Andrew Rader points out some problems with the movie:

The main problem was also pointed out by Kip Thorne in The Science of Interstellar: that fighting the blight on Earth would make a lot more sense than going to a different planet.

Thorne also raises the problem of orbital mechanics in chapter 7 of the book:

and proposes a few speculative mechanisms to get the necessary changes in velocity from gravity assists. Note that there are two decelerations one of $c/3$ and one of $c/4$ for a total speed change of  $7c/12$ or $1.75\times 10^{8}$ m/s. Returning to the Endurance requires an increase in speed of $1.75\times 10^{8}$ m/s as well.

To see the size of the problem, let's say they take 500 seconds (8 minutes and 20 seconds) to do each maneuver (while the rest of the Universe ages significantly) and the Ranger's mass is 2 metric tons (for simplicity, we'll assume that the water taken in on the planet makes up for the loss of Dr. Doyle to stupidity, indiscipline, and lack of planning). If we assume constant thrust for simplicity, assume away all friction and ignore the propellant mass loss (yay, infinite specific impulse!), the thrust needed for each maneuver is $7 \times 10^8$ Newton or about the same as 1077 SpaceX Merlin engines (averaging their atmosphere and vacuum thrust to 650 kN). Since there's propellant mass loss, let's say we "only" need the equivalent of 900 Merlin engines. So, yes, only a gravity assist would do.

Yes, it's an oversimplification, but didn't feel like solving the Tsiolkovsky equation. Hence the drop from 1077 to 900 engines. (That's still equivalent to 100 Falcon 9 rockets.) By the way, Thorne appears unconvinced of the feasibility of those gravity assists and hence of the feasibility of whole expedition to Miller's planet. But at least they tried to be accurate with some science in the movie.

Oh, and speaking of nerds:

Love of science and depth of knowledge

For a successful modern society, reality must take precedence over public relations, for Technology cannot be fooled. -- Adapted by JCS from Richard Feynman's final sentence in his appendix to the Report of the PRESIDENTIAL COMMISSION on the Space Shuttle Challenger Accident.

Suppose someone says "I love French [the language]." You'd probably assume they spoke French. If someone says "I love skiing," you'd probably assume they can ski; if someone says they "love science," well, that's a bit more complicated.

In fact, if people "loved French" like they "love science," most of them wouldn't be able to translate "Oui."

And that's a problem on three different levels:

1. At the most basic level, pretending to like science but with no interest in learning any (which is what "I love science" people do) creates a disconnect between words and reality. That disconnect has been thoroughly exploited by publicity-seeking celebrities, opportunistic politicians, and greedy stem-o-preneurs to advance their own agendas.

2. Past this basic 'branding/image-driven' level, we find that those who benefit from a distortion of the meaning of science (STEM, really) and those who are afraid their pretense will be exposed actually act against the advancement of science (STEM, really), using arguments more suited to politics ("x percent of scientists believe that..." as if science was a matter of votes) or authoritarian autocracies.

3. But at a very deep level, this "I love science" pretense corrupts the very idea of actually knowing or understanding something, which is essential to the development (and maintenance) of our technological-dependent society.

A previous blog post has touched on this idea, but we'll elaborate on it here, with some implications.

The figure at the top describes four levels of knowledge, roughly separated by their real-world implications; a big problem with the "I love science" crowd is that they act as if the differences between these levels have no real world implications, which they do. From top to bottom:

Ignorance, particularly when combined with obliviousness, can be funny but can also be exasperating. I make some hay from media ignorance in a number of posts (one, two, three), and YouTubers Thunderf00t and EEVblog have fun debunking nonsense that's based on exploiting this ignorance.

But ignorance of science persists, and persists in people who "love science," mostly because their interlocutors are not willing to ask questions. Imagine that someone said they love French; we could then say "tu parles Français, alors?" The people who love French like they "love science" will hear gibberish. This would be an immediate "poseur" alarm; but most people who would do it for French won't ask these questions for science.

(One may even be called anti-social for asking sciencey things to someone who "loves science.")

A passing familiarity with the topic can be a dangerous social trap. As the joke goes, these are the people who believe they can argue successfully with an expert based on having heard a TED talk on the subject while cycling at the gym. It's particularly dangerous when this passing familiarity is acquired by reading popularization tomes created by popularizers (instead of people working in the field).

The problem with passing familiarity is that most people tend to overestimate the reach of their familiarity, mistaking the recognition of sentences for actual understanding of those sentences. In our continuing French example, this would be the case of someone who had some French lessons decades ago and watches French movies with subtitles but can't do much more than ask people in France if they speak English.

In STEM this is a complicated level, since there are people who have a reasonable qualitative understanding of the issues without being able to actually solve technical problems (of any complexity), while there are others who follow the Mythbusters' "science as big booms" or focus on the scientists rather than the science.

There's a second-order effect in this problem, which comes from the importance of quantitative thinking in STEM. Many people have some sort of numerophobia: they resist numerical thinking for whatever reason. Perhaps insecurity, perhaps bad experiences with the educational system. But for STEM, once we're past the basics, numbers matter. Numbers become all that matters.

(There's an interesting case of this familiarity-level overreach in Business Management [as a discipline]: many people who have a vague familiarity with business speak think that they actually know business material. Some of them say things as ignorant as "management is just common sense," at which point I ask them to value an option or process some market research data using common sense.)

Operational knowledge is the level at which most people who actually know something operate. For our French example, that would be a person who can communicate like a French person (talk with French people, watch French-language movies and TV shows, write blog posts in French, read French books).

In STEM this level is easy to separate from the passing familiarity (and to divide into sub-levels) by using actual applications. In the chart at the top of the post, computing the angular speed of the axles of a differential is a simple, high-school level Physics question; the kind of thing engineering students have to know how to do in their freshman year.

I have in the past suggested screening social interactions using simple questions, sometimes as simple as asking for basic unit conversion (how many Joule in a kilowatt-hour?) sometimes with a problem or two:

A deep understanding of the field is something most people, including those who have operational knowledge, have no need for. Continuing with the French example, this would be the case of someone who creates crossword puzzles for Le Monde, copyedits literature tomes in French, and generally argues fancy matters of language.

In STEM these tend to be the Research and Development departments, the research scientists, the design engineers, the specialized technical consultants. In other words, the people who create the future of our technological society.

(At this point one feels obliged to note that people with a deep understanding of STEM tend to be the most reviled in most social environment: cf. definitions for nerd and geek.)



What is both ironic and dangerous is that (as indicated in the chart at the top) the number of people in each level of knowledge decreases with increasing knowledge, but (not indicated in the chart) the level of confidence these same people have in their statements about STEM doesn't. I believe that this is a definite change relative to a few decades ago, and not a change for the better.

It appears that the cost of increasing the popularity of "loving science" was the loss of meaning of "knowing science" (STEM, really). This is a dangerous trend in a technology-dependent society.

Again, the problem with science communication

The problem with science communication is the science communicators who aren't interested in communicating science.

Take, for example, this tweet:

Yes, it's quite obvious that the Science Channel twitterer is referring to the solar system, not the galaxy.

No. That's not true.

The announced television show itself, I'm sure will get that right. But the twitterer? I literally can't even, as the kids say. And I literally can't even... bet a cup of coffee that the twitterer understands the difference between the solar system and the galaxy --- because I have an MBA.

Yes, a Master's degree in Business Administration, and that's what tells me that it's quite likely that the twitterer has no clue about the science. First, because it was posted at midnight on Friday; second, because it's television; and third because it's on twitter.

It's not even a case of people who "love" science (as long as they don't have to learn any). It's more a case of 'we need a "communications/social media team" for this property.' (Property here refers to the Science Channel.) That's the twitter part: the team is grown as an appendage to the marketing group because that's how people in media tend to see twitter, just another channel to add to the communications mix.

And these "communication/social media team" members are recruited from communication programs and from people who are part of the influence network of those in charge of recruiting, because that's how things are done in mass media conglomerates. So that's the television part.

At midnight on a Friday, the most junior or least competent members of the team will be the ones operating the account. And those are likely to be the ones who are least likely to know the difference between galaxies and solar systems.

But the recruitment of people who know nothing about science to positions of science communication isn't the worst problem.

The worst problem is that there's no problem, not really, because:

• The audience doesn't care, overwhelmingly. They are mostly people who "love science," and even if someone points out the error, that will not change the fact that watching the Science Channel is an identity product and the brand has the word "science" in it.

• Since the audience doesn't care, the advertisers don't care either. After all, it's not like they really want a critical thinking audience for their commercials. (Remember, I have an MBA. Only few products and companies want a critical thinking audience.)

• Since the advertisers don't care, the channel management doesn't care. And most in management have no interest in science; it's a product to be sold, just like potato chips and time-share vacations.

And the science-educated audience, the ones who notice these things? Well, everyone hates a know-it-all tattle-tale nerd. Until the technological society that was built by engineers on the foundations of science collapses.

Then, well, then that was a totally unpredictable act of God Nature.

Why I write careful posts on nonsensical topics

Basically, because I'm not allowed to write or talk about work-related matters.

So I apply my considerable intelligence, broad knowledge, and unbeatable modesty to things like the differences between powerlifting and bodybuilding (and the superiority of the former over the latter), using the standard B-school two-by-two matrix format (click for bigger):

I also take to task people who think that knowledge is superfluous as long as their intentions are good (or at least consistent the the current "virtuous" narrative). For example, I did congratulate TIME for not using a photo of cooling towers for this article (unlike almost everyone else who uses images of cooling towers' steam to write about pollution),

but I do have to point out that most of what's seen coming out of those stacks is also steam. First, the color and the shape of the expansion give that away, but even if they didn't, gaseous $\mathrm{CO}_{2}$ is transparent, as is water vapor. (Steam is liquid water suspended in water vapor.) And soot and other common pollutants have distinctive colors; that white means water.

If you're surprised that combustion would generate water vapor, which condenses when it expands at the top of the stack, remember that hydrocarbon-based fuel combustion is mostly

$ \mathrm{C}_{n}\mathrm{H}_{m}  + (n+ m/4)\,\,\, \mathrm{O}_{2}\rightarrow n\,\,\, \mathrm{CO}_{2}  + m/2 \,\,\, \mathrm{H}_{2}\mathrm{O},$

and most of the rest (nitrous and sulfurous compounds, metals, soot and ash, the souls of the damned) are removed from the smoke before it's allowed to leave through the stacks (because of laws against pollution):

Sometimes I do take the nonsense dial to 11 --- but all the calculations are correct.

About a year ago, when I temporarily changed the name of this blog to Project 2016, the idea was to track non-work related learning, which is one of my hobbies; but time constraints made me choose between actually learning stuff and blogging about it, and I chose the learning.

So, expect some more carefully thought-out nonsense. Careful thinking is another one of my hobbies, so I practice it even on nonsensical topics. I have very strange hobbies: another one is moving heavy objects for no immediate purpose, like this gentleman

Live long and prosper -- JCS

Non-linearity is a pain in the neck and other smart content of this week

Non-linearity is a pain in the neck

Literally; and I use "literally" literally, not figuratively.

Most of the time we have an implicit linear worldview: if $x$ effort gives you $y$ result, then $(1+\epsilon)x$ effort should give you $(1+\epsilon)y$ result, approximately. And in many cases, where the $\epsilon$ is very small, this tends to be the case.

But the world isn't linear, especially in the gym. Especially in conditioning. (Editor note: conditioning is like cardio, except it actually works because it's high-intensity, short, and paused; that makes it very painful. This is why most people who are happy with no results prefer cardio, which delivers no results with only mild discomfort.)

Along with the basic, more functional conditioning movements (hill sprints, farmer's walks, stair sprints, sandbags), I've been doing medicine ball Atlas stones. Basically, one lifts a medicine ball from between one's feet to a platform above shoulder height (like an Atlas stone), then brings it back to the floor. Like any other conditioning exercise, this needs to be done correctly to avoid injury and not the CrossFit way of "fake it until you break it."

(The real Atlas Stone exercise. Those are not medicine balls.)

Medicine ball Atlas stone lifts have one of the most nonlinear pain response functions in the gym. Basically, for the first 5-10 reps, it feels like nothing is happening; the heart rate raises slowly and the muscles get a little hot. Then, at about 15, you discover muscles that never hurt before; discover them as they start hurting hard and fast. I discovered several new muscles in my neck --- and I regularly train neck as part of the posterior chain.  At 20-25, the ball has become pure neutronium, the platform has relativistically moved up several parsecs, and your blood pressure could drive a nuclear power plant turbine. So you rest 90 seconds, then restart; that's conditioning.

That's non-linearity.

In fact the response function is highly non-linear, not something that could easily be approximated with a low-degree polynomial, so I propose the following model:

Plot of $\mathsf{Pain} \doteq \exp(\exp(\exp( 0.035 \times \mathsf{Reps})))$

One of these days I'll write something serious about the misuse of linearity in everyday thinking; possibly also comment on the use of "exponential" to describe all convex functions and the unprofessionalism of drawing said "exponentials" on slides using the 'draw ellipse segment' tool in PowerPoint instead of plotting the actual function. But that's for another day.

Added Nov 16, 2016: while we wait for that "another day," here's a visual comment on convex functions:

Stephen Wolfram helps popularize science. Real science.

Stephen Wolfram, creator of Mathematica and author of A New Kind Of Science (but don't hold that book against him), helped the producers of the movie Arrival (2016) make less fools of themselves than the usual in scifi movies:

When I watch science fiction movies I have to say I quite often cringe, thinking, “someone’s spent $100 million on this movie—and yet they’ve made some gratuitous science mistake that could have been fixed in an instant if they’d just asked the right person”.

Part of that is the audience, who says "I love science" but really only likes the image (or at most the idea) of liking science and has no interest in actually learning any. It's like those people who like the idea of getting in shape, but don't exercise or change their unhealthy habits.

Occasionally one can see code. Like there’s a nice shot of rearranging alien “handwriting”, in which one sees a Wolfram Language notebook with rather elegant Wolfram Language code in it. And, yes, those lines of code actually do the transformation that’s in the notebook. It’s real stuff, with real computations being done. (Emphasis added.)

Here's Dr. Wolfram (whose alter ego is Mr. Tungsten --- couldn't resist 😀) talking about serious things:

Living in the future is great, never mind those who long for the "good" old times.

I have two words for these who long for the good bad old times: modern dentistry. (Not my original thought, but I've heard it from many sources; don't know original attribution. Still effective at capturing the power of technological change at an emotional level.)

This Intelligent 3D Printer Is Building Big, Beautiful Structures:

Ai Build's system uses video cameras outfitted with machine learning algorithms to allow robots to learn from their mistakes—meaning they can operate more quickly, correcting for errors on the fly instead of moving slowly to prevent them. According to Cam, Ai Build's arms can print in half the time it would take using standard techniques. (Via Singularity Hub.) 

Pill Packing 100 Billion Designer Bacteria Could Be Tested Next Year

In one of the first medical applications of this concept, Synlogic has patented a version of E. coli engineered to develop “an unquenchable appetite for ammonia” and turn it into the amino acid arginine, which, unlike ammonia, is harmless to the human body. (Via Singularity Hub.)  

Media Briefed on New NASA Hurricane Mission

As you can see, NASA is causing all these hurricanes to create a New World Order where scientists will rule and… huh, no. It's just that hurricanes are kind of easier to spot from high above the atmosphere than from the basements where the people who come up with these NASA conspiracies spend their lives.

That's it for this geek-out. Live long and prosper. --JCS

(Mood music.)

Powerlifters vs Gym Rats, take 2

(This is a redo of the numbers in my previous powerlifters vs gym rats post, with assumptions that are less favorable to powerlifters.)

First, since we need some sort of metric to compare athletes, I'll unbiasedly 😀 choose the average of three lifts, bench press, deadlift, and squat, as a percentage of the bodyweight of the athlete. Call that metric $S$.

We'll use a standard Normal for the distribution of this metric, by subtracting the mean (100 percent of bodyweight for non-powerlifters, assuming that the average gym rat can bench, deadlift, and squat their own bodyweight) and dividing by the standard deviation (say 15 percent of bodyweight, using the scientific approach of judging 10 to be too little and 20 to be too much). In other words, for non-powerlifters, $z \doteq (S-100)/15.$

As in the previous post, we'll assume that powerlifters are 1 percent of the gym rats; but instead of the powerlifters having a mean at 2 (in $z$ space, 130 in $S$ space), they only have a one-SD advantage, that is their mean is at 1 (in $z$ space, 115 in $S$ space). In other words

$\qquad z \sim \mathcal{N}(0,1)\qquad $ for non-powerlifters
$\qquad z \sim \mathcal{N}(1,1)\qquad $ for powerlifters

Using these assumptions we can now compute the percentage of powerlifters that exist in a gym population above a given threshold; we can also compute the median score of all athletes who score above that threshold (click for larger):

Note that the conditional median that we're using here is lower  than the conditional mean, as the conditional distribution is skewed to the right, i.e. has a long right tail. The choice of the median is more informative for skewed distributions as a "sense of what we'll see in the gym."*

It's interesting to note that this is the median of the combined distribution of powerlifters and other gym rats, weighted by their proportion in the population above the threshold, so the difference between this median and the threshold is a non-monotonic function of the threshold as the curvature and the weight of the distribution of each type of athlete change significantly in the $1-8$ range of the table.

Under these weaker assumptions (pun intended), only when the threshold for inclusion passes 5 standard deviations from the other gym goers' mean do powerlifters become the majority of the qualifying athletes. Unless the gym is full of football players (that's american football), weightlifters, and strongman competitors, I think these assumptions are too unfavorable to powerlifters.

Here are some strong athletes moving metal, for variety (NSFW language):

"While they squat I eat cookies" has to be the most powerlifter-y sentence ever.

Update Nov 11, 2016: Here's the percentage of powerlifters in the population of qualifying athletes for different assumptions about the advantage of powerlifters (i.e. the mean of the powerlifters' distribution in standard deviation units); click for larger:

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* Unless there are CrossFit-ers in the gym, in which case what we typically see in the gym is dangerous, counter-productive nonsense.

Kicking "Angels and Demons" while it's down

First, the ever entertaining Cinema Sins:

Now for some science. Let's assume that the stolen vial contained 1 gram of antimatter. Then, the explosion would release $E = mc^2 = (0.002) \times (3 \times 10^8)^2 = 1.8 \times 10^{14}$ Joule. At 4.184 petajoule per megaton of TNT equivalent, that is an explosion of roughly 43 kiloton.

(The more observant readers will notice that there's two grams in the energy computation. That's one gram each matter and antimatter.)

The operational ceiling of helicopters is around 25,000 ft, but the helicopter piloted by Ewan McObi-Wan Kenobi is nowhere close to that altitude when he jumps. An air burst of 43 kiloton even at say 10,000 ft would create a lot more damage than shown in the movie. (For comparison, Hiroshima's burst was at the yield-optimized height of 2,000 ft and with a yield of about 15 kt.)

So Ewan McThe Ghost Writer would probably be a carbonized carmelengo rather than a usurper to the Vatican throne. And probably so would the faithful in St. Peter's square and the Cardinals in Busch Stadium The Sistine Chapel.

- - - - Fait divers - - - -

Here's the page that CERN put up to address the errors in the movie.

Nikolaj Lie Kaas, who plays the assassin, plays the corrupt CEO of the energy company in the recent Danish series "Follow The Money." I guess he's typecast as the sociopathic type now.

I claim extra nerd points for using RStudio to do the computations (was already open; it's pretty much always open these days):

Gravity "batteries"

When there's too little demand for electricity, certain grid operators (like the Portuguese one) use excess capacity to pump water from downstream of dams to the dam reservoir. This is a way to store energy for peak demand.

I understand that some mountainous region is studying the possibility of replicating this with a funicular that would operate as the water in the dam. The losses involved in moving the funicular imply low roundtrip efficiency (the ratio of the energy recovered to the energy entered into the "battery"). And, of course, the funicular can't be used for passengers, unless there's some special discount for unpredictable schedules.

At least two people have told me about a start-up (I forgot its name) that wants to solve the battery problem by using the same approach, only with dedicated masses on vertical tracks.

The tragedy of engineering is the murder of beautiful illusions by ugly numbers.

Let's say this company can use $100\%$ roundtrip-efficient motor/generators, that is, all the electrical energy that is converted into potential energy of the moved mass can be recovered as electrical energy with zero losses in the whole process. (Yes, this is a ridiculously generous assumption, but it won't matter.)

Say this company has a 1000 metric ton mass that can be raised up to 10 meters. It can therefore accumulate $98$ megajoule (MJ) or $27.44$ kWh. Sounds ok-ish for a battery, except:

1. If that mass is made of lead (density = $11.34$ kg/l), a cheap-ish dense material, its volume is 88.2 cubic meters. That's large for a battery: it's a cube almost 4.5 meters on the side. Remember that this assumes $100\%$ roundtrip efficiency motor/generators.

2. Gasoline has an energy density of $32$ MJ/l and jet fuel has an energy density of around $30$ MJ/l; using a readily available commercial-grade combined-cycle generator with around $65\%$ total efficiency, 98 MJ can be generated with less than 4 liters of jet fuel or gasoline.

Okay, the combined cycle generator takes some space, but so do the motor/generators and the support frame for the 1000 ton mass. And the space for the vertical track, of course.

Numbers. Killing illusions. No wonder so many people avoid them.

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To make up for the bursted bubble of delusion, here's the feel-good video of this week:

Aging engineers versus experienced engineers

There are growing complaints that Silicon Valley companies discriminate against middle-aged engineers. But it might not be just ageism, it might just be aggregation error.

Engineering comprises mainly two things: a body of knowledge and a problem-solving mindset. To be a good engineer one needs an up-to-date body of knowledge in the relevant field and a facility with different problem-solving approaches used in the field (and possibly outside it as well).

(For the moment let's leave aside the problem-solving mindset; its dynamics are complicated and very situation-dependent: while some engineers acquire and develop problem-solving skills with experience, other fossilize their thinking, for example due to organizational practices.)

As part of what I do is continuing education, I have observed the dynamics of the body of knowledge as engineers' careers progress.

• The largest group by far (sadly), makes little attempt to keep up-to-date with their field after formal education ends. In conversation, after a corporate training event, a member of this group told me that keeping up-to-date was "very nice in theory, but we don't have the time." All of us would like more time; but this person spent tens of hours per week watching TV. One of those hours per week spent updating their skill set would mean 52 hours per year, which would be more than enough (most of the participants in that event had fewer than 20h/year of training or study, and self-paced learning can be much more effective than group events.)

• Most of the remaining engineers realized their technical obsolescence would become a problem and were retooling themselves for a management job. The main problem with this attitude is that there will always be fewer management jobs than engineers who plan to go into management. Secondarily, firms have both partially replaced management jobs with consultancy engagements and started prioritizing management-trained applicants over engineers.

• A few engineers fell into a third category: those who keep up-to-date either because they realize the job implications of doing so or because they really love their engineering field. The problem, for those in this group, is that their small number makes them liable to be categorized into one of the other groups.

Placing ourselves in the position of Google, for example, the decision to consider a candidate who's been out of formal education for several years versus considering one that's just graduated --- even if Google believes that the energy of youth can be balanced by the temper of experience --- comes down to which of the three groups above the older candidate will fall into.

In the absence of good information, statistically the older candidate will be in the first group, in other words, aged, not experienced, a distinction that most of the engineers can but will not make (as it defeats their case).

(The younger candidate's type is irrelevant, because being fresh from school means an up-to-date skill set, at least for the near future.)

There are obviously many confounds: consider a choice between a newly minted computer engineer from Idaho State - Tubertown with no code to show (not even from school projects) versus a 45-year-old Caltech graduate class of '95 who has code on GitHub that is particularly relevant to the job, for example.

For the other engineers, who have been lax in their updating of skills, there's a solution: it's never too late to learn. And then: show, don't tell.

Much ado about "loving" science

Science identity products

Science identity products like t-shirts, mugs, posters, and computer wallpapers are used to signal that the owner has an interest in science; unfortunately, because this interest in science has become fashionable -- at least in some segments of the population -- poseurs also buy these objects, lowering the quality of the signal.

I've written often (one, two, three, four, five times at least) about the problems with using science as an identity product, as with the people who "love science" as long as they don't have to learn any.

These products aren't necessarily only appealing to poseurs, though. People with a real interest in science and in science education also like them for, among other reasons,

1. Identity signaling. Like the poseurs, except it this case it's a real signal. People want to communicate their interest in science and the beauty of some scientific results and natural phenomena. (I own quite a few science identity products myself.)

2. Recruitment. These products can be useful motivators for bringing newcomers into an appreciation of science. By showing that there are other nerds geeks people interested in science, they create social conditions for others to come out as nerds geeks people interested in science.

3. Mere exposure. People like or at least feel more comfortable with things that appear familiar. The more exposure people have to scientific concepts and images, even if as part of jokes or background material in sitcoms like The Big Bang Theory, the less aversion they may feel when science content is presented to them.

There's one possible disconnect undermining these three points, though: that people who are influenced by exposure to the science identity products only like the aesthetics:

The big problem with the poseurs, which is a real problem not just my "I liked that band before it was cool" complaint, is not that they use the products to pretend to like science, though that would be bad enough. The real problem is that poseurs know that they don't actually like (or know) real science, so they feel threatened by those who do and take action to counter that threat, usually distracting from the science.

As my previous post showed, many poseurs in the media try to be "sciencey" but they fail miserably because in the end they don't understand that science is not like literature or art where the judgment of some other people is what matters. In science, reality is what matters. Poseurs don't get that, because to them reality is whether others buy into their pose.


Popular science content

Making science accessible to the general public is one of the most effective ways to improve society: it allows more people to partake of the benefits of knowledge (for example, avoiding junk science and quackery), it helps garner support for scientific enterprises that require public funding, and it creates the foundations for new generations with more and better scientists.

The problem is that popularizers can be real science popularizers or they too can be poseurs. And the poseur popularizers tend to be more popular. The glaring exception is Carl Sagan, but that's because he was both a pioneer in popularization and a real research scientist prior to that.

The most obvious difference is that Carl Sagan's Cosmos was designed to impress people with the power of science, while many current popularizers design their programs to impress upon the audience (a) how special they, the audience, are; and (b) how smart, knowledgeable, and suave the popularizer is. There are some exceptions, but they aren't the most successful popularizers, at least not on TV.

A rule-of-thumb that works for me is to ask whether the popularizer is an active researcher (or was until recently active) in the field. People whose job is some variation of "science popularizer" tout-court, even if they have some scientific training (which many of them don't), tend to focus on people and events rather than concepts and principles. In other words, they popularize the story of science rather than the actual science. (In many cases they either avoid the science completely, or they get most of it wrong.)

This rule works for two reasons:

First, an active researcher will know the science better than a non-researcher popularizer. This IMNSHO more than balances any communication advantages the non-researcher might have. One of the hilarious examples of this advantage is The Igon Value Problem, where active researcher Steven Pinker takes on the intellectual lightweight Malcolm Gladwell. (But supporting my observation above, Gladwell is more popular than Pinker.)

Second, an active researcher has to protect his/her reputation in the field. This adds motivation to get things right to the knowledge (the ability to do things right). When no one in Astrophysics takes you seriously (because you  call yourself a scientist but your career total citations of 150 mark you as a museum manager), you can say ignorant things on twitter about planes and helicopters. An engineer who wrote nonsense like this would be mocked at any future technical conferences he/she attended:

Personally I decided to read textbooks in lieu of popularization books,* but there are some popular books I've read that I found worthy of recommendation, so here are two for now:

Why Zebras Don't Get Ulcers, by Robert Sapolsky. (Sapolsky teaching at Stanford.)

The Black Hole War, by Leonard Susskind. (Susskind teaching at Stanford.)

Deep science (or other technical) content

Leaning technical material is something that requires audience (perhaps in this case "student" would be the better term) participation.

Lectures can motivate study and are a good introduction to the material, but only self-paced study and practice exercises can make technical material stick.

There's a qualitative difference between (to quote again from my old post about Heisenberg) understanding that this is a joke, i.e. popularizer-level understanding:

Police officer: "Sir, do you realize you were going 67.58 MPH?
Werner Heisenberg: "Oh great. Now I'm lost."

and being able to completely spoil the joke by computing the actual uncertainty (deep understanding):

A simplified form of Heisenberg's inequality, good enough for our purposes, is 

$\qquad \Delta p \, \Delta x \ge h $ 

Going by orders of magnitude alone, assuming that the mass of Heisenberg plus car is in the order of 1000 kg, and noting that the speed is given to a precision of 0.01 mi/h, an order of magnitude of 10 m/s, with $h \approx 10^{-34}$ Js, we get a $\Delta x$ of the order of 

$\qquad \Delta x  \approx \frac{ 10^{-34} }{10 000} = 10^{-38}$ m.

Only practice and study can create the kind of deep understanding that allows you to spoil people's fun at parties with numerical sidebars like this. Certainly something to aspire to...

That's not to say that lectures don't have value; I think of them as the warm-up sets you do before actually exercising. In that sense, they are very important, since they provide a passive experience that gets the material into context, setting up the active experiences of self-paced study and practice exercises.

Walter Lewin, shamefully retconned out of OCW and their official YouTube channels by MIT for undisclosed non-scientific transgressions, was one of the best Physics instructors online; even better than Feynman, since Lewin used actual in-class demonstrations and calculations matched to the examples. Here's a great class on standing waves:

As for most MOOCs, I already wrote my views in my post "MOOC-rize this," and the TL;DR is:

1. MOOCs have economies of scale in production and diffusion, but the difficult parts of education, personalized attention, for example, don't scale.

2. MOOCs can derive brand equity from the institutions associated with the teaching, but whether that brand equity is deserved is an open question: there are many components to education beyond what most MOOCs offer. I made some observations about that regarding the Kenan-Flagler Online MBA.

3. MOOCs built out of classroom teaching and associated materials are audience-targeted; a course like Lewin's works well at MIT and possibly CalTech, but the speed of exposition and the amount of off-classroom work that Lewin expected from his students will not work for most other universities. Other materials, like textbooks, may partially make up for this, but even so most students would probably prefer better match between materials and audiences.

4. The major weakness of MOOCs as they exist now is the lack of evaluation and, in many cases, of ways to check your exercises. Since audiences (students) learn from these exercises, done individually and then corrected by a knowledgeable instructor, this is actually a much bigger weakness than I noted on the "MOOC-rize this" post.


In conclusion

There's nothing wrong about being out and proud as a nerd geek someone who likes science; take care to avoid poseurs, both individuals and media darlings who don't have a track record of research; and if you want to learn more (kudos to you), there are plenty of MOOCs and other free resources to help you. One of those resources is called a Public Library and for the effort of getting a library card you can get a good education because in the end what matters is that you want to learn.


In the end what matters is that you want to learn. Poseurs don't want to.




-- -- -- -- -- -- FOOTNOTE -- -- -- -- -- --

* I find textbooks to do a better job than popularization books since I want to learn things at a more proficient level than a passing understanding. This requires time and effort, but I like it. (Hey, I lift heavy weights for no reason other than I like lifting heavy weights, so this isn't that different.)

The one enormous barrier to this approach is the ridiculous cost of textbooks in the US. I was interested in molecular biology, so I got Molecular Biology of the Gene, I believe for its weight in gold. There's now a new edition which costs its weight in diamonds, so I won't get that. Note that this is a personal interest in molecular biology; this is not work-related or anything monetizable, so the $\$200$ are a hobby expenditure. Which is fine, but still could discourage others from buying such an expensive book for a hobby.

I rationalize the cost by reminding myself of an old business associate who spent $\$150$ on a date with someone who, according to his later report, made Lady Macbeth sound warm and cuddly. So, that's about 3/4 of a textbook he could have bought there...

Ah, "science" in the media, always good for a laugh

There's nothing wrong with the idea of science in the media, per se: I want more and better science in the media. But there's a lot wrong when people who clearly don't know any science write (or illustrate) pieces about science or related matters like engineering, the environment, and space exploration.


The Wall St. Journal, where people who don't understand basic Physics units write tweets about trading systems designed by hordes of Math and Physics PhDs:

With friends like Engadget "green" writers, the environment won't improve.

The Motley Fool, being its foolish self.

That's it for September. A lot of incipient posts in the hamper, but paid work got in the way of blogging. Such is life.

Carbon capture, perpetual motion machines, and IGORs

There's one quick rule to evaluate energy-related technologies: if you can turn them into perpetual motion machines, they aren't real.

In conversation with an IGOR (Ignorant Grandstanding Oblivious Rabble-rouser), I pointed out that the idea of using atmospheric carbon dioxide to make fuel isn't entirely new (Nature did it first), but the technologies being proposed aren't realistic, for the reason above.

IGOR countered that these processes could, in his view, be the solution to our energy crisis (do we have one?), because the fuel produced by carbon-capture will provide the energy to keep the process going.

Ahem. Let's think about this, with a diagram:

What reasonable people say is that the energy extracted from the fuel will partially cover the energy needs of the capture and conversion process (that is $x > y$ but not by much); what IGORs say is that $y>x$. But if that were so, we could feed the exhaust from the energy production system into the input for the capture system, and get a perpetual motion machine that generates free energy.

Some of the more reasonable proponents of this carbon-capture and conversion idea suggest that the energy coming in can itself be green energy, like solar, and therefore there's a net "carbon-based" energy coming out of the system. Two points:

First, that's fine, but then why use part of that solar energy to create carbon-based fuels, instead of using the solar energy to replace the carbon-based fuels? Note that any $\mathrm{CO}_2$ that gets turned into fuel will yield another $\mathrm{CO}_2$ after the energy generation (conservation of the carbon), so no advantage there.

Second, the designs proposed look extremely wasteful of energy: capturing $\mathrm{CO}_2$ after it has diffused into the atmosphere is bound to require a lot of energy to flow non-$\mathrm{CO}_2$ gases in the atmosphere through the carbon-capture process. Better to stop $\mathrm{CO}_2$ at the source, if that's what you're after.

Of course, as I mentioned, Nature does provide us with a technology to use solar power to capture $\mathrm{CO}_2$ and turn it into fuel:

It also has the advantage of being pretty, giving shade, operating in silence, and bearing fruit. Trees. It's trees. Let's plant more trees. I like trees.

One particularly oblivious IGOR insinuated I was anti-environment because I prefer trees to useless noisy subsidy-harvesting machines.

With friends like that, the environment is doomed.

The problem with wireless earbuds for audiophiles

(The lack of an headphone jack on the iPhone 7 upset many people, but not me. I generally don't use my iPhone as a source of music, and if I were to do so in the future, I'd use an external DAC/Amp.)

To see why the wireless earbuds are a problem for audiophiles, we need to begin at the opposite end of the process, when analog signal (music) becomes a digital representation.

There are two steps in the process: first, the continuous analog signal is sliced in time, "sampled," so that it's now represented by a sequence of analog levels; second, those analog levels are compared with a finite scale, the digital scale, and the best approximation is used to represent the level, thusly:

There are two sources of information loss (or "noise") in this process:

1. By taking level slices of a continuous curve, the sampling creates an imperfect representation of the curve; that's called sampling noise. The longer the slices, that is the less often the analog input is sampled, the higher this sampling noise. 

2. By forcing the analog samples, which are on a continuous scale, to match the limited levels of a digital scale, the process creates a second type of noise, quantization noise. In the above example, the difference between the digital output for periods (1) and (2) is higher than the difference between the analog samples for those periods. Also, periods (2) and (3) have the same digital output, despite the different analog sample levels.

To reduce sampling noise we can sample more often, that is have thinner slices of time so that there are more analog samples to represent the same curve. To lower quantization noise we can have more digital levels; typically the number of levels is a power of 2, since we use binary coding.

For example, CD encoding used 44,100 samples per second per channel at 16 bits of resolution (allowing $2^{16}$ or 65,536 different levels); this was deemed enough for music since it allowed for an upper frequency limit of over 20 kHz (generally considered the limit of human hearing) and a dynamic range of 96dB (each bit adds 6dB; the choice of 96dB was widely panned by audiophiles as too small).*

As with everything in engineering (and in life, really) this was a matter of trade-offs. Later we've gone beyond these limits with other standards like SACD, for example. But the problem of trade-off remains, typically that of space or bandwidth against quality of reproduction.

Before compression, the total number of bits necessary to represent a stereo signal sampled at a rate of $s$ samples per second and a number of digital levels $2^{N}$ is $2 \, s \, N$ bits per second; because there's a lot of redundancy in music (no, it's not just Philip Glass), there are opportunities for compression.

Sometimes the music is compressed without losing information, called "lossless compression"; an example is FLAC, which has all the information necessary to reconstruct the original uncompressed digital music file. This is similar to compressing a data file for transmission; after decompression the reconstituted file must be identical to the original. (FLAC uses regularities of music to compress data more efficiently than a general compression algorithm.)

Sometimes the compression loses information that is deemed unnecessary, called "lossy compression"; MP3 compression is lossy. Lossy compression adds sampling and/or quantization noise to the original data, though the design of the compression scheme is supposed to minimize the aural effect of those additional errors in some trade-off with the compression ratio.

On the other hand, because plastic CDs and wireless signals sometimes get damaged, some space or bandwidth has to be used for error-correction codes and other digital administrative minutia. When the iPhone connects to the earbuds by wire, it can send an analog signal, but when it connects via Bluetooth, the signal is digital, must be compressed for transmission and requires a lot of network administration detritus.

So, one of the first questions wireless earbuds raise is: is Apple sending enough data over that Bluetooth connection for an audiophile? This isn't the only question, though.

Using the very best in advanced engineering CAD displays, we can see that this is only the first of four classes of problems:

Problem class 1: Quality of the Data

Apple's decision to go wireless changes the transmission of data between the main processor and the digital-to-analog conversion from a wired connector inside the phone, and protected from most interference, to a digital transmission over a noisy channel (Bluetooth). That means that a lot of other things have to be transmitted, in particular handshaking data, error-correction codes, and diagnostic signals.

The problem is mostly that Apple went from being a perfectionist's personal fiefdom (during the reign of His Steveness, may his divine hand bless you with a bounty of new MacBookPros) to being a company looking to make a buck. And companies looking to make a buck make different trade-offs.

His Steveness wanted the best. He might not have gotten it always, but he made products for people who wanted to brag they had the best. (Even when by all objective measures they didn't.) But now, the whole company seems to be into the "milk our brand while it lasts" phase of its corporate life cycle, so I'd venture that their trade-offs are much closer to the general public's than those of the fringes.

His Steveness run the company targeting the fringes, so that the general [Apple-buying] public could pretend aspire to be in the fringes. Depending on who you ask that's "aspirational marketing" or a "reality distortion field."

Not anymore. Not for Apple.

Taking a lossy compression like MP3 and compressing even further for the earbuds (possibly limiting both the frequency and the dynamic ranges) isn't a recipe for audiophile sound. It does work for phone calls, and that's probably what most phones are used for. But for music... no.

(At this point I should mention that digital audiophiles have moved on from Apple a while ago, putting up with miserably bad less than optimal interfaces to use things like —to go entry-level— a second-generation Fiio X5.)



Problem class 2: Quality of Digital To Analog Conversion

A second source of problems is the digital-to-analog conversion circuitry. Among the many problems that can come from a cheap (and low-power, which is important in wireless earbuds) DAC, the most obvious are reproduction errors (the same digital input doesn't map to the same voltage consistently, or the difference between digital levels doesn't match to the appropriate difference in voltages). This isn't that much of a problem in 2016 (it used to be in the 1990s).

Another, more serious problem has to do with the precision of the timing, which is one of the major reason why if you care about computer music you'll get an external DAC, possibly a Chord Mojo or an Audioquest Dragonfly. (Or maybe something from the brand that can't be named.)

Even small errors in timing (some of which are induced by the buffering and data processing necessary to extract the digital music from the wireless signal) can lead to significant phase distortion, in that the 'time' used to reproduce the music doesn't match real time.

To illustrate this problem, consider the following phase-distorted sine wave (slightly exaggerated to make the case visible, but even very small phase distortions sound horrible):

Comparing the two periods of the distorted wave, T1 and T2, you can see that phase distortion in this case induces frequency variation. This means that instruments will sound as if they are out-of-tune, and [if you're over 30 you'll get this reference] like your brand-spanking-new iPhone is a cassette player running out of battery power.

If you accidentally downloaded a [poorly encoded] FLAC file from a torrent site you accidentally fell into while looking for a French Literature study group, accidentally run that FLAC file through a FLAC to MP3 converter that you accidentally had on your computer, then accidentally played it and noticed strange warbling and high pitch glitches, that's an entirely accidental observation of very bad phase distortion.

This is why any audiophile wants a DAC that uses its own timing circuitry and buffer, rather than depend on the shared circuitry involved in network management etc.



Problem class 3: Fixed- vs Variable-Gain Analog Amplification

Many computers (and I assume all iPods and iPhones) have a fixed gain amplifier for the reconstructed analog signal. That means that changes in volume are created by multiplying the digital signal by digital fractions prior to conversion to analog. In essence, removing data from the signal.

For example, to halve a digital number, all you need to do is shift all bits right, disposing of the lower-significance bit and adding a zero at the highest significant bit (or, depending on how negative numbers are encoded, adding a copy of the previously high bit). This means that one bit of data has been lost. The sound is not just half-volume, but also half-dynamic range; each halving of volume removes one bit or 6 dB of dynamic range:

$\texttt{[1000101001011011]} \rightarrow \texttt{[0100010100101101]} \rightarrow \texttt{[0010001010010110] }$

If the original dynamic range of the data was higher than that of humans (CD or CD-derived online purchase or stream? No, it wasn't!), then this loss isn't important. Otherwise (i.e. basically always), your music just became lower resolution.

In a better sound system (i.e. any external DAC/amp), the analog signal out of the DAC goes into an analog amplifier that has variable gain. In some systems the variable gain is controlled with a knob, in others using a digital interface. But in both cases the amplifier tends to be a digitally controlled variable gain amplifier, in which the analog signal path is all analog and only the gain is controlled by a digital system (typically a feedback network of switchable topology).

(An alternative approach is to take the, say, 16-bit data and shift it 8 bits up into the most significant bits of a 24-bit word, then multiply that by an 8-bit fraction (thus allowing for 256 different volume levels) and feed the result to a 24-bit DAC, whose result will feed a fixed-gain amplifier. This allows for the whole process to be digital as long as possible.)

The amplification issue alone is worth getting an external DAC; but it's important to also consider the next point.

(My Audioquest Dragonfly is usually plugged into a powered USB hub, so it doesn't rely on the computer USB bus power.)


Problem class 4: Power issues

And this is the big big one. You like loud music? Well, expect distortion as soon as the volume gets loud. Because most of these small batteries aren't able to deliver the current needed fast enough. So what happens is that as the output voltage increases by $\Delta v$, requiring a $\propto (\Delta v)^2$ increase in power, the amplifier "fixed" gain starts to decrease, more so the higher the $\Delta v$, and we get... well, we get this:

That compression of the sine wave makes it sound nasal. When your music sounds like that, it's a sign that your amplifier is not being able to draw enough power. Note that this is different from the clipping that happens if the transistors in the output stage enter the saturation regime; in that case, instead of a smooth scrunched sine wave, we get a flat-volume squared wave, which makes everything sound like a heavy metal guitar.**

Ever wonder why 100W audiophile amplifiers have external power supplies that look bigger than the 1000W power supply on a computer server? That's because they are. Abundant power is an essential part of clean amplification, and without clean amplification the rest doesn't matter. And the way you get abundant power is you have a lot of slack available.

Care to bet how much slack power those earbuds have?



Does it matter?

To whom?

To me, no. I have a number of other, better sources of music, and I use the iPhone as an internet device and, astonishingly, as a phone. Weird, I know.

To those who just want to listen to podcasts, audiobooks, maybe some music in noisy environments? Of course not.

To an audiophile, who for some unexplained reason doesn't get a cheap lossless player like the Fiio X5? Yes, it matters, but this audiophile has the option to get the new Audioquest Dragonfly RED, with a tail adapter for the iPhone, so that's what s/he should do. Pair that with a nice pair of big cans like the Sennheiser 650s (in my opinion the best quality/price cans on the market), and you're set.

To an audiosnob who can't tell the difference between 866kbps Apple lossless and 32kbps mono MP3 but insists on having "the very best," preferably Bang & Olufsen or some other design-heavy, sound quality-light, high-reconition brand? Yes, it will matter a lot. (Audiosnobs have already invaded Head-Fi and other audiophile forums arguing against the iPhone 7 from their usual position, ignorance.)




-- -- -- -- Footnotes -- -- -- --

* Yes, the Nyquist limit for 44.1 kHz sampling is 22.05 kHz... as long as the anti-aliasing filter is a perfect step function in the frequency domain. The universe containing exactly zero perfect step function anti-aliasing filters, I and the entire engineering profession prefer to hedge by saying that it's "over 20 kHz."

When audiophiles say that LPs (Long Play records,  aka "vinyl," Olivia Wilde not included) have better sound than CDs, they are usually referring to dynamic range. It's not just that CDs have only 96dB of range, but much worse, that in transferring the music from the master recordings to CD, sound butchers engineers would monkey about with the original dynamic ranges to "make it fit better," which was disastrous for music with broad dynamic ranges.

(The standard example is the butchery of Dire Straits' "Money For Nothing," which was so compressed for the CD that it lost the whole point of the intro. Hey, though I listen almost exclusively to art music and jazz, nostalgia has its place.)


** That's because the sound effect that makes electric guitars sound like that is precisely pre-amping the sound so high that the output stage transistors will saturate and clip the waveform square, at the same time removing almost all volume envelope effects. You can do this to any instrument including voice.

Added later: yes, I know all these effects are digital now. Kids these days! In my day you built your effects with transistors, µA741s and sometimes NE555s. None of that "digitize, FFT, do whatever, convert out" nonsense. We had grit!

Multitasking at the gym

Powerlifting and other training (including conditioning) are not multi-taskable. It's very important to keep one's concentration and focus on the exercise. I cringe when I see people talking with each other while moving metal. Even during warm-up sets; perhaps especially during warm-up sets, when the low weight allows one to do a preflighting of the movement, check for any anomalies in mobility or weak or sore prime movers or stabilizers.

When walking short distances, cooking, or doing housework, I tend to listen to podcasts or sometimes to the audiotrack of YouTube hangouts (basically the equivalent of radio's Morning Zoo). These are ways to get some low-density information into the brainpan without distracting too much from the errands. (I also listen to podcasts on shared transportation, like shuttles. Too much entropy for anything else.)

Some podcasts I listen to (there are more; I usually only listen to a few episodes a week):

(Yes, I have a significant déformation professionelle.)

When I go for a real walk, what I call a walk-n-think, I typically listen to music, not any sources of information. The point is to think and clear the cobwebs of my mind. I find the Baroque a particularly good cobweb-solvent period. Here's a walk-n-think with a side-trip to exchange books at the SFPL:

Once in a repetitive-motion machine in the gym, for oxygenation not conditioning purposes, the main determinant of the type of content is the movement of the head, in particular the eyes.

When walking on treadmills (my preferred cool-down approach) or rowing on a machine (which for me is real exercise, but of form and rhythm, not muscle), the head moves too much to fix the eyes on a screen; as the activity itself requires less attention than the errands, freeing attention for content, my choices of media are audio lectures and audio books.

(I only run on treadmills for High-Intensity Interval Training, which is conditioning, which means it cannot be multitasked. When doing anything that stresses the body, I always want 100% of the attention to be on the exercise. I have this strange desire to avoid injury, ridicule, and absence of gains; sort of the philosophical opposite of CrossFit.)

I should clarify that I'm using "lecture" to mean all sorts of purposeful speeches, not just university lectures. I do have a number of these speeches and lectures which work out well, many of them extracted from videos of talks where there were no significant visuals (or the visuals were the dreaded "power points," which are speaker's notes not audience-centered visuals).

As for audiobooks, I've been a Platinum member of Audible for fifteen years, which means I have two new books per month, which I complement by filling up on the seasonal sales and the occasional extra purchase.

Here are a few of my latest Audible purchases:

 On average I listen to around 30 audiobooks per year, some of which are re-listens.

(Yes, I re-read and re-listen to books. There are some books I read pretty much every year… Waugh, Wilde, and Wodehouse; certain Poirots and Maigrets; a few favorite Discworld pieces. There are 1000-page books I read every year, though that's just Anathem. And Cryptonomicon. And Reamde. And Seveneves, now on its second year. Guess who my favorite living author is.)

For other machines, like elliptical runners, stairclimbers, and exercise bicycles, the head doesn't move, so it's feasible to use the eyes. My old-but-trusted iPad 1.0 has seen this gym duty pretty much from the first day I bought it, which was the day it came out. (100% impulse purchase, as I was coming back from brunch and passed an Apple Store.)

Though in the past I've read books (paper books), journals (academic magazines), and magazines on paper on these machines, and have evolved to read electronic versions of these, I find that I prefer to give the eyes a break by letting them watch video instead of processing written words. I tend to watch lectures (again including speeches, but in this case a lot more real lectures) on the elliptical and the stairclimber, and to read books (ebooks with large type) only on the exercycle.

(Basically I use elliptical, exercycle, and stairclimbers in my building exercise room. It's not a "gym event," rather a "I need to take a break and instead of vegetating in front of the TV, which I no longer have service for, I can go do some movement while imbibing some basic knowledge.)

I keep a Rite-in-the-rain notebook and a Fisher space pen nearby in case I want to make notes, something that confuses other users of our exercise room. And that others have started to copy.

I hasten to point out that despite the déformation professionelle mentioned above, I tend to think of these books and lectures as leisure, so I keep them broadly within my areas of interest but not focussed on my actual area of work. For example, here are a few courses that I've enjoyed on the elliptical machines in the exercise room:

It's worth mentioning that real intellectual work cannot be multitasked, as indicated by the position of textbooks and research papers in the diagram. Anytime I'm looking to learn something, that requires dedicated attention, note-taking, and a block of dedicated time.

I don't mean work-related textbooks (though american textbook prices do their darndest to discourage the intellectually curious from serious study) or research papers (ditto with the gating, but public libraries and authors' own webpages are a good workaround), but even when I'm trying to learn something, say geology, our of pure curiosity, reading textbooks and research papers has been a much better experience than the materials that now pass for science popularization.

(My opinion on the decline of science popularization is well established in this blog.)

One thing I used to do at the gym (the real big gym, not the exercise room and not the powerlifting gym I occasionally go to instead of driving to the big gym) and eventually stopped due to social pressure, was to watch FoodTV network on the gym TV while cooling down on a treadmill or an elliptical, after 90-120 minutes of iron and conditioning. For some reason, those whose entire workout is 30 min of slow walking on the elliptical (what I call a Potemkin workout, still better than Planet Fatness or CrossFit) were not happy with my selection of programming.

Go figure.