Bacteria hardly any of us know

 kw: book reviews, nonfiction, science, bacteriology, surveys

Behold the largest species (so far known) of bacteria. Thiomargarita namibiensis, the "sulfur pearl from Namibia", at 300 or more microns in diameter, can be larger than the smallest parasitic wasp, shown for comparison. It is visible without a microscope, being the size of the dot of a printed "i".

This is the first species of microbe described in The Curious World of Bacteria, by Ludger Wess (originally in German, translated by Jamie McIntosh). The author made many difficult choices to select just 50 species of Bacteria and Archaea for this book. Although Bacteria and Archaea are different domains of life, most of us, specialists included, usually use the term "bacteria" to speak of them all.

If they think of them at all, most people consider bacteria to be primitive life forms. Few realize that they have been subject to the same 4+ billion years of evolutionary history as every other kind of life on Earth. Most are less than 10 microns (or 0.01 mm) in their longest dimension. A few are smaller than 1 micron. But they come in a wide array of sizes and shapes.

Even more various are their metabolisms. Many species don't need oxygen—some are killed by it—and "breathe" sulfur or hydrogen plus carbonate, or even iron oxide. The author points out that life is energized by the transfer of electrons, by oxidation and reduction reactions. I learned a mnemonic in chemistry class: LEO & GER. LEO = "Loss of Electrons is Oxidation". Leo is the Lion, who says "Grr" (GER), which = "Gain of Electrons is Reduction".

When we use oxygen to oxidize chemicals in our bodies to get energy, the oxygen is reduced: Electrons move from some molecule to the oxygen. This rod-shaped bacterium, Desulforidis audaxviator, reduces sulfur instead of oxygen. The rod-shaped cells are about 5 microns long, but very narrow, 1/3 of a micron. This critter is found in deep mines, where some populations have been out of contact with Earth's surface for 25 million years.

Many folks only know about "bad" bacteria. By the way, the Archaea are not pathogenic. None of them. So all disease-causing "germs" are Bacteria. 

Certainly some great plagues have arisen from specific Bacteria. "The Plague", or the Black Plague, is possibly the most famous. The cause is Yersinia pestis, where "pest" means Plague in European languages. Like many bacterial diseases, these need a vector, or in this case, two vectors: The rat flea and the black rat.

The Plague changed the course of European history, twice, once in the late Roman Empire ("Justinian Plague") and once again some 700 years later. It still crops up here and there, and is a lot more deadly than COVID-19, but because of indirect spread (fleas+rats), it doesn't pose as much of a threat.

This is a book to read right through, as I tend to do, or to browse here and there for interesting articles. Either way, it's very well written and very informative. The author is young enough to write a few more books; maybe he'll pick another 50 (he has thousands of interesting species to choose among!) and write a sequel. Luscious thought!

A fine mind ruined by Marxism

 kw: book reviews, nonfiction, biological evolution, philosophy, social justice, polemics

I was raised to care for what people can do, not what they look like. This was during the era of Jim Crow. I was 15 when Dr. King made his "I have a dream" speech. Once it was fairly reported (a chancy thing in 1963), I embraced its core idea: to judge people by the content of their character, not the color of their skin. For most of the sixty years since, I have seen the systemic racism I grew up within gradually abated. Progress in this area halted sometime after 2008 when our first black President showed by his actions that he liked to poke a stick in the eyes of anyone who wasn't a Leftist or Marxist. Overt racism began to rise again.

Judged against the past 15 years, racism in America has been on the rise. Judged against the prior 45 years, tremendous progress was followed by a significant pullback. However, there was a parallel trend that I have watched for more than the past 60 years, of creeping leftism that has gradually taken over the Democratic Party.

When I was in college during "the Sixties" there was radical activity all over the country, particularly on campuses. It was very visible for a few years, and then seemed to vanish. Later I realized that the wiser radicals didn't go on the stump, they went to Law school. Bill and Hilary Clinton exemplify them. They also exemplify the utter amorality of leftism.

I am a classical liberal, which means "conservative" in America. I am for smaller government, the greatest amount of freedom for the greatest number of people, for the rule of law and not by fiat ("executive orders" for example), and for a strong social attitude that supports personal responsibility and eschews blaming others for our own errors. The Left is against all these.

I was taught to be color blind; now that's called racism. It is the opposite of racism!

I was taught to treat everyone fairly; a few percent of people demand to be treated better than fairly. I decline.

Most particularly, I learned from the Bible that the people of God are not called to destroy the wicked (Jesus called them "tares", or "weeds") but to leave that to God. The Left is intent on destroying the good, and they began by demonizing everything that is good about America and vilifying "ordinary Americans" who happen to not be leftist. Leftism is the enemy of all that is good.

There is huge hue and cry about "white supremacy" and "institutional racism". One would think that all white Americans (except, of course, the Left) are arrayed in a crusade against all "people of color". Not so. Consider this: All the "institutions" have been taken over by the Left, including most news organizations, universities, and a growing number of businesses. If there is institutional racism, guess who is running the institutions? Not conservatives.

During World War II my father trained a squad of primarily black soldiers. He and they were all in the Corps of Engineers. His previous squad was primarily white. He told my brothers and me that the white soldiers were better educated, but neither squad had any engineering background. The two groups learned equally fast. Having grown up in a racist family, Dad got re-educated that "race" didn't mean anything, from his own experience. He took that lesson to heart.

Let me also mention that I am about as White as they come, without being Scandinavian. Most of my ancestors that immigrated to America were from England, Ireland or Scotland; none that I know of were Celtic. Throw in a bit of German and Welsh, and that almost completes the picture. I also have a grandfather who was between a quarter and half Cherokee, and a great-grandfather who had a black grandfather or great-grandfather. European Americans who don't hail from the British Isles are descended from Roman citizens and Roman slaves, which in both cases were 10% African. My nonwhite ancestry is about 15%. I am neither proud of it nor shamed by it. I am descended from serfs and kings, merchants and pirates, soldiers and criminals. What I am is what I am, no more, no less.

This is just a taste of my background, so you have a chance to understand my reaction to A Voice in the Wilderness: A Pioneering Biologist Explains How Evolution Can Help Us Solve Our Biggest Problems by Joseph L. Graves. The book is half memoir and half social observation with a strong "social justice" flavor.

Dr. Graves is the first African American to earn a PhD in Evolutionary Biology. He is seven years younger than I am, so when I was on campus heckling leftist radicals, he was in Jr. High School, not yet sure if he would go to college. As he tells it, he experienced pervasive racism all his life. Interestingly, his primary mentors were white; of course, there were nearly no black role models for him. Once he did enter college, before long he read Karl Marx and became a Marxist. It seems he still is.

I reserved judgment through the whole book. By the end, though, I became clear. Dr. Graves is a brilliant biologist, a leader and mentor in his field. Equally clearly, he is politically blind. The only sources of news he cites are CNN and other outlets of genuinely Fake News. He claims that the fakery is all on the right, but I've observed every trace of truth drain out of the "mainstream media" since midway through the broadcasting career of Walter Cronkite, about the time the Huntley-Brinkley Report went off the air in 1970. By the time Cronkite retired, the decline of "the media" was well under way.

The last chapters of the book are full of diatribes against Donald Trump and those who voted for him. This is what I would expect of a Marxist, and of someone who believes the extremely gross and misleading caricature of Trump found in nearly all the media. In one sentence he groups Trump with Stalin and Hitler. Seriously?!?!? Stalin assassinated several political opponents and upon achieving power he exiled hundreds to Siberia, where most soon died. He was later responsible for the deaths of more than 15 million Russians. And we all know Hitler's history. 

If Donald Trump were actually the man "the media" (and Joe Graves) think he is, the day after his inauguration he would have had Nancy Pelosi, both Clintons, James Comey, Chuck Shumer and probably several others arrested and summarily executed. Three years later, after his first weaselly speech about COVID-19, Dr. Fauci would have "disappeared". I could go on, but what's the point? Here's a plain fact that seems to have escaped Dr. Graves: During the Trump administration, unemployment fell to the lowest level is decades, and to record low levels for people of color. Donald Trump was the best thing that ever happened to "the Blacks and Browns among us", to use an oft-repeated phrase. Biden and the Left are their worst enemies. Those whom they can't gaslight they denigrate, sideline, and if possible indict.

I am wholly opposed to Marxism in all its manifestations. Of the four biggest mass murders of the 20th Century, three were committed by Marxist rulers (Stalin, Mao, and Pol Pot), and the fourth was perpetrated by "national socialists", abbreviated Nazi. The other genocides of the same Century were nearly all by Marxists. Dr. Graves wrote, "…Karl Marx was probably one of the greatest theorists of human social activity…" Idiocy! Mark's "theories" have always been carried out via enormous bloodshed and oppression.

I was hoping that the phrase in the title, "explains how evolution can help", would be followed up by a clear, cogent explanation with workable suggestions. That ought to have been the subject of the last 2-3 chapters, not diatribes against conservatives. What a pity. The idea that evolutionary thinking can help us solve great problems is a good one. A proper treatment of the subject would be very helpful. But the book is instead a screed in favor of Socialism. As Churchill wrote, "Capitalism is the worst system, except for all the others." Socialism is a formula for misery. Always has been, always will be.

How many EV batteries can we make?

 kw: analysis, lithium ion batteries, cobalt, resource limits

When I lived in South Dakota I sometimes visited the sites of abandoned mines. A number of these had mined spodumene, a lithium-bearing mineral that is famous in the Black Hills for forming gigantic crystals such as this one in the Plumbago pegmatite. It is 12 feet long and 3-4 feet wide (~4m x 3m). Crystals approaching 50 feet long (~15m) have been reported.

A pegmatite is a special igneous (crystallized from molten rock) deposit that formed in the presence of high-pressure water and cooled slowly, so large crystals were produced. Many gemstone mines are in pegmatites. For example, while there are often ruby or sapphire crystals in granitic rocks, they are usually microscopic. It takes "pegmatite conditions" for large (cm size) gem crystals to form.

Spodumene is the primary source of lithium around the world. Pure spodumene has the chemical formula LiAl(SiO₃)₂. To understand the physical economics of lithium mining, it helps to know just how much lithium the mineral contains. This table will help:

This presumes the pure mineral. Elemental lithium content is less than 4%. Ore grades are reported as the oxide, Li₂O, which comprises 16% of the pure mineral.

Spodumene in bulk is seldom pure. Its gemstone varieties, hiddenite and kunzite, are nearly pure and transparent, with coloration due to trace impurities. The "log" of spodumene shown in the image above is probably no more than 60% pure, containing iron oxide and iron silicate and other impurities. Spodumene ore is considered "good" when its composition of Li₂O is above 8%.

Also, a spodumene pegmatite seldom contains more than 15% of such "good" spodumene. The best spodumene ore in the world, found in Australia, has a Li₂O content of 1.6%. About 1% is more common. See this Wikipedia article for more detail.

What is needed to produce an EV battery? From a number of sources I find that a "typical" EV battery contains 8 kg of lithium, 14 kg of cobalt, and 20 kg of manganese in its cathode, the + electrode. Such a battery as a whole weighs about 250 kg, much of which is the casings (metal shells of the cells). By contrast, the battery in a Tesla Model S contains 62.4 kg of lithium. I haven't discerned whether the proportions of cobalt and manganese are the same, but that is probably so. The packaging is more efficient, so the Model S battery weighs 900 kg (about a ton).

What do the cobalt (Co) and manganese (Mn) do? They are part of the cathode, and increase its energy density. Much experimentation and optimization have resulted in this composition. One restriction is the scarcity of cobalt, seen in figures for known world reserves for these metals:

• Li: 89 billion kg
• Mn: 1,700 billion kg
• Co: 8.3 billion kg (9% compared to Li)

A battery made with Li and Mn but without Co is less efficient, but it appears we'll need to go that way anyway; batteries aren't the only use we have for cobalt.

So, what are the implications of replacing every vehicle with an electric vehicle? In the US there are nearly 280 million registered vehicles; worldwide, about 1.4 billion. Let's assume as an initial estimate that each one needs 8 kg Li, 14 kg Co, and 20 kg Mn. That works out to

• Li: 2.24 billion kg for the US and 11.2 billion kg for the world. So far, that's doable (NOT easy!)
• Mn: 5.6 billion kg for the US and 28 billion kg for the world. Ditto.
• Co: 3.92 billion kg for the US and 19.6 billion kg for the world. OOPS! Almost 2.4 times the known supply.

Using all known cobalt to make EV batteries using the currently-accepted technology, the number would be 590 million. Almost half of that would be snarfed up by the US, if that were allowed.

Extracting the elements produces lots of waste. In the case of Lithium, each kg produced is accompanied by 27.3 kg of waste if the spodumene is pure, and usually by 98-99 kg of waste. Cobalt and Manganese are heavier and their ores are a bit richer, but their production also yields enormous piles of waste material. By the way, seabed mining can't help much. The "manganese nodules" do contain a lot of manganese, but usually a nearly equal amount of iron; they contain less than a percent of cobalt.

All this is big, but it is actually the tail wagging the elephant in the room. Transportation uses about 30% of US energy consumption, and half of that is for private autos. In the world, the figures are 25% and 12%, which means for the non-US countries, private auto transportation is even less of the total, around 10%. Electric generation would have to increase mightily to support another half billion or billion EV's. What could be done to replace petroleum and coal used for electric generation, the other 80-90%?

Burning coal, oil, and natural gas are three of the four stable forms of electric generation. The fourth is nuclear fission. None of these depend on daylight, or wind, or tides. I am disregarding geothermal because its practical, widespread use is two or more generations in the future, at the very best. Hydropower is comparatively stable, but nearly all the hydropower available in the US is already being used, and worldwide, it cannot provide more than a few percent of the need.

The two big technologies that seem able to produce large amounts of electricity are solar and wind. Solar reached energy breakeven 10-20 years ago, and improvements continue. Wind power does not yet generate enough new electricity to replace what is used to manufacture, transport, erect, and maintain the equipment. Wind turbines also kill birds, lots of them, including eagles and numerous endangered species, but the industry gets a pass because of climate-change activism. Both technologies have variable output that depends on the time of day and the local weather. Thus, utility-scale battery storage is required. Tons and tons and millions of tons of batteries.

I could get into a rant here, but I'll stop with this admonition: we need new battery technologies that depend on neither lithium nor cobalt nor any "rare earth" elements (which aren't rare, just hard to separate from their ores). A 10x-100x increase in funding for battery research is definitely worth pursuing.

Scientific questions answered enjoyably

 kw: book reviews, nonfiction, answers, science, humor

Want to know the easy way to convert between °F and °C? On page 192 of  What Einstein Didn't Know: Scientific Answers to Everyday Questions by Robert L. Wolke, he explains the 40-40 method as clearly as any I have seen. We just need to remember 2 things:

1. A Celsius degree is 1.8 (or 9/5) as big as a Fahrenheit degree.
2. -40°C = -40°F.

Because the meeting point of the two scales is -40, first shift the zero point by adding 40. Then, if it's °C, multiply by 1.8, and finish by subtracting 40. If you're starting with °F, divide instead of multiplying: add 40, divide by 1.8, and subtract 40. Examples:

• Starting with 68°F: 68+40 = 108. 108/1.8 = 60. 60–40 = 20°C.
• Starting with 40°C: 40+40 = 80. 80*1.8 = 144. 144–40 = 104°F.

To do it without a calculator, if you can multiply and divide in your head but find 1.8 a hard number to use, to multiply by 1.8, multiply instead by 9 and then divide by 5; to divide by 1.8, multiply by 5 and then divide by 9. It's easiest to do the multiplying first. It's even better if the result won't be in even degrees. For example, to convert 56°F, add 40 (=96), multiply by 5 (=480), divide by 9 (=53.33...), then subtract 40, to get 13.33...°C.

Dr. Wolke passed away last August at the age of 93. I suppose this book is his last legacy. He wrote a number of books in the same vein. He liked to write about "Kitchen Science." In this volume he confines The Kitchen to one chapter of 24 pages, including the answer to "How does a simmer differ from a slow boil?" (Quick answer: The bubbles in simmering water seldom make it to the surface, but their presence lets you know the temperature is the same. Simmering saves energy.)

When explaining chemical and chemico-physical processes he takes us right to the molecular or atomic level. Even below boiling, for example, some water escapes into the air because the temperature represents the average of a range of molecular speed, and the faster water molecules find it easier to escape the liquid water into the atmosphere. Boiling means we've added enough energy to raise all (or most) of the volume of the water in a pot to the boiling temperature, so more energy just goes into driving water molecules into the air. They gather into bubbles on their way up from the bottom of the pan, where the heat is being added.

I remember when kids could get a Chemistry Set for a birthday present. Just about everything in those sets is banned today. Even in Chemistry class in high school, I've been told the teacher does nearly all the experiments in front of class, wearing lots of safety gear, and the students hardly have any lab time. You just can't learn chemistry by watching it!

Here and there in the book we find bits called "Try It". They are safe little experiments anyone can do with little or no equipment. Here is one from page 124 (next to a discussion of sublimation, or the evaporation of ice directly without passing through a liquid stage):

Measure the length of a convenient icicle during a cold spell. Then come back in a few days and measure it again. Make sure the temperature hasn't gotten above freezing in the meantime, so that there hasn't been any melting. You will see that the icicle has gotten smaller by sublimation.

I my experience it takes only a day or two for a noticeable change to occur, even in very frigid weather. In addition to answering questions he has encountered during a long career as a professor of Chemistry, he has items here and there titled, "You didn't ask, but..." One is "Why won't a candle burn without a wick?" (p 50) The answer is based on the need to get some of the hot wax above the surface of the pool of melted wax, which would cool it too much to burn.

The author encourages us to browse or even hop about, and many readers may enjoy doing so. I am a straight-through kind of reader. Either way, it's a great introduction to many less-well-known subjects, and offers a new take on some better known ones.

If BARD is a poet, I wouldn't know it

 kw: analysis, artificial intelligence, experimental linguistics, poetry

My first queries to BARD were related to Shakespeare. BARD bungled the iambic meter of a soliloquy. I decided to try poetry in a more general sense. I will comment in each section.

P07: There are 3 kinds of photosynthesis: C3, C4 and CAM. Please write a sonnet about photosynthesis in the Italian rhyming style.

Bard: Sure, here is a sonnet about photosynthesis in the Italian rhyming style:

Photosynthesis

The leaves unfurl, the sun shines bright,
And plants begin their daily flight.
They take in carbon dioxide,
And water from the ground below.
 
They use the energy from the sun,
To turn these things into one.
A sugar called glucose,
And oxygen, which is released into the air.
 
There are three main types of photosynthesis,
C3, C4, and CAM.
Each type has its own advantages and disadvantages,
And they are all used by different plants.
 
C3 photosynthesis is the most common type,
And it is used by most plants.
It is not as efficient as C4 or CAM photosynthesis,
But it is less demanding of water.
 
C4 photosynthesis is more efficient than C3 photosynthesis,
But it requires more water.
It is used by plants that live in hot, dry climates,
Such as cacti and succulents.
 
CAM photosynthesis is the most efficient type of photosynthesis,
But it is also the most demanding of water.
It is used by plants that live in very hot, dry climates,
Such as cacti and succulents.
 
No matter what type of photosynthesis they use,
All plants play an important role in the environment.
They help to clean the air,
And they provide food and oxygen for animals.

A sonnet has 14 lines. Here we have 28. The Italian rhyming style is ABBAABBA CDECDE, although there are various ways the last six lines are handled, including CDCDCD and CDDCDD. None of the quartos above has an ABBA rhyming pattern. Also, sonnets are typically in iambic meter, but none of that is found here.

P07: Please write a limerick about a coder named Larry

Bard: Sure, here is a limerick about a coder named Larry:

There once was a coder named Larry,
Whose code was as tight as a curry.
He could write in any language,
From C++ to Python,
And his programs always ran merrily.

This limerick was in a box, so maybe Bard copied it from somewhere…but it doesn’t rhyme lines 3&4. There were two other drafts:

There once was a coder named Larry,
Whose code was quite hairy and scary.
He said, "I'll rewrite it,
But first I must write it,
Then I'll test it, and then maybe I'll marry."
 
There once was a coder named Larry,
Whose code was quite hairy.
He said, "I'll rewrite it,
So it's not so tight,
And maybe I'll get a raise, maybe."

The first alternate draft is a near-perfect Limerick; just remove "and" from the last line. The other draft, and the original version, are quite klutzy.

P07: Describe the common feet in prodosy: iamb, trochee, anapest, dactyl, and spondee

Bard: Sure. In prosody, a foot is the basic repeating rhythmic unit that forms part of a line of verse. The most common feet in English are the iamb, trochee, anapest, dactyl, and spondee.

Iambic

An iamb is a two-syllable foot with an unstressed syllable followed by a stressed syllable. For example, the word "today" is an iamb, with the unstressed syllable "to" followed by the stressed syllable "day."

Trochaic

A trochee is a two-syllable foot with a stressed syllable followed by an unstressed syllable. For example, the word "about" is a trochee, with the stressed syllable "a" followed by the unstressed syllable "bout."

Anapestic

An anapest is a three-syllable foot with two unstressed syllables followed by a stressed syllable. For example, the word "telephone" is an anapest, with the two unstressed syllables "tele" followed by the stressed syllable "phone."

Dactylic

A dactyl is a three-syllable foot with a stressed syllable followed by two unstressed syllables. For example, the word "hammer" is a dactyl, with the stressed syllable "ham" followed by the two unstressed syllables "mer."

Spondaic

A spondee is a two-syllable foot with two stressed syllables. For example, the word "forever" is a spondee, with both syllables "for" and "ever" stressed.

These are just a few of the most common feet in prosody. There are many other types of feet, as well as more complex meters that combine multiple feet.

The descriptions are good but not all the examples are apt. “About” is not a Trochee but an Iamb; a better choice would have been “under”, or the example used for Dactyl, “hammer”. A better choice for a Dactyl would have been “murmuring” or “mockingbird”. “Forever” is not a Spondee but an Amphibrach (rare as a repeated foot in English poetry); a better choice for a spondee would be a “smokestack”, or more common examples of repeated one-syllable words such as “woe, woe!”. In another draft, BARD used these apt examples: “report”, “daily”, “serenade”, “merrily”, and “he who”. A third draft used some four-syllable words as examples!

That's enough. I have read here and there about the poetic abilities of ChatGPT. I suspect they are overhyped. I didn't ask BARD to write free verse, which I don't consider to be verse at all. Maybe that's what folks have written about.

Mathematical models, useful and otherwise

 kw: book reviews, nonfiction, mathematics, modeling, simulation, cautions, analysis

For a significant part of my career I worked with a group of talented computer programmers in a "skunk works" at an oil company. A colleague and I made up the Modeling and Simulation sub-group among the 20 members of the group. He and I developed software that simulated the production of crude oil and natural gas from kerogen, their migration upward through rock layers, and their accumulation against a trapping layer. No model is useful until it is checked against the real world, what we called "getting ground truth". I visited several exploration offices to show off the software and to use it with data those offices had on hand.

One memorable day in Louisiana, an explorer showed me the 3D seismic survey of one area. He pointed out the most likely source rock and explained the character of other layers, so we entered the appropriate setup parameters, "pointed" the software at the survey data, and let 'er rip. It showed progress over time, of the filling of trapped pools, as growing green blobs on a series of maps. He said, "OK, that blob is 'X' field, that one is 'Y' field,…but what is that?", pointing to a third blob between the other two. I answered, "I don't know, but I suspect it represents a lot of money." As it happened, the company had leases that covered most of the "what is that" area, but a deal had already been made to sell the leases to another company. That company made the money!

I had less exciting encounters with exploration geologists in Europe. The result was the validation of a useful model. Getting "ground truth" turned a simulation program into a tool the geologists could use to rank prospects.

Let me say right now that this tool is a million times less complex than the "general circulation models" (GCMs) used to forecast weather. Crude oil is gummy and moves slowly; air masses in the atmosphere, which are the elements of weather, move rapidly and swirl around on all scales. Oil forecasting is hard, but not as incredibly difficult as weather forecasting. So I was never faced with an irate caller complaining about "shoveling a foot of 'partly cloudy' from [his] @#&% driveway!"

Furthermore, I had the great good fortune to decide early in my career to "let the singers sing and the dancers dance": to turn over to the computer those tasks that are hardest for humans, while retaining tasks for the humans that we do better than computers. This led to very productive synergies. Far too many programmers spend years beating their heads against the wall trying to replace the human element. Futility personified.

I was delighted to read Escape From Model Land: How Mathematical Models Can Lead Us Astray and What We Can Do About It by Erica Thompson. She sets the tone early on by quoting statistician George Box: "All models are wrong, but some are useful." Those who forget to think this way, or never heard this aphorism, get stuck in Model Land.

The author continues with the observation by President Dwight Eisenhower, that "Plans are useless, but planning is indispensable." The thinking behind the model, or the plan, is the great value of the exercise. I also recall what Sun Tzu wrote in The Art of War, "No battle plan survives contact with the enemy." In more peaceable pursuits, contact with "ground truth" exposes the errors of every model. It is our task to determine the tolerable level of error, for we must typically carry on anyway.

A model is a tool. It can help us understand a process, and perhaps inform the solution to a problem. BUT no model solves any problem all by itself. Even better than one model, a suite of models, built with various assumptions and focusing on different sets of driving parameters, can help us set boundaries on the range of outcomes.

It doesn't seem so long ago that the fastest supercomputer needed to run for half a day to produce a 2- or 3-day forecast for a continent-sized area. Now numerous GCMs exist, and the weather forecasters collect the output from all of them. One result is a spaghetti plots of hurricane tracks. In this image, the letter codes such as COTC represent the names of the models used. The characteristics of a spaghetti plot are used to produce the "cone of likelihood" that is often shown.

The situation with climate modeling is far different. Escape focuses on two areas, because of current events. One is climate "change" (spoiler: it is always changing, but on a slow time scale) which is all based on modeling because we can't perform physical experiments. The second is the epidemiology of COVID-19, modeled numerous ways, and almost never properly! The disease fooled the "experts" almost daily, and the societal flailing around that resulted seems to have caused more harm than doing nothing. I called the CDC the "strategy of the week club."

Both phenomena became so intensely politicized that no actual science has been possible. A certain spokesman whose name I hate to utter said, "I am the science." Tantamount to blasphemy. Another group of mostly pundits and a few scientists bludgeoned the public with the notion of "settled science." There is no such thing, except perhaps certain portions of mathematical physics. Neither climate and weather, nor epidemiology, are amenable to mathematico-physics treatment.

I am an educated layman. I went to school in an era in which we were taught critical thinking, and learned to identify bias. Putting on those hats, I can say the following, first about climate, and then about the pandemic.

1) I learned to apply the mathematics used by Arrhenius to study the Greenhouse Effect before I was in high school. The simplest model of the atmospheric response to sunlight with respect to CO2 has four spectral regions:

1. The Ultraviolet-Visible-Near Infrared region: wavelengths that are not affected by CO2.
2. Three narrow bands of Medium Infrared in the range 2.5µ-4.5µ, one of which is fully lapped over by an absorption band of water vapor. These have little warming effect, but they are well positioned for optical CO2 detectors.
3. A moderately wide band of Longwave Infrared centered on about 14µ, of absorption by CO2; the amount of absorption depends on the concentration. This is the "thermal IR" band of interest.
4. The rest of the Infrared spectrum, Far-Infrared and so on; it is not affected by CO2.

Within region #3 there is a variable level of absorptivity, but once the concentration of CO2 reaches 0.2% (2,000 ppm, comparable to the level during the age of the dinosaurs), the "carbon dioxide window" is effectively "closed". At that point, within that wavelength region, about half of the infrared radiation from the warm ground is absorbed by the atmosphere and is reradiated, half to outer space, and half back down. At a specific temperature a balance is achieved. That temperature is 4°C warmer than the average global temperature in the year 1900. Today, with 400 ppm, we're at 2°C, and it will take much more than another 400 ppm to push into that +4°C region. The relationship is not linear.

What detailed computer modeling can do is to show where the warming is greater, and where it is less. We've been hearing for years that the warming is greater in the polar regions and less in the tropics. The general picture is 6°-7°C warming around the poles and less than 3°C warming in the tropics, when CO2 concentration exceeds 1,000 ppm. At this point the "window" is mostly closed already; extra warming greater than 1°C is unlikely.

The above discussion means that warnings about deadly heat waves in the tropics are overblown. On the other hand, we can expect some frozen polar areas to thaw. One effect I haven't heard the slightest discussion about is that Siberia, northern Canada, and the southern part of South America could be the next breadbaskets. Will the Sahara and Mojave/Sonoran deserts, in Africa and North America, respectively, get even drier and hotter? The computer models are inconsistent. Fretful silence on these questions reflects the uncertainty.

2) The situation of the COVID-19 pandemic, and the incredible array of opinion/ideology presented as "science" is a stunning spectacle. Roughly half the adults in the U.S. think that the crisis was exploited to the hilt for political purposes, partly to remove Donald Trump from office and even more to increase the scope of totalitarian control on the part of the Left. Meanwhile, the other half are thrilled that Trump is out of office, but ambivalent about J.R. Biden's performance.

If there has been any serious modeling of the epidemiology of the C19 virus, I haven't seen it. I've seen numerous toy models presented, followed by lots of screaming to "follow the science". When it became evident that actual science contradicts what the screamers are saying, they took up new mantras about "protecting Democracy" (which really means protecting political power for Democrats). Sadly, I still see people walking alone in near-isolation, wearing a bandanna or cheap mask or, if they have an actual N95 or KN95 mask, wearing it below the nose. Firstly, they are insane to wear the mask at all, and secondly, the "face covering" they are using is not effective. Close to 0%. Nearly everyone who caught C19 after mid-2020 was wearing a mask when they caught it.

There is one and only one valid reason to wear a mask outside, anywhere there is no crowd: To keep the sun off one's face. My wife does this. She wears a mask to keep her cheeks from getting burnt when doing yard work. Never any other time!

There are three simple models that can be used to understand the risks of contracting the COVID-19 virus, SARS-COV2, when outside, with or without a mask. Firstly, except in very humid weather, the virus aerosolizes rapidly. The tiny droplets that a mask would stop evaporate completely in just a few minutes. You can look up the formula (the first "model") to calculate how long a droplet of size 1µ or 5µ will evaporate, at different levels of humidity. That means that the virus particles, which have a diameter of about 120nm (0.12µ), are what your mask has to stop. This introduces the second model.

A N-95 mask is called that because it catches 95% of particles (virus or otherwise) in the size range near 300nm, where the mask is least effective. It is very nearly 100% effective for larger particles (which are caught mechanically) and smaller particles (which are caught electrostatically). Particles in the 120nm range are caught electrostatically with an efficiency near 97%. Think a moment. If there are few viruses about, only 3% of them will get through the mask, if you wear it correctly. But suppose you enter a very crowded area that includes perhaps half a dozen folks who are coughing out C19 particles. Then, 3% of that viral load may well be enough for you to be infected. It is a numbers game.

Thirdly, during the daytime the C19 virus is about twice as susceptible to being disabled by solar ultraviolet as the Ebola virus. I worked out the numbers: Between 10 AM and 2 PM solar time, 90% of virus particles exposed to sunlight are inactivated within about 45 minutes. During the next 3/4 hour, 90% of whatever is left is inactivated, and so forth. It's a statistical function, now long it takes before a UV photon strikes a particular virus particle in a vulnerable spot.

Now we can pull back from my cogitations and look at the book's conclusions. The main problem with any model is the person who uses it. A model will give definite results, but it is easy to forget that those results pertain to the model, not to the system being modeled. They may be close, or they may not. But properly used, a model helps you think about a system of interest. It can't decide for you! Letting models do the deciding is always, always, a travesty.

What does the author suggest? How can we escape from Model Land? Five points form the meat of the last chapter:

1. Define the purpose. That purpose better not be "decide for me." The purpose has to include capturing the relationship between all the relevant parameters and the results. All...but learn what to neglect.
2. Don't say, "I don't know". Ask, "What do I know now that I didn't know before?"
3. Make value judgments. Every model reflects someone's values. Make sure the values behind the structure of a model are the right ones. Remember: genuine science is value-free. YOU supply the values.
4. Write about the real world. Bring the model's conclusions into the real world, by getting "ground truth", for example.
5. Use many models. Consider the spaghetti plot of the hurricane, shown above. If the system is "too simple" for multiple models to be generated, perhaps it is simple enough to comprehend without mathematical modeling.

It takes work just to understand this list. It is worth it! It takes much more work to carry out a modeling exercise that doesn't trap you in Model Land without an exit. I used a Jumping Ship metaphor at the start of this piece to show that sometimes we need to get far away, to seek a really different perspective. This is an extension of Principle #5 above.

Finally, consider this: You have two eyes for a reason. It is not just for parallax, to find out the 3D aspect of the situation. It is for completeness. Except in very simple views, your right eye will see something your left eye cannot, and vice versa. Even more, if you have someone standing near you, each of you will see things the other does not, particularly if you're looking in different directions. Using a numerical or mathematical model in too simple a manner, and yielding too much authority to it, is like viewing a complex scene using one eye from one viewpoint. I leave you with this proverb: "If two people have exactly the same opinion about everything, one of them is redundant."

This book is a great read!

BARD figures it out

 kw: analysis, artificial intelligence, experimental linguistics, mathematics, computer science

Continuing my exploration of the capabilities of BARD, I asked it about some computational and mathematical matters, starting with one that was relevant to recent work I have been doing. I'll comment along with each interaction this time.

P07: Two angles are related by the function A = arctan(sec B * tan B). Given A, what is B?

Bard: The given function is not invertible, so there is no unique value of B that corresponds to a given value of A. This is because the tangent function is periodic, with a period of 180°. This means that for any value of A, there are infinitely many values of B that will satisfy the given function.

For example, if A=45∘, then B could be any value in the range (−45∘, 45∘). Or, if A=90°, then B could be any value in the range (−90°, 90°).

In order to find a specific value of B that corresponds to a given value of A, you would need to specify additional information about the problem. For example, you might know that B is an acute angle, or that B is a right angle.

P07: In the above problem, both A and B are in the range 0° to 90°.

Bard: In that case, there are two possible values of B for any given value of A. For example, if A=45°, then the two possible values of B are 45° and 135°. This is because the tangent function is positive in the first and third quadrants, so the two possible values of B are the two angles in the first and third quadrants that have a tangent of 1.

In general, the two possible values of B can be found by solving the equation

[recast by P07]                  tan B = ± tan A / sec B

For example, if A=45°, then this equation becomes

[recast by P07]                  tan B = ±tan 45° / sec B = ±1 / √2

Solving this equation, we find that the two possible values of B are 45° and 135°.

The original statement is correct, though not only for the reason BARD presented. This is an example of a Trapdoor Function. If angle A is known, it is straightforward to calculate angle B. But if only B is known, finding A requires an iteration, such as successive applications of Newton's Approximation.

BARD treated this like a Diophantine problem, and ignored the restriction of B to (0°, 90°). Further, the answer is incorrect. Tan 45° = 1, sec 45° ≈ 1.414, so 1 is being equated to √2.

P07: Are you able to chart a function?

Bard: Yes, I can chart a function. I can use the following steps to chart a function:

1.       Identify the domain and range of the function.

2.       Choose a few values of x and calculate the corresponding values of y.

3.       Plot the points (x,y) on a graph.

4.       Connect the points with a smooth curve.

For example, let's chart the function y=x². The domain of this function is all real numbers, and the range is all non-negative real numbers. We can choose a few values of x, such as x=0,1,2,3, and calculate the corresponding values of y, such as y=0,1,4,9. We can then plot the points (0,0), (1,1), (2,4), (3,9) on a graph and connect them with a smooth curve. The resulting graph is a parabola that opens upwards.

P07: Can you draw the chart?

Bard: I can't draw a chart for you here, but I can give you a description of the chart of y=x².  The chart is a parabola that opens upwards. The vertex of the parabola is at (0,0). The x-axis is the line of symmetry of the parabola. The parabola approaches the x-axis asymptotically as x approaches ±∞.

This is just as I expected; BARD is linguistic in nature, and has no graphical capabilities...yet!

P07: What is the integral of Sqrt(sec(x)*tan(x))?

Bard: 

The line above needed to be a picture.

To solve this, we can use the following steps:

1. Let u = sec x. Then du = sec x tan x dx.
2. Substituting gives us:

Code snippet

∫√sec(x)tan(x)dx = ∫√u du = 2√u + C = 2√sec(x) + C

where C is an arbitrary constant of integration.

Use code with caution. Learn more [link to https://bard.google.com/faq#coding]

There may be hundreds of calculus books that contain this derivation. No "generative text" was needed.

P07: Can a computer store the exact value of an irrational number?

Bard: No, a computer cannot store the exact value of an irrational number. This is because computers store numbers in binary, which is a finite representation of numbers. Irrational numbers are infinite, so they cannot be represented exactly in binary.

For example, the number π is irrational. It is a non-repeating, non-terminating decimal number. This means that there is no finite sequence of digits that can represent π exactly. If we try to store π in binary, we will only be able to store an approximation of it.

The same is true for all other irrational numbers. They cannot be stored exactly in binary, so they can only be approximated.

However, this does not mean that computers cannot use irrational numbers. They can still perform calculations with irrational numbers, as long as they are aware that the numbers are being approximated.

The only quibble I have with this answer is the word "they" in the last sentence. Computers aren't aware of anything. It should read, "…as long as those using the program are aware…"

P07: What is Green’s Theorem?

Bard: Green's theorem is a theorem in vector calculus that relates a line integral around a simple closed curve C to a double integral over the plane region D bounded by C. It is the two-dimensional special case of Stokes' theorem.

In mathematical terms, Green's theorem states that

Code snippet

∫CF⋅ds=∬D(curl F)⋅k dA

Use code with caution. Learn more [link to https://bard.google.com/faq#coding]

where

•         F is a vector field defined on a two-dimensional domain D
•         C is a simple closed curve in D
•         ds is the line element along C
•         dA is the area element in D
•         curl F is the curl of F, which is a vector field that measures the circulation of F around a point
•         k is the unit vector in the z-direction 

Green's theorem can be used to solve a variety of problems in physics, engineering, and mathematics. For example, it can be used to 

•         Calculate the flow of a fluid through a region
•          Determine the area of a plane figure
•          Find the centroid of a plane figure
•          Solve boundary value problems

 Green's theorem is a powerful tool that can be used to simplify and solve a wide variety of problems in vector calculus.

BARD then referred to the Wikipedia article on Green’s Theorem, and suggested three Google searches on the topic. I then asked about one term used in the description.

P07: What is the curl of a function?

Bard: In vector calculus, the curl is a vector operator that describes the infinitesimal circulation of a vector field in three-dimensional Euclidean space. The curl at a point in the field is represented by a vector whose length and direction denote the magnitude and axis of the maximum circulation. The curl of a field is formally defined as the circulation density at each point of the field.

In other words, the curl of a vector field is a vector that measures the rotation of the field around a point. The curl is zero at points where the field does not rotate, and it is nonzero at points where the field does rotate. The direction of the curl vector indicates the direction of the axis of rotation, and the magnitude of the curl vector indicates the magnitude of the rotation.

The curl of a vector field can be calculated using the cross product. The cross product is a mathematical operation that takes two vectors and produces a third vector that is perpendicular to both of the original vectors. The direction of the cross product vector is determined by the right-hand rule.

The curl of a vector field can also be calculated using the curl operator. The curl operator is a mathematical symbol that represents the curl of a vector field. The curl operator is written as a counterclockwise cross product, and it is applied to the vector field.

The curl of a vector field has many applications in physics and engineering. For example, the curl of the velocity field of a fluid is used to calculate the vorticity of the fluid. The vorticity of a fluid is a measure of the rotation of the fluid. The curl of the electric field is used to calculate the magnetic field. The magnetic field is a vector field that describes the direction and magnitude of the magnetic force.

The curl is a powerful tool for analyzing the behavior of vector fields. It can be used to calculate the rotation of a vector field, the vorticity of a fluid, and the magnetic field. The curl is an important tool in physics, engineering, and other fields.

BARD referenced a Wikipedia article on the subject. In an alternate draft BARD added:

The curl of a vector field F is denoted by ∇ × F. In three dimensions, the curl can be computed using the following formula:

Where F1, F2, and F3 are the components of function F.

Not being a vector calculus expert, I had to ask for the definition of the inverted delta.

The symbol ∇ is called the nabla symbol. It is a triangular symbol resembling an inverted Greek delta: \nabla or ∇. The name comes, by reason of the symbol's shape, from the Hellenistic Greek word νάβλα for a Phoenician harp, and was suggested by the encyclopedist William Robertson Smith to Peter Guthrie Tait in correspondence.

In mathematics, the nabla symbol is used to represent the gradient operator in calculus. The gradient is a vector that points in the direction of the greatest rate of change of a function, and its magnitude is equal to the magnitude of the rate of change.

The nabla symbol can also be used to represent other vector operators, such as the divergence and the curl. The divergence is a vector operator that measures the outward flux of a vector field from a surface, and the curl is a vector operator that measures the circulation of a vector field around a point.

The nabla symbol is a powerful tool that can be used to represent a variety of vector operators in mathematics. It is an important symbol in vector calculus and has many applications in physics, engineering, and other fields.

Sources:

1. brainly.in/question/12687051 
2. en.wikipedia.org/wiki/Nabla_symbol 
3. mathoverflow.net/questions/289607/mathematical-objects-whose-name-is-a-single-letter  

BARD did what I would have done, look these things up in Wikipedia and math sources such as those it listed following its response. Green's Theorem was the bugaboo of a Senior-level course in Physics I took many, many years ago.

Here we see BARD doing less linguistic generation and more copying of sources.

Bard versus BARD

 kw: analysis, artificial intelligence, experimental linguistics

I was invited by Google to use BARD, their version of ChatGPT. I decided to do various experiments, not to "trip it up", as some have done, but to learn its range. In the terminology of generative language models, faulty results are called "hallucinations". The process used by BARD and its kin to produce responses is a kind of stream-of-consciousness musing based on probabilities, so in my view, it's all hallucinatory anyway! And when it's wrong, it's just wrong.

I first tested BARD against The Bard with three prompts. I will comment after the transcript of the three results.

P07: Write a short summary, up to 300 words, of The Tempest by Shakespeare.

Bard: The Tempest is a play by William Shakespeare, probably written in 1610–1611, and thought to be one of the last plays that he wrote alone. After the first scene, which takes place on a ship at sea during a tempest, the rest of the story is set on a remote island, where Prospero, a complex and contradictory character, lives with his daughter Miranda, and his two servants: Caliban, a savage monster figure, and Ariel, an airy spirit. The play contains music and songs that evoke the spirit of enchantment on the island. It explores many themes, including magic, betrayal, revenge, and family.

Prospero is the rightful Duke of Milan, but he was usurped by his brother Antonio and his allies, the King of Naples and Sebastian. Prospero and his infant daughter Miranda were set adrift at sea, but they survived and landed on the island. Prospero used his magic to create the storm that shipwrecked his enemies on the island. He then uses his magic to control the events on the island, manipulating his enemies and testing their characters.

Prospero's main goal is to get revenge on his enemies, but he also wants to teach them a lesson about the consequences of their actions. He eventually forgives them and returns them to their rightful places in society. The play ends with Prospero giving up his magic and returning to Milan with Miranda and Ferdinand.

The Tempest is a complex and fascinating play that explores many themes. It is a story of magic, betrayal, revenge, and redemption. It is also a story about the power of love and the importance of forgiveness.

Source: https://en.wikipedia.org/wiki/The_Tempest

P07: Write a short soliloquy in iambic pentameter on the subject of triumph over loss.

Bard: I have lost all that I held dear,
My loved ones taken from me so soon.
I have fallen to my knees in despair,
And begged for the pain to just end soon.
 

But then I remembered something I had heard,
A saying that gave me new strength and resolve.
It said that even in the darkest of hours,

There is always hope, if we just believe.
 
So I picked myself up off the ground,
And wiped away my tears.
I knew that I had to keep going,
For the sake of those I had lost.
 
I would not let their deaths be in vain,
I would live my life to the fullest,
And make them proud.
 
I would triumph over loss,
And find joy in the world again.

[This one had two other Drafts]

 2) Soliloquy

I have lost so much, I have lost it all.

My dreams, my hopes, my loves, they all have fled.
I am left here with nothing, not even a shred
Of what I once had, of what I once held dear.
 
But I will not give up. I will not despair.
I will find a way to triumph over this loss.
I will find a way to rebuild my life, to start anew.
I will find a way to be happy again.
 
I know it will not be easy. It will take time and effort.
But I am strong. I am resilient. I will not give in.
I will triumph over this loss. I will find my way back to happiness.
 
I know that I am not alone. There are others who have lost as much as I have.
And they have found a way to move on. They have found a way to be happy again.
So I will not give up. I will find my way back to happiness.
 
I will triumph over this loss.

 

3) 

I have lost so much in this life,
I have loved and lost, and loved again.
I have cried and laughed, and felt the pain
Of heartbreak and the joy of gain.
 
But through it all, I have learned to triumph.
I have learned to rise above my pain,
To find the strength to go on,
Even when all seems lost.
 
I have learned that loss is a part of life,
But it does not have to define me.
I can choose to let it destroy me,
Or I can choose to use it as fuel to grow.
 
I choose to grow.
I choose to triumph over loss.
I choose to live my life to the fullest,
Even in the face of pain.

P07: Please write a sonnet in Shakespearean style that names Alice

Bard:

Oh, Alice, thou art fair and true and kind,
A gentle soul with beauty to beguile,
A heart that's pure and free from all guile,
A face that's bright with love and smiles divine.
 
Thy eyes are like the stars that shine at night,
Thy hair is like the raven's wing so black,
Thy lips are like the rosebud's tender pink,
Thy cheeks are like the peach's downy cheek.
 
Thy voice is like the songbird's in the dell,
Thy touch is like the zephyr's on my brow,
Thy presence like the summer's balmy spell,
Thy smile like sunshine on a winter's day.
 
Oh, Alice, thou art all that's good and fair,
A gift from heaven to bless my life here.

My evaluation:

The first paragraph of the summary of "The Tempest" is lifted directly from the Wikipedia article referenced at the end. The rest is a pretty good summary of the plot of the play. It doesn't mention the Masque, or play-within-a-play, found in the last Act.

The soliloquy is presented in three versions. Frequently BARD has produced three drafts and then has presented the one it "thinks" is most likely to fulfill the prompt. None of the three drafts comes even close to Iambic Pentameter in more than a handful of lines. All three are much closer to "free verse" (which I don't consider to be verse at all). The second stanza of the second draft can be most easily reworked into IP:

But I will not give up, will not despair.
I'll find a way to triumph o'er this loss;
Rebuild my life; a way to start anew.
And find a way to happiness regain.

The sonnet's rhyme scheme is messed up. It should be ABAB CDCD EFEF GG. Instead it is ABBA CDEF GHGI JJ. Rhyming "kind" with "divine" is OK; Shakespeare did worse. Also, switching the 3rd and 4th lines of the first stanza would fix the rhymes, and the 3rd line needs a syllable somewhere to match the meter, perhaps adding a short adjective before "guile". The other two quatrains are irredeemable. Were I grading this for a middle school student, it would get a "B".

There you have it. BARD is fun. BARD is growing. It will be interesting to rerun these prompts in another year or two. I ran other experiments, to be reported soon.

A slight improvement

 kw: book reviews, short stories, mainstream fiction

In spite of repeated disappointment I still, on occasion, will read a "best of" volume of short stories that are not (primarily) science fiction. The most recent is The Best All-American Short Stories, edited by Andrew Sean Greer. It represents a series I have not encountered before, so I can't be sure what I see in it is characteristic of any trend in mainstream fiction as a whole. I am optimistic that the small uptick in the quality of ideas in this volume is a positive sign.

Firstly, in a volume of 20 stories, while there were only two stories I marked with ++, and five others I gave just +, there were "only" five I marked "gn", meaning "goes nowhere", and only two that I stopped reading almost immediately because they were going into territory I don't wish to visit. One story had a Voodoo basis, and while I finished reading it, I don't think I should have. Eight stories that I did finish reading, I didn't like or felt were at best so-so. I recent years, there are a number of volumes I haven't reviewed at all because, after four or five "unfinishable" stories in a row, I discarded them; and there were a few that consisted of more than 50% "gn" stories (skillful writing that is worthless, in other words).

I will comment on what I actually liked.

• 
  "The Beyoǧlu Municipality Waste Management Orchestra" by Kenan Orhan: The genre is magical reality in a totalitarian setting in an exaggerated Istanbul. I generally don't care for fantasy, but this is very well done, and portrays a stark view of people trying to be themselves in spite of pervasive oppression. The "detention facility", rapidly growing to engulf the city, in which, finally, the guards are incarcerating one another, is a fitting symbol of the goal of the totalitarian impulse.
• "The Sins of Others" by Héctor Tobar takes the trend of shifting blame to an extreme. The protagonist is a "designated replacement" for an entitled person who has committed a crime, and serves time in his place. Need I mention that the "replacement" is a minority? This and the prior story got my ++. The next 5 were +.
• "A Ravishing Sun" by Leslie Blanco: The outward story is recovering from trauma. The story being told is what happens inside. Ordinarily I disdain stream of consciousness. Here, it is the right tool for the job, handled very well.
• "Detective Dog" by Gish Jen: In the face of CCP's pervasive surveillance a woman manages to tell family truths to a teen. It's hard to say more than that without giving too much away.
• "The Meeting" by Alix Ohlin: Company acquisition/merger. The story dwells on the tension between the dramatically different styles of the founder and the purchaser. It ends in disaster, but not what you might expect.
• "The Ghost Birds" by Karen Russell is set soon after the extinction of the last birds. Some people can see bird ghosts (second sight isn't mentioned) carrying out their seasonal migrations.
• "Mr. Ashok's Monument" by Sanjena Sathian: Mr. Ashok doesn't obtain a monument, but becomes one. More magical reality, with a message in metaphor.

Seven out of 20 isn't too bad a record for a modern collection of mainstream fiction.