Superman is boring

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Superman, as orginally described, was invulnerable. Having a hero with superpowers that are too strong makes for a boring story, because a good story needs conflict. There are several ways of handling that, of course.

1. Kryptonite weakens my powers

According to some accounts, kryptonite was invented specifically to make Superman less invulnerable and boring (Paul Fairchild explains why this was a bad decision). Kryptonite, of one kind or another, is a classic solution to the problem of an overly strong superhero which, to some extent, has been used by multiple authors. It can be overused, however. If your superhero is always weak, why have such a character at all? A better variation of this approach is for the protagonist to carry his or her own metaphorical kryptonite inside, as some kind of “fatal flaw.”

2. My powers come at a heavy cost

This is one of the easiest ways for an author to ensure that his or her character does not overuse their superpowers. These superpowers may cause pain, coma, physical harm, or other damage that enforces a break between uses of the superpowers. For example, the psychic Greg Mandel in Peter F. Hamilton’s Mindstar Rising and its two sequels suffers severe headaches when his powers are used to excess. Variations of this approach are used in a number of fantasy novels.

3. My powers disturb or frighten me

A good example of this option is Doctor Who, in the eponymous TV series, who often needs to be talked into taking action. The advantage of this approach is that it produces a great deal of interesting dialogue on why the superpowers are disturbing or frightening.

4. I am still learning to use my powers

This option is particularly common in young adult fiction. It allows the author to have an attempted use of powers either succeed or fail at any point; but this makes sense with a young protagonist. The young magician Pug in Raymond E. Feist’s Riftwar Saga is a good example. So is Luke Skywalker in the original Star Wars movie trilogy. To some extent, Aragorn in The Lord of the Rings can be viewed as having a combination of (3) and (4). But, however the author does it, I think that some limitation on superpowers is essential for a story to remain interesting. What do you think?

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Calendar for December

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Here is the calendar for December (click for hi-res image). The Earthrise photograph was taken 50 years ago, along with the Christmas Eve broadcast from the Moon.

See more calendars here.

Boyle’s law

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Boyle’s law is the principle that, at constant temperature, the volume occupied by a gas is inversely proportional to pressure (at least until the pressure gets extremely high). In symbolic terms, PV = k, where k is a constant. The pioneering scientist and amateur theologian Robert Boyle published this law in 1662, in his New Experiments Physico-Mechanical, Touching the Air (2nd edition): Whereunto is added a defence of the authors explication of the experiments against the objections of Franciscus Linus and Thomas Hobbes. The chart above shows the data he collected, together with a diagram of his apparatus and a scan of his original data table (cleaned up from an image in the Wellcome Collection).

Boyle’s apparatus involved an uneven U-shaped tube, sealed at the short end, and with mercury in the “U.” Further mercury was added to the long end, in order to compress the air in the short end to a specified volume. The pressure in each case (in inches of mercury) was the measured amount in the long end of the tube, plus 29.125 inches for atmospheric pressure.

Boyle’s experimental work was excellent, with all errors less than 1% (on my calculation). This is shown visually by the close fit of his experimental datapoints to the line PV = 351.9. His arithmetic was not quite so good – column “E” in his original table showed his predicted pressure, calculated laboriously using fractions. Seven of the 25 entries are incorrect. For example, using his approach, the 7th entry should be 1398 / 36 = 38 5/6, but Boyle has 38 7/8.

Home replications of Boyle’s work generally involve weights, a large syringe, some precarious balancing, and the fact that the air column sitting on a square centimetre weighs about 1.03 kg. Like so:

The Invention of Clouds: a book review

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The Invention of Clouds: How an Amateur Meteorologist Forged the Language of the Skies by Richard Hamblyn (2001)

I recently read The Invention of Clouds by Richard Hamblyn, who also wrote Terra (which I reviewed some years ago). The present volume focuses on the Quaker pharmacist Luke Howard, who produced a taxonomy of clouds in 1802. Essentially the same classification is still used today (but not, as Hamblyn points out, without considerable debate during the 1800s):

Although the focus is on Howard’s work and life, Hamblyn in fact provides a brief history of meteorology (or at least of the study of clouds), and there is a chapter on the Beaufort scale. Contemporary literature referred to includes:


Google Ngrams plot for three of the cloud types (with and without hyphens). The words “cirrostratus” and “cirrocumulus” first appear in reprintings of Howard’s pioneering essay, while the word “cumulonimbus” is introduced around 1887. There is a renewed spike of interest in cloud types beginning in the early 1940’s.

The Invention of Clouds also has some interesting comments on clouds in art and on how to get an education at a time when the two English universities banned non-Anglicans from attending. However, the book does have a few small errors. For example, cloud droplets are not “a mere millionth of a millimetre across,” but in the range 0.005 to 0.05 mm. However, that does not stop the book from being both enjoyable and informative (although I did wish for colour images). See also this review from the NY Times.


The Invention of Clouds by Richard Hamblyn: 3½ stars

Sundials!

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Above is an analemmatic sundial. The idea is to orient the sundial facing south, and then place a vertical pointer on the central figure-8 track, in a position corresponding to the date. The sundial above shows a simulated shadow for 2:15 PM yesterday. It can be seen that the sundial tells the time reasonably well, thanks to the inbuilt adjustment for variation in solar position.

For large-scale analemmatic sundials, like the one below, people can stand on the central figure-8 track and act as a human pointer. A sundial like this is fun to have in the garden.

Here are blank sundials for some Southern Hemisphere cities:

The ShadowsPro software will also generate sundials like these, if anyone is particularly enthusiastic.

Voting patterns in the United States

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Because of my interest in social statistics, I’ve been exploring county-level results from the US 2016 presidential election. The map below (click to zoom) summarises the results (blue for Democrat and red for Republican, coloured according to how strongly counties voted one way or the other). Nine of the more extreme counties are highlighted.

Most of the variance in this data can be explained by demographic factors such as race, age, education levels, local unemployment, rural-urban continuum code, and median household income. The latter is particularly interesting, and the chart below provides a summary.

On a scale from −0.5 being 100% Republican to +0.5 being 100% Democrat, the curve shows the average vote of counties by 2016 median household income (where the averages are weighted by county population sizes, and LOESS smoothing is used to draw the curve). Overlaid on the diagram is a bar chart for the total population of different median household income groups (the scale for this bar chart is on the right).

It can be seen that, at the very poorest end, votes are balanced between Democrat and Republican. For example, here are the 7 poorest counties in the United States, by median household income. They are all rural:

Above that bottom end, votes trend Republican, with the peak Republican vote occurring at median household incomes around $40,000. Above about $56,000, counties swing Democrat, and the Democrat vote increases with increasing wealth. For example, here are the 4 richest counties in the United States, by median household income. They are all part of the Baltimore–Washington metropolitan area:

Essentially, the Republican Party seems to have become the party of the poor, particularly the rural poor. Indeed, the (population-weighted) median of 2016 median household incomes for Democrat-majority counties was $61,042; while for Republican-majority counties it was $52,490 ($8,552 less). For a visual perspective, the map below limits the previous one to counties with a 2016 median household income below $56,000. It is precisely because the Republican Party has become the party of the rural poor that these maps are mostly red. I had not fully appreciated this before analysing the data (although others have), but it certainly explains much of recent politics in the US. However, predicting the results of the next presidential election would require some solid demographically linked polling data as well as a good voter turnout model.