Orthoepy. Elucubrate. Lachrymatory. Ephectic. Palilogy. Sempiternal. Anadrome. Entelechy. Paracosm. Amerce. Syndactyly. Ustulation. Darrein. Mesority. Busker. Philematology. Episiotomy. Codger. Dacite. Obliviality.

Vermiculate. Temeritous. Buckler. Gormless. Vaginismus. Twerp. Décolletage. Wimple. Buccal. Anadromous/catadromous. Seraglio. Theriomorphic. Hypogeum. Sempervirent. Chinwag. Belonephobia/aichmophobia. Blepharospasm. Vigesimal. Eonism. Grandisonant.

Tiddly. Dactylography. Fulgurous. Oppilate. Xerophagy. Ostler. Skeuomorph. Lubricity. Yclept.
Dyspareunia. Sthenic. Magnalium. Vigil. Sejunction. Tonology. Tussle. Radix. Natatory. Obsidional.

Quillet. Elutriate. Runnel. Energumen. Mullered. Aquatint. Wyvern. Undine. Hectograph.
Traction engine. Custrel. Ochlagogy. Saturnalia. Querent. Tucket. Custrel. Sanguinolent. Abaisse. Clavis. Scenester.

Stonker. Ramus. Anfractuous. Scrumptious. Ctenoid. Enfleurage. Lamina. Worsted. Schlemiel. Erubescent. Clachan. Vinew. Dottle. Armlet. Kernel. Quitclaim. Avulsion. Dehisce. Zephyr. Kenning.

May 30, 2017 Posted by | language | Leave a comment


Sciolism, amative, hypocorism, leiotrichouslatitudinariancircumlocutionary, daedal, ceruse, wimple, doyen, fuscous, jorum, groupuscule, gelid, hadal, palfrey, malum, cachou, fellmonger, susurrus.

Zeteticeirenicon, dystocia, vicereine, brachiation, odalisque, daglock, galumph, plantain, insufflation, marquetry, névé, samite, pangram, whisk, hamiform, addeem, oeillade, daggle, teratophilia.

Boffin, paraph, girandole, stramineouscusp, telishment, lenition, paludous, phoresy, foramen, zymurgy, pinion, clusivity, gnomon, enallage, zymogram, autopoiesis, bradyseism, appurtenant, dealation.

Peen, chamfer, siphonapterology, onomastics, stridulate, whinging, irrorate, amnion, pectination, sturt, anthelminthic, arrhinia, aprosopia, viscidity, periotic, constat, muffler, ostosis, petrichor, scelidate.

Thalassochorykex, engastration, braw, urbicolous, armillary, clanger, crith, enteron, mullion, quag, hooch, enounce, congé, bdelygmia, catenative, falx, cotyledon, egret, pericyte.

May 20, 2017 Posted by | language | Leave a comment


Almost all the words included in this post are words I encountered while reading the Flashman novels Flashman and the Mountain of Light, Flash for Freedom!, and Flashman and the Redskins. Almost all the words are words I have not included in similar posts in the past, but I decided to include a few words (2 or 3 words, something like that) I already included in similar posts in the past because I like those words and the fact that I had taken notice of them while reading these novels indicates to me that they haven’t yet stuck in my mind the way I’d like them to do; I usually only mark out words with which I’m either unfamiliar or words the meaning of which I have trouble remembering.

The post includes 6 segments of 20 words/concepts each.

Duff. Coparcener. Chunter. Haver. Sop. Purdah. Bedewing. Paynim. Conniptions. Pap. Tiffin. Aigrette. Whippet. Grandee. Caparison. Howdah. Mahout. Malediction. Tipple. Slantendicular.

Collogue. Hocussing. Sobersided/sobersides. Grog. Ramage. Hutment. Peradventure. Truckle. Caracole. Hustings. Gamester. Barracoon. Bowsprit. Gorget. Midge. Mumchance. Kurbash. Mudge. Unchancy. Mizzenmast/mizzen.

Wiseacre. Cully. SibilantHummock. Gloaming. Clew. Bestride. Dragoman. Lanyard. Binnacle. Stevedore. Corn pone/pone. Bawd. Spavin. Plaintiff. Wickiup. Julep. Holystone. Crimp. Melodeon.

Bitumen. Reticule. Roustabout. Teamster (Interestingly what this word means seems to have changed over time. In the Flashman setting the word is used to describe someone who’s handling teams of slaves; i.e. a slave driver). Serape. Crupper. Stockman. Carter. Clodpole. Tenderfoot. Chevron. Doss. Coonskin. Roué. Bight. Ferrule. Bodkin. Pelf. Pother. Ford.

Concourse. Dixie. Tobyman. Kedgeree. Prepossess. Rivet. Clubbable. Bower. Pottle. Clog. Waft. Lariat. Bargee. Gallus. Navvy. Papoose. Levee. Minatory. Wend. Statuary.

Fustian. Blatherskite. Escritoire. Twanging. Tippet. Wanton. Convivial. Blandishment. Quirt. Coulee. Guidon. Sorrel. Arrant. Contumelious. Depilation. Magnate. Vatic. Grimalkin. Manciple. Banns.

May 2, 2017 Posted by | Books, language | Leave a comment


Lately I’ve been reading some of George MacDonald Fraser’s Flashman books, which have been quite enjoyable reads in general; I’m reading the books in the order in which the actions in the books supposedly took place, not in the order in which the books were published, and a large number of the words included below are words I encountered in the first three of the books I read (i.e. FlashmanRoyal Flash, and Flashman’s Lady); I decided the post already at that point included a large number of words (the post includes roughly 120 words), so I saw no need to add additional words from the other books in the series in this post as well. I have reviewed a few of the Flashman books I’ve read on goodreads here, here, and here.

Havildar, gimbal, quorum, unmannerly, tribulation, thalassophobia, kiln, sheave, grody, contemn, arcanum, deloping, poulterer, fossorial, catamount, guttersnipe, nabob, frond, matelot, jetty.

Sangar, palliasse, junoesque, cornet, bugle, fettle, toady, thong, trollop, sepoy, wattle, hardtack, snuffle, chunter, ghillie, barker, trousseau, simper, madcap, ramrod.

Welt, landau, declaim, burgomaster, scupper, windlass, maunder, sniffy, sirdar, randy, dowager, toffs, pug, curvet, pish, scriveners, hoyden, manikin, lecher/lechery, busby.

Ruck, leery, ninny, shillyshally, mincing, ringlet, covey, pip, munshi, risaldar, maidan, palankeen/palanquin, forbye, feringhee, cantonment, puggaree, pannikin, dollymop, snook, cordage.

Suet/suety, strumpet, kenspeckle, magsman, scrag, chandler, prigger, chivvy, décolleté, dundrearies, assignation, bruit, purblind, trull, slatterncoffle, doggo, cellarette, cummerbund, agley.

Sampan, wideawake, popsycollation, déshabillé, pinnace, pennant, murk, sprig, linstock, tassel, bangle, trammel, prau, shellback, shako, clobbertaffrail, crinolinetaffeta, commonalty.

April 15, 2017 Posted by | Books, language | Leave a comment


Over the last couple of weeks I’ve been reading James Herriot’s books and yesterday I finished the last one in the series. The five books (or 8, if you’re British – see the wiki…) I read – I skipped the ‘dog stories’ publication on that list because that book is just a collection of stories included in the other books – contain almost 2500 pages (2479, according to the goodreads numbers provided in the context of the editions I’ve been reading), and they also contained quite a few unfamiliar/nice words and expressions, many of which are included below. If you’re curious about the Herriot books you can read my goodreads reviews of the books here, here (very short), here, and here (I didn’t review The Lord God Made Them All).

Eversionskeevy, censerknout, byreelectuary, trocar/trocarization, clogirascible, gilt, curvet, bullock, niggle, scapegrace, cur, pantile, raddle, scamper, skitter, odoriferous.

Dewlap, seton, muzzy, stirk, shillelagh, borborygmi, omentum, fettle, guddle, cruciate, peduncle/pedunculated, ecraseur, curlew, gabble, gable, festoon, cornada, lambent, lank.

Lope, billet, casement, scree, caliper, dale, stoup, puisne, tumefy, scamp, probang, famble, footling, colostrum, towsle/tousle, loquacious, dapper, cob, meconium, locum.

Mullion, roan, slat, dustman, carvery, abomasum, rostrum, zareba, flithackle, tympanites, pewter, opisthotonos, concertina, miliarylief, spay, otodectic.

March 24, 2017 Posted by | Books, language | Leave a comment


The great majority of the words below are from books I’ve recently read, I’ve almost not spent any time on since my last post of this kind; the guys add new words much too slowly, and most of the words they’ve recently added were not in my opinion all that interesting.

GelidCicatrization. Caudal. Stanchion. Saurian. Griddle. Branks. Purlieu. Arras. Slicker. Insipidity. Sedulously. Splay. Traipse. Gaff. Costive. Depauperate. Quaver. Homiletic.

Anemometer. Flagitious. CarboyMatutinalCognizance. Crispation. Doughty. Crepuscular. Giblets. Venery. Collier. Charnel. Dirge. Natter. Lintel. Disquisition.

Papuliferous. Vespertine. Lusciousness. Damask. Vaunt. Cicatrix. Integument. Heresiarch. Traducement. Apotheosis. Sardanapalian. Vocable. Desiderium. Leucocholy. Compathy.

Callosity. Skosh. Hellacious. Jouncy. Scilicet. Benignancy. TenebrificIpseityHoydenish. Quean. Handsel. Piton. Belvedere. Yenta. Officinal. Sanative. Umbra. Abaxial. Idiographic.

March 6, 2017 Posted by | language | 4 Comments


I’ve usually in the past combined these lists with other stuff, but I am now strongly considering making these lists into posts of their own in order to make a potential lack of ‘other stuff’ to include in such posts less likely to stop me from posting the words; stuff I don’t blog is more likely to get lost to my memory, so I don’t want to give myself any more excuses not to blog stuff I want to remember/learn than I have to. Most of the words are from books I’ve read over the last weeks, I rarely spend time on these days (I don’t encounter enough new words on the site these days to justify a significant amount of activity there; there are too many review questions, likely a result of me having mastered words much faster than they’ve added new ones..).

I’ve by now decided to stop (more-or-less…-) systematically checking in each case if I’ve already included a word on a similar list in a previous post; not all the words on these lists from now on will necessarily be ‘new’ to me (to the extent that the words on the previous lists have been, that is…) – so some of these words (and the words to come, assuming other posts will follow) are likely just words I’ve forgot about, and some are words I simply consider to be ‘nice’/’unappreciated’/’not encountered often enough’… I decided to split the words in this post up into smaller groups of words, as one big chunk of words looked slightly ‘scary’ and unapproachable to me. There’s no system to the groupings, the words were originally randomly added to a list I keep of words I knew I’d want to get back to at some point and the cut-offs I later applied when writing this post were more or less completely arbitrary. If you want non-arbitrary groups of interesting words, I refer to the goodreads lists.

Saudade, malapertauriferousfrissonanchorite, lacquerermisoneismcamarilla, cloy, cooper, prevaricatory, impugn, prestidigitation, compeer, lapidary, contumely, contumelious.

Dotard, creel, parricide, assonance, habiliment, assail, mimesis, investiture, irruption, tenuity, tribulation, analectic, succour, augercanker, apophthegm, haruspex, rapine.

Sward, chafferer, argol, sprightly, disport, eyas, garishly, teeter, flocculent, crick, dandle, picaresque, newelanamnesis, imprecateemically, mulch, sommelier, julienne.

Logomachy, chockablock, fusty, diarchy, perfervid, estivationlogy, tumescence, portcullislox, unprocurable, admonitory, kelp, enjambment, lithography.

February 14, 2017 Posted by | language | Leave a comment

Random Stuff

i. On the youtube channel of the Institute for Advanced Studies there has been a lot of activity over the last week or two (far more than 100 new lectures have been uploaded, and it seems new uploads are still being added at this point), and I’ve been watching a few of the recently uploaded astrophysics lectures. They’re quite technical, but you can watch them and follow enough of the content to have an enjoyable time despite not understanding everything:

This is a good lecture, very interesting. One major point made early on: “the take-away message is that the most common planet in the galaxy, at least at shorter periods, are planets for which there is no analogue in the solar system. The most common kind of planet in the galaxy is a planet with a radius of two Earth radii.” Another big take-away message is that small planets seem to be quite common (as noted in the conclusions, “16% of Sun-like stars have an Earth-sized planet”).

Of the lectures included in this post this was the one I liked the least; there are too many (‘obstructive’) questions/interactions between lecturer and attendants along the way, and the interactions/questions are difficult to hear/understand. If you consider watching both this lecture and the lecture below, I would say that it would probably be wise to watch the lecture below this one before you watch this one; I concluded that in retrospect some of the observations made early on in the lecture below would have been useful to know about before watching this lecture. (The first half of the lecture below was incidentally to me somewhat easier to follow than was the second half, but especially the first half hour of it is really quite good, despite the bad start (which one can always blame on Microsoft…)).

ii. Words I’ve encountered recently (…or ‘recently’ – it’s been a while since I last posted one of these lists): Divagationsperiphrasis, reedy, architravesettpedipalp, tout, togs, edentulous, moue, tatty, tearaway, prorogue, piscine, fillip, sop, panniers, auxology, roister, prepossessing, cantle, catamite, couth, ordure, biddy, recrudescence, parvenu, scupper, husting, hackle, expatiate, affray, tatterdemalion, eructation, coppice, dekko, scull, fulmination, pollarding, grotty, secateurs, bumf (I must admit that I like this word – it seems fitting, somehow, to use that word for this concept…), durophagy, randy, (brief note to self: Advise people having children who ask me about suggestions for how to name them against using this name (or variants such as Randi), it does not seem like a great idea), effete, apricity, sororal, bint, coition, abaft, eaves, gadabout, lugubriously, retroussé, landlubber, deliquescence, antimacassar, inanition.

iii. “The point of rigour is not to destroy all intuition; instead, it should be used to destroy bad intuition while clarifying and elevating good intuition. It is only with a combination of both rigorous formalism and good intuition that one can tackle complex mathematical problems; one needs the former to correctly deal with the fine details, and the latter to correctly deal with the big picture. Without one or the other, you will spend a lot of time blundering around in the dark (which can be instructive, but is highly inefficient). So once you are fully comfortable with rigorous mathematical thinking, you should revisit your intuitions on the subject and use your new thinking skills to test and refine these intuitions rather than discard them. One way to do this is to ask yourself dumb questions; another is to relearn your field.” (Terry Tao, There’s more to mathematics than rigour and proofs)

iv. A century of trends in adult human height. A figure from the paper (Figure 3 – Change in adult height between the 1896 and 1996 birth cohorts):


(Click to view full size. WordPress seems to have changed the way you add images to a blog post – if this one is even so annoyingly large, I apologize, I have tried to minimize it while still retaining detail, but the original file is huge). An observation from the paper:

“Men were taller than women in every country, on average by ~11 cm in the 1896 birth cohort and ~12 cm in the 1996 birth cohort […]. In the 1896 birth cohort, the male-female height gap in countries where average height was low was slightly larger than in taller nations. In other words, at the turn of the 20th century, men seem to have had a relative advantage over women in undernourished compared to better-nourished populations.”

I haven’t studied the paper in any detail but intend to do so at a later point in time.

v. I found this paper, on Exercise and Glucose Metabolism in Persons with Diabetes Mellitus, interesting in part because I’ve been very surprised a few times by offhand online statements made by diabetic athletes, who had observed that their blood glucose really didn’t drop all that fast during exercise. Rapid and annoyingly large drops in blood glucose during exercise have been a really consistent feature of my own life with diabetes during adulthood. It seems that there may be big inter-individual differences in terms of the effects of exercise on glucose in diabetics. From the paper:

“Typically, prolonged moderate-intensity aerobic exercise (i.e., 30–70% of one’s VO2max) causes a reduction in glucose concentrations because of a failure in circulating insulin levels to decrease at the onset of exercise.12 During this type of physical activity, glucose utilization may be as high as 1.5 g/min in adolescents with type 1 diabetes13 and exceed 2.0 g/min in adults with type 1 diabetes,14 an amount that quickly lowers circulating glucose levels. Persons with type 1 diabetes have large interindividual differences in blood glucose responses to exercise, although some intraindividual reproducibility exists.15 The wide ranging glycemic responses among individuals appears to be related to differences in pre-exercise blood glucose concentrations, the level of circulating counterregulatory hormones and the type/duration of the activity.2

August 13, 2016 Posted by | Astronomy, Demographics, Diabetes, language, Lectures, Mathematics, Physics, Random stuff | Leave a comment

Random stuff

I find it difficult to find the motivation to finish the half-finished drafts I have lying around, so this will have to do. Some random stuff below.


(15.000 views… In some sense that seems really ‘unfair’ to me, but on the other hand I doubt neither Beethoven nor Gilels care; they’re both long dead, after all…)

ii. New/newish words I’ve encountered in books, on or elsewhere:

Agleyperipeteia, disseverhalidom, replevinsocage, organdie, pouffe, dyarchy, tauricide, temerarious, acharnement, cadger, gravamen, aspersion, marronage, adumbrate, succotash, deuteragonist, declivity, marquetry, machicolation, recusal.

iii. A lecture:

It’s been a long time since I watched it so I don’t have anything intelligent to say about it now, but I figured it might be of interest to one or two of the people who still subscribe to the blog despite the infrequent updates.

iv. A few wikipedia articles (I won’t comment much on the contents or quote extensively from the articles the way I’ve done in previous wikipedia posts – the links shall have to suffice for now):

Duverger’s law.

Far side of the moon.

Preference falsification.

Russian political jokes. Some of those made me laugh (e.g. this one: “A judge walks out of his chambers laughing his head off. A colleague approaches him and asks why he is laughing. “I just heard the funniest joke in the world!” “Well, go ahead, tell me!” says the other judge. “I can’t – I just gave someone ten years for it!”).

Political mutilation in Byzantine culture.

v. World War 2, if you think of it as a movie, has a highly unrealistic and implausible plot, according to this amusing post by Scott Alexander. Having recently read a rather long book about these topics, one aspect I’d have added had I written the piece myself would be that an additional factor making the setting seem even more implausible is how so many presumably quite smart people were so – what at least in retrospect seems – unbelievably stupid when it came to Hitler’s ideas and intentions before the war. Going back to Churchill’s own life I’d also add that if you were to make a movie about Churchill’s life during the war, which you could probably relatively easily do if you were to just base it upon his own copious and widely shared notes, then it could probably be made into a quite decent movie. His own comments, remarks, and observations certainly made for a great book.

May 15, 2016 Posted by | Astronomy, Computer science, History, language, Lectures, Mathematics, Music, Random stuff, Russia, Wikipedia | Leave a comment

Random Stuff

i. Some new words I’ve encountered (not all of them are from, but many of them are):

Uxoricide, persnickety, logy, philoprogenitive, impassive, hagiography, gunwale, flounce, vivify, pelage, irredentism, pertinacity,callipygous, valetudinarian, recrudesce, adjuration, epistolary, dandle, picaresque, humdinger, newel, lightsome, lunette, inflect, misoneism, cormorant, immanence, parvenu, sconce, acquisitiveness, lingual, Macaronic, divot, mettlesome, logomachy, raffish, marginalia, omnifarious, tatter, licit.

ii. A lecture:

I got annoyed a few times by the fact that you can’t tell where he’s pointing when he’s talking about the slides, which makes the lecture harder to follow than it ought to be, but it’s still an interesting lecture.

iii. Facts about Dihydrogen Monoxide. Includes coverage of important neglected topics such as ‘What is the link between Dihydrogen Monoxide and school violence?’ After reading the article, I am frankly outraged that this stuff’s still legal!

iv. Some wikipedia links of interest:


Steganography […] is the practice of concealing a file, message, image, or video within another file, message, image, or video. The word steganography combines the Greek words steganos (στεγανός), meaning “covered, concealed, or protected”, and graphein (γράφειν) meaning “writing”. […] Generally, the hidden messages appear to be (or be part of) something else: images, articles, shopping lists, or some other cover text. For example, the hidden message may be in invisible ink between the visible lines of a private letter. Some implementations of steganography that lack a shared secret are forms of security through obscurity, whereas key-dependent steganographic schemes adhere to Kerckhoffs’s principle.[1]

The advantage of steganography over cryptography alone is that the intended secret message does not attract attention to itself as an object of scrutiny. Plainly visible encrypted messages—no matter how unbreakable—arouse interest, and may in themselves be incriminating in countries where encryption is illegal.[2] Thus, whereas cryptography is the practice of protecting the contents of a message alone, steganography is concerned with concealing the fact that a secret message is being sent, as well as concealing the contents of the message.”

H. H. Holmes. A really nice guy.

Herman Webster Mudgett (May 16, 1861 – May 7, 1896), better known under the name of Dr. Henry Howard Holmes or more commonly just H. H. Holmes, was one of the first documented serial killers in the modern sense of the term.[1][2] In Chicago, at the time of the 1893 World’s Columbian Exposition, Holmes opened a hotel which he had designed and built for himself specifically with murder in mind, and which was the location of many of his murders. While he confessed to 27 murders, of which nine were confirmed, his actual body count could be up to 200.[3] He brought an unknown number of his victims to his World’s Fair Hotel, located about 3 miles (4.8 km) west of the fair, which was held in Jackson Park. Besides being a serial killer, H. H. Holmes was also a successful con artist and a bigamist. […]

Holmes purchased an empty lot across from the drugstore where he built his three-story, block-long hotel building. Because of its enormous structure, local people dubbed it “The Castle”. The building was 162 feet long and 50 feet wide. […] The ground floor of the Castle contained Holmes’ own relocated drugstore and various shops, while the upper two floors contained his personal office and a labyrinth of rooms with doorways opening to brick walls, oddly-angled hallways, stairways leading to nowhere, doors that could only be opened from the outside and a host of other strange and deceptive constructions. Holmes was constantly firing and hiring different workers during the construction of the Castle, claiming that “they were doing incompetent work.” His actual reason was to ensure that he was the only one who fully understood the design of the building.[3]

Minnesota Starvation Experiment.

“The Minnesota Starvation Experiment […] was a clinical study performed at the University of Minnesota between November 19, 1944 and December 20, 1945. The investigation was designed to determine the physiological and psychological effects of severe and prolonged dietary restriction and the effectiveness of dietary rehabilitation strategies.

The motivation of the study was twofold: First, to produce a definitive treatise on the subject of human starvation based on a laboratory simulation of severe famine and, second, to use the scientific results produced to guide the Allied relief assistance to famine victims in Europe and Asia at the end of World War II. It was recognized early in 1944 that millions of people were in grave danger of mass famine as a result of the conflict, and information was needed regarding the effects of semi-starvation—and the impact of various rehabilitation strategies—if postwar relief efforts were to be effective.”

“most of the subjects experienced periods of severe emotional distress and depression.[1]:161 There were extreme reactions to the psychological effects during the experiment including self-mutilation (one subject amputated three fingers of his hand with an axe, though the subject was unsure if he had done so intentionally or accidentally).[5] Participants exhibited a preoccupation with food, both during the starvation period and the rehabilitation phase. Sexual interest was drastically reduced, and the volunteers showed signs of social withdrawal and isolation.[1]:123–124 […] One of the crucial observations of the Minnesota Starvation Experiment […] is that the physical effects of the induced semi-starvation during the study closely approximate the conditions experienced by people with a range of eating disorders such as anorexia nervosa and bulimia nervosa.”

Post-vasectomy pain syndrome. Vasectomy reversal is a risk people probably know about, but this one seems to also be worth being aware of if one is considering having a vasectomy.

Transport in the Soviet Union (‘good article’). A few observations from the article:

“By the mid-1970s, only eight percent of the Soviet population owned a car. […]  From 1924 to 1971 the USSR produced 1 million vehicles […] By 1975 only 8 percent of rural households owned a car. […] Growth of motor vehicles had increased by 224 percent in the 1980s, while hardcore surfaced roads only increased by 64 percent. […] By the 1980s Soviet railways had become the most intensively used in the world. Most Soviet citizens did not own private transport, and if they did, it was difficult to drive long distances due to the poor conditions of many roads. […] Road transport played a minor role in the Soviet economy, compared to domestic rail transport or First World road transport. According to historian Martin Crouch, road traffic of goods and passengers combined was only 14 percent of the volume of rail transport. It was only late in its existence that the Soviet authorities put emphasis on road construction and maintenance […] Road transport as a whole lagged far behind that of rail transport; the average distance moved by motor transport in 1982 was 16.4 kilometres (10.2 mi), while the average for railway transport was 930 km per ton and 435 km per ton for water freight. In 1982 there was a threefold increase in investment since 1960 in motor freight transport, and more than a thirtyfold increase since 1940.”

March 3, 2016 Posted by | Biology, Cryptography, History, language, Lectures, Random stuff, Wikipedia, Zoology | Leave a comment

A couple of lectures and a little bit of random stuff

i. Two lectures from the Institute for Advanced Studies:

The IAS has recently uploaded a large number of lectures on youtube, and the ones I blog here are a few of those where you can actually tell from the title what the lecture is about; I find it outright weird that these people don’t include the topic covered in the lecture in their lecture titles.

As for the video above, as usual for the IAS videos it’s annoying that you can’t hear the questions asked by the audience, but the sound quality of this video is at least quite a bit better than the sound quality of the video below (which has a couple of really annoying sequences, in particular around the 15-16 minutes mark (it gets better), where the image is also causing problems, and in the last couple of minutes of the Q&A things are also not exactly optimal as the lecturer leaves the area covered by the camera in order to write something on the blackboard – but you don’t know what he’s writing and you can’t see the lecturer, because the camera isn’t following him). I found most of the above lecture easier to follow than I did the lecture posted below, though in either case you’ll probably not understand all of it unless you’re an astrophysicist – you definitely won’t in case of the latter lecture. I found it helpful to look up a few topics along the way, e.g. the wiki articles about the virial theorem (/also dealing with virial mass/radius), active galactic nucleus (this is the ‘AGN’ she refers to repeatedly), and the Tully–Fisher relation.

Given how many questions are asked along the way it’s really annoying that you in most cases can’t hear what people are asking about – this is definitely an area where there’s room for improvement in the context of the IAS videos. The lecture was not easy to follow but I figured along the way that I understood enough of it to make it worth watching the lecture to the end (though I’d say you’ll not miss much if you stop after the lecture – around the 1.05 hours mark – and skip the subsequent Q&A). I’ve relatively recently read about related topics, e.g. pulsar formation and wave- and fluid dynamics, and if I had not I probably would not have watched this lecture to the end.

ii. A update. I’m slowly working my way up to the ‘Running Dictionary’ rank (I’m only a walking dictionary at this point); here’s some stuff from my progress page:

I recently learned from a note added to a list that I’ve actually learned a very large proportion of all words available on, which probably also means that I may have been too harsh on the word selection algorithm in past posts here on the blog; if there aren’t (/m)any new words left to learn it should not be surprising that the algorithm presents me with words I’ve already mastered, and it’s not the algorithm’s fault that there aren’t more words available for me to learn (well, it is to the extent that you’re of the opinion that questions should be automatically created by the algorithm as well, but I don’t think we’re quite there yet at this point). The aforementioned note was added in June, and here’s the important part: “there are words on your list that can’t teach yet. can teach over 12,000 words, but sadly, these aren’t among them”. ‘Over 12.000’ – and I’ve mastered 11.300. When the proportion of mastered words is this high, not only will the default random word algorithm mostly present you with questions related to words you’ve already mastered; but it actually also starts to get hard to find lists with many words you’ve not already mastered – I’ll often load lists with one hundred words and then realize that I’ve mastered every word on the list. This is annoying if you have a desire to continually be presented with both new words as well as old ones. Unless increases the rate with which they add new words I’ll run out of new words to learn, and if that happens I’m sure it’ll be much more difficult for me to find motivation to use the site.

With all that stuff out of the way, if you’re not a regular user of the site I should note – again – that it’s an excellent resource if you desire to increase your vocabulary. Below is a list of words I’ve encountered on the site in recent weeks(/months?):

Copaceticfrumpyelisiontermagantharridanquondam, funambulist, phantasmagoriaeyelet, cachinnate, wilt, quidnunc, flocculent, galoot, frangible, prevaricate, clarion, trivet, noisome, revenant, myrmidon (I have included this word once before in a post of this type, but it is in my opinion a very nice word with which more people should be familiar…), debenture, teeter, tart, satiny, romp, auricular, terpsichorean, poultice, ululation, fusty, tangy, honorarium, eyas, bumptious, muckraker, bayou, hobble, omphaloskepsis, extemporize, virago, rarefaction, flibbertigibbet, finagle, emollient.

iii. I don’t think I’d do things exactly the way she’s suggesting here, but the general idea/approach seems to me appealing enough for it to be worth at least keeping in mind if I ever decide to start dating/looking for a partner.

iv. Some wikipedia links:

Tarrare (featured). A man with odd eating habits and an interesting employment history (“Dr. Courville was keen to continue his investigations into Tarrare’s eating habits and digestive system, and approached General Alexandre de Beauharnais with a suggestion that Tarrare’s unusual abilities and behaviour could be put to military use.[9] A document was placed inside a wooden box which was in turn fed to Tarrare. Two days later, the box was retrieved from his excrement, with the document still in legible condition.[9][17] Courville proposed to de Beauharnais that Tarrare could thus serve as a military courier, carrying documents securely through enemy territory with no risk of their being found if he were searched.” Yeah…).

Cauda equina syndromeCastleman’s disease, Astereognosis, Familial dysautonomia, Homonymous hemianopsia, Amaurosis fugax. All of these are of course related to content covered in the Handbook.

1740 Batavia massacre (featured).

v. I am also fun.

October 30, 2015 Posted by | Astronomy, History, Immunology, language, Lectures, Medicine, Neurology, Personal, Physics, Random stuff, Wikipedia | Leave a comment

Random Stuff / Open Thread

This is not a very ‘meaty’ post, but it’s been a long time since I had one of these and I figured it was time for another one. As always links and comments are welcome.

i. The unbearable accuracy of stereotypes. I made a mental note of reading this paper later a long time ago, but I’ve been busy with other things. Today I skimmed it and decided that it looks interesting enough to give it a detailed read later. Some remarks from the summary towards the end of the paper:

“The scientific evidence provides more evidence of accuracy than of inaccuracy in social stereotypes. The most appropriate generalization based on the evidence is that people’s beliefs about groups are usually moderately to highly accurate, and are occasionally highly inaccurate. […] This pattern of empirical support for moderate to high stereotype accuracy is not unique to any particular target or perceiver group. Accuracy has been found with racial and ethnic groups, gender, occupations, and college groups. […] The pattern of moderate to high stereotype accuracy is not unique to any particular research team or methodology. […] This pattern of moderate to high stereotype accuracy is not unique to the substance of the stereotype belief. It occurs for stereotypes regarding personality traits, demographic characteristics, achievement, attitudes, and behavior. […] The strong form of the exaggeration hypothesis – either defining stereotypes as exaggerations or as claiming that stereotypes usually lead to exaggeration – is not supported by data. Exaggeration does sometimes occur, but it does not appear to occur much more frequently than does accuracy or underestimation, and may even occur less frequently.”

I should perhaps note that this research is closely linked to Funder’s research on personality judgment, which I’ve previously covered on the blog here and here.

ii. I’ve spent approximately 150 hours on altogether at this point (having ‘mastered’ ~10.200 words in the process). A few words I’ve recently encountered on the site: Nescience (note to self: if someone calls you ‘nescient’ during a conversation, in many contexts that’ll be an insult, not a compliment) (Related note to self: I should find myself some smarter enemies, who use words like ‘nescient’…), eristic, carrel, oleaginous, decal, gable, epigone, armoire, chalet, cashmere, arrogate, ovine.

iii. why p = .048 should be rare (and why this feels counterintuitive).

iv. A while back I posted a few comments on SSC and I figured I might as well link to them here (at least it’ll make it easier for me to find them later on). Here is where I posted a few comments on a recent study dealing with Ramadan-related IQ effects, a topic which I’ve covered here on the blog before, and here I discuss some of the benefits of not having low self-esteem.

On a completely unrelated note, today I left a comment in a reddit thread about ‘Books That Challenged You / Made You See the World Differently’ which may also be of interest to readers of this blog. I realized while writing the comment that this question is probably getting more and more difficult for me to answer as time goes by. It really all depends upon what part of the world you want to see in a different light; which aspects you’re most interested in. For people wondering about where the books about mathematics and statistics were in that comment (I do like to think these fields play some role in terms of ‘how I see the world‘), I wasn’t really sure which book to include on such topics, if any; I can’t think of any single math or stats textbook that’s dramatically changed the way I thought about the world – to the extent that my knowledge about these topics has changed how I think about the world, it’s been a long drawn-out process.

v. Chess…

People who care the least bit about such things probably already know that a really strong tournament is currently being played in St. Louis, the so-called Sinquefield Cup, so I’m not going to talk about that here (for resources and relevant links, go here).

I talked about the strong rating pools on ICC not too long ago, but one thing I did not mention when discussing this topic back then was that yes, I also occasionally win against some of those grandmasters the rating pool throws at me – at least I’ve won a few times against GMs by now in bullet. I’m aware that for many ‘serious chess players’ bullet ‘doesn’t really count’ because the time dimension is much more important than it is in other chess settings, but to people who think skill doesn’t matter much in bullet I’d say they should have a match with Hikaru Nakamura and see how well they do against him (if you’re interested in how that might turn out, see e.g. this video – and keep in mind that at the beginning of the video Nakamura had already won 8 games in a row, out of 8, against his opponent in the first games, who incidentally is not exactly a beginner). The skill-sets required do not overlap perfectly between bullet and classical time control games, but when I started playing bullet online I quickly realized that good players really require very little time to completely outplay people who just play random moves (fast). Below I have posted a screencap I took while kibitzing a game of one of my former opponents, an anonymous GM from Germany, against whom I currently have a 2.5/6 score, with two wins, one draw, and three losses (see the ‘My score vs CPE’ box).

Kibitzing GMs(click to view full size).

I like to think of a score like this as at least some kind of accomplishment, though admittedly perhaps not a very big one.

Also in chess-related news, I’m currently reading Jesús de la Villa’s 100 Endgames book, which Christof Sielecki has said some very nice things about. A lot of the stuff I’ve encountered so far is stuff I’ve seen before, positions I’ve already encountered and worked on, endgame principles I’m familiar with, etc., but not all of it is known stuff and I really like the structure of the book. There are a lot of pages left, and as it is I’m planning to read this book from cover to cover, which is something I usually do not do when I read chess books (few people do, judging from various comments I’ve seen people make in all kinds of different contexts).

Lastly, a lecture:

August 25, 2015 Posted by | Biology, Books, Chess, language, Lectures, Personal, Psychology, Statistics | 2 Comments

(10.000) Words…

“The language denotes the man. A coarse or refined character finds its expression naturally in a coarse or refined phraseology.” (Christian Nestell Bovee)


(Click to view details/full size)

Doff, pabulum, astringent, enervate, mountebank, argot, sluice, sequin, indite, vitiate, simper, tarry, casuistry, saturnine, sidle, meretricious, fugacious, esurient, scabrous, disquisition, winsome, sedulous, badinage, abeyance, effrontery, minatory, synecdoche, lubricious, adjure, asperse, encumbrance, careen, desuetude, syllepsis, limn, bathetic, surcease, taut, tribulation, chrysalis, farrier, vane, virago, rictus, gewgaw, vituperate, curdleichthyology, abrogate, stultify, approbatory, intrepid, nugatory, contumacious, append, vociferate, tenebrous, arrogate, vermilion, descry, sententious, repine, procrustean, undulate, abstemious, palter, iniquitous, endue, lugubrious, obloquy, obdurate, importunate, apotheosis, obviateperegrinate, sacrum, …

In a way it makes absolutely no sense for someone like me to spend as much time on this stuff as I have over the last year or two; I almost never engage in conversations with other people as I rarely interact with other people at all (and also tend to avoid conversations when I do because conversations are usually unpleasant), and when I do both interact and converse with other people I only rarely engage in conversations in English as my first language, and the first language of most of the people with whom I interact regularly, is Danish. If the aim were to improve my vocabulary in order to hide my stupidity (‘make me look smarter’), I’d do a lot better by learning some more fancy-sounding Danish words. As it is, I can’t even remember the last time I last looked up a word in a Danish dictionary, but it’s been at least a few years (if not much more than that). Of course on the other hand I do read a lot of books, and I only read books in English. So it’s probably not a complete waste of time. But I’ve been thinking lately that I might derive a lot more benefit from these sorts of activities, in the sense that more words would ‘stick’, if I actually had to interact with other people in English on a daily basis. It seems to me likely that in a sense my language production capabilities might not be improved as much by these activities as are my language consumption capabilities. What I mean by this is that I frequently encounter new words I’ve worked on in the books I read, but at the same time I’m very rarely forced to ever actually use any of them in conversations with other people, so I don’t. I don’t know enough about linguistics to tell if this distinction between production and consumption matters, but it seems to me that it might. On a related note I’ve recently had the idea that my activities in these areas might implicitly be lowering my opportunity costs of book-reading, compared to personal interactions with others, because these activities make it easier for me to read books but does not at the same time much improve upon my social skills (e.g. conversational skills; though I’m on a related note open to the suggestion that conversational skills and vocabulary size are in some contexts relevant to this discussion in fact perhaps best conceived of as orthogonal variables (which doesn’t help at all…)) – which is hardly what I would conceive of as a desirable outcome. Oh well.

As you should have been able to infer from the screencap above and/or the post title, I’ve by now reached another major milestone (here’s the first one) on the site as I have now ‘mastered’ more than 10.000 words on the site – I figured it made sense to make a post about this and related matters, and this is the post in question. In the time that has passed since I wrote the post to which I link above the site has undergone a few minor changes, but actually most of it works pretty much the same way it did last year; if you’re curious about how the site works and you have not heard about it before, go have a look at that post before reading on. As I have noted before I don’t fully trust the dictionary; or at least I like Webster’s online dictionary better, which is why the links above are all to Webster entries. I’ll often ‘check out’ particular words which I’m curious about after having encountered them on, because sometimes specific interpretations of the words in question are simply wrong, or at least so I would argue; if the site is trying to tell me that a specific word means X, but I ‘know’ that it doesn’t and the Webster entry also provides zero support for this specific usage/interpretation – or actively ‘disagrees’ – then I go with Webster and I’ll get annoyed at the people behind (again). One thing to note when making comparisons here is that in general I believe that the dictionary has a greater ‘range’ of meanings covered, which also means that if you look up the entries to which I link above you might fail to appreciate how many different types of questions that might be required for someone to ‘master’ the words on; if the word has some rare meaning in a very specific context, you can expect to ask you about that before you master the word (and you can expect a subset of those questions to be poorly worded, making you angry at the programmers behind the site). This also means that even if you think you know a word, the site may still cause you some challenges along the way.

I’ve used the site pretty much every week during the last year, though in some periods I used the site very little; the relative inactivity meant that I dropped out of the top 100 list for a while, but over the last weeks I’ve done some more work on the site, and I’m now back in the top 100. So I seem to focus more on improving my vocabulary than do most users on the site, which I actually find somewhat curious given that this tool has apparently been introduced to thousands of children throughout the US. On the other hand I’ve put in a lot of hours when you add them all together (the site actually logging the hours you put in is incidentally a new feature which was not present when I posted my first couple of posts about the site a year ago; I actually didn’t like this feature to start with, in part because I realized how much time I’d spent on this stuff).

The site is in my opinion very bad at explaining how to properly use the site to learn new words in the semi-long run, so I should probably explain why I recently came to ‘rediscover’ my joy of using the site. The main factor rekindling my interest was that I discovered how to use ‘lists’ to focus on new words. If you play the challenge without any bells and whistles and never add lists or anything, you’ll at some point get to a situation where you may well be given 500 questions without ‘mastering’ more than one or two new words; the site will recycle and recycle, asking you hundreds of questions about words you’ve already mastered and occasionally ask you about a new word which you’ll never get enough questions about to actually ever master – this is incredibly frustrating, to the point where I last year decided to send the staff an email suggesting they make changes to the algorithms, because this just seemed insane and probably killed the motivation for a lot of users. You’d put in 20 hours almost without being allowed to actually achieve mastery of any of the new words, then suddenly you’d ‘master’ more than a thousand words one after the other because now suddenly the site could be bothered to finally allow you to show that you’ve mastered those words the site last asked you about last April – or whenever. Or not – I have a suspicion that a lot of users have given up before this point was reached and just said ‘screw this’ before getting to the mastery questions at the end of the line, and that stuff like this may be part of the reason why I’m in the top 100 list now. If this is true it’s sort of sad, because it seems like such a big missed opportunity; what you’d ideally want is not just a site useful for learning a few thousand words after which the way the site is coded will contribute strongly to making many people sick of it, but rather a site which mixes new words and old in an optimal manner which might encourage users to keep using the site in the long run. People may argue about what’s an optimal mix, but I don’t think you can argue with a straight face that the current configuration is anywhere near this point – and if the perceived optimal mix is different for different people, why not allow users to have an influence on this variable in the first place? In a way the site implicitly does, in an admittedly roundabout manner, give people some influence on these sorts of variables via the lists, but I remained unaware of this for a very long time so a lot of users presumably don’t know this. Either way I certainly think I’m justified in assuming that far more care has been taken to optimize the user experience early on than has been taken to making sure the site remains useful even to people who’ve already mastered a lot of words; I’d argue that the site has an excessive focus on review questions, compared to questions about new words, and from personal experience it has seemed to me that this problem seems to get bigger and bigger the more words you learn.

Adding to the problems mentioned above it also does not help that some of the review questions – not many of them, but some – are so poorly thought out that you can’t really tell what the right answer is supposed to be despite knowing very well what the word means, so you risk getting stuck in loops where a substantial proportion of the questions you’re asked are about words you already know at least in part because the questions are bad (if you answer a tricky review question like that incorrectly, you’ll be given quite a few more other questions in the future about this word you don’t care about and don’t want to answer questions about anymore, because an incorrect answer to a review question is always taken by the site as an indication that you don’t understand the word as well as you should, and never as an indication that someone should seriously have a closer look at some of those shitty questions (again, there aren’t that many of them, but they’re very annoying to someone like me)).

So in short, if you’re contemplating using the site or already does, don’t do what I did – instead of just playing the basic challenge, at some point it becomes necessary to instead start exploring the lists. If you add a list to learn, the site will mostly (though not exclusively) focus on the words on the list you’re currently learning, avoiding the outcome outlined above. You can add more than one list simultaneously. I’ll put it bluntly – if you don’t use lists, this site will eventually kill pretty much all desire to use it, because you’ll eventually get to a point where you’ll feel you’re not making any progress and you’ll also at the same time have the distinct impression that the site actively refuses to give you any opportunities to making progress. I can’t be the only person who until recently did not use lists, and frankly without lists this site is a disaster waiting to happen. If you use lists well, it is however a very useful tool.

The site does not help you with grammar – if you know about a site that does, I’d be curious to know about it in the comments below. On a related note I thought I should end this post with this quite amusing quote from Jerome Jerome’s book Three Men on the Bummel, published in 1900:

“In the course of the century, I am inclined to think that Germany will solve her difficulty in this respect by speaking English. Every boy and girl in Germany, above the peasant class, speaks English. Were English pronunciation less arbitrary, there is not the slightest doubt but that in the course of a very few years, comparatively speaking, it would become the language of the world. All foreigners agree that, grammatically, it is the easiest language of any to learn. A German, comparing it with his own language, where every word in every sentence is governed by at least four distinct and separate rules, tells you that English has no grammar. A good many English people would seem to have come to the same conclusion; but they are wrong. As a matter of fact, there is an English grammar, and one of these days our schools will recognise the fact, and it will be taught to our children, penetrating maybe even into literary and journalistic circles. But at present we appear to agree with the foreigner that it is a quantity neglectable. English pronunciation is the stumbling-block to our progress. English spelling would seem to have been designed chiefly as a disguise to pronunciation. It is a clever idea, calculated to check presumption on the part of the foreigner; but for that he would learn it in a year.”

June 1, 2015 Posted by | language, Personal, Quotes/aphorisms | Leave a comment

Random stuff/Open Thread

i. A lecture on mathematical proofs:

ii. “In the fall of 1944, only seven percent of all bombs dropped by the Eighth Air Force hit within 1,000 feet of their aim point.”

From wikipedia’s article on Strategic bombing during WW2. The article has a lot of stuff. The ‘RAF estimates of destruction of “built up areas” of major German cities’ numbers in the article made my head spin – they didn’t bomb the Germans back to the stone age, but they sure tried. Here’s another observation from the article:

“After the war, the U.S. Strategic Bombing Survey reviewed the available casualty records in Germany, and concluded that official German statistics of casualties from air attack had been too low. The survey estimated that at a minimum 305,000 were killed in German cities due to bombing and estimated a minimum of 780,000 wounded. Roughly 7,500,000 German civilians were also rendered homeless.” (The German population at the time was roughly 70 million).

iii. Also war-related: Eddie Slovik:

Edward Donald “Eddie” Slovik (February 18, 1920 – January 31, 1945) was a United States Army soldier during World War II and the only American soldier to be court-martialled and executed for desertion since the American Civil War.[1][2]

Although over 21,000 American soldiers were given varying sentences for desertion during World War II, including 49 death sentences, Slovik’s was the only death sentence that was actually carried out.[1][3][4]

During World War II, 1.7 million courts-martial were held, representing one third of all criminal cases tried in the United States during the same period. Most of the cases were minor, as were the sentences.[2] Nevertheless, a clemency board, appointed by the Secretary of War in the summer of 1945, reviewed all general courts-martial where the accused was still in confinement.[2][5] That Board remitted or reduced the sentence in 85 percent of the 27,000 serious cases reviewed.[2] The death penalty was rarely imposed, and those cases typically were for rapes or murders. […] In France during World War I from 1917 to 1918, the United States Army executed 35 of its own soldiers, but all were convicted of rape and/or unprovoked murder of civilians and not for military offenses.[13] During World War II in all theaters of the war, the United States military executed 102 of its own soldiers for rape and/or unprovoked murder of civilians, but only Slovik was executed for the military offense of desertion.[2][14] […] of the 2,864 army personnel tried for desertion for the period January 1942 through June 1948, 49 were convicted and sentenced to death, and 48 of those sentences were voided by higher authority.”

What motivated me to read the article was mostly curiosity about how many people were actually executed for deserting during the war, a question I’d never encountered any answers to previously. The US number turned out to be, well, let’s just say it’s lower than I’d expected it would be. American soldiers who chose to desert during the war seem to have had much, much better chances of surviving the war than had soldiers who did not. Slovik was not a lucky man. On a related note, given numbers like these I’m really surprised desertion rates were not much higher than they were; presumably community norms (”desertion = disgrace’, which would probably rub off on other family members…’) played a key role here.

iv. Chess and infinity. I haven’t posted this link before even though the thread is a few months old, and I figured that given that I just had a conversation on related matters in the comment section of SCC (here’s a link) I might as well repost some of this stuff here. Some key points from the thread (I had to make slight formatting changes to the quotes because wordpress had trouble displaying some of the numbers, but the content is unchanged):

“Shannon has estimated the number of possible legal positions to be about 1043. The number of legal games is quite a bit higher, estimated by Littlewood and Hardy to be around 1010^5 (commonly cited as 1010^50 perhaps due to a misprint). This number is so large that it can’t really be compared with anything that is not combinatorial in nature. It is far larger than the number of subatomic particles in the observable universe, let alone stars in the Milky Way galaxy.

As for your bonus question, a typical chess game today lasts about 40­ to 60 moves (let’s say 50). Let us say that there are 4 reasonable candidate moves in any given position. I suspect this is probably an underestimate if anything, but let’s roll with it. That gives us about 42×50 ≈ 1060 games that might reasonably be played by good human players. If there are 6 candidate moves, we get around 1077, which is in the neighbourhood of the number of particles in the observable universe.”

“To put 1010^5 into perspective:

There are 1080 protons in the Universe. Now imagine inside each proton, we had a whole entire Universe. Now imagine again that inside each proton inside each Universe inside each proton, you had another Universe. If you count up all the protons, you get (1080 )3 = 10240, which is nowhere near the number we’re looking for.

You have to have Universes inside protons all the way down to 1250 steps to get the number of legal chess games that are estimated to exist. […]

Imagine that every single subatomic particle in the entire observable universe was a supercomputer that analysed a possible game in a single Planck unit of time (10-43 seconds, the time it takes light in a vacuum to travel 10-20 times the width of a proton), and that every single subatomic particle computer was running from the beginning of time up until the heat death of the Universe, 101000 years ≈ 1011 × 101000 seconds from now.

Even in these ridiculously favorable conditions, we’d only be able to calculate

1080 × 1043 × 1011 × 101000 = 101134

possible games. Again, this doesn’t even come close to 1010^5 = 10100000 .

Basically, if we ever solve the game of chess, it definitely won’t be through brute force.”

v. An interesting resource which a friend of mine recently shared with me and which I thought I should share here as well: Nature Reviews – Disease Primers.

vi. Here are some words I’ve recently encountered on augury, spangle, imprimatur, apperception, contrition, ensconce, impuissance, acquisitive, emendation, tintinnabulation, abalone, dissemble, pellucid, traduce, objurgation, lummox, exegesis, probity, recondite, impugn, viscid, truculence, appurtenance, declivity, adumbrate, euphony, educe, titivate, cerulean, ardour, vulpine.

May 16, 2015 Posted by | Chess, Computer science, History, language, Lectures, Mathematics | Leave a comment


i. Troubadour, gainsay, sordid, repast, calumniate, skinflint, gentile, enjoin, prestidigitation, compunction, madrigal, bacchanalian, reify, effete, seamy, betoken, codicil, peripatetic, reactionary, mendicant, osculate, expiation, propitiation, viand, panegyric, fulsome, paean, rarefied, vitiate, bibulous, delineate, wistful, hirsute, staid, bandy, mettle, saturnine, prorogue, legerdemain, caesura, dilatory, prolix, din, hoary, obsequious, spoonerism, gratuitous, diverting, contrite, grouse, preen, poignant, roil, aver, importune, lampoon, flagitious, expedient, parlous, obdurate, piebald, dolorous, parsimony, mawkish, natty, blithely, fractious, pique, bathos, cant, recreant, plumb, diaphanous, argot, ursine, frisson, insouciant, meretricious, upbraid, pugnacious, curate, plaintively, spate, cabal, slake, odium, encomium, mulct, turgid, disport, ply, cavort, cloying, sable, svelte, idempotent, teleological, inchoate, comity, bucolic.

The above is a list of the first 100 words I’ve ‘mastered’ on the site. Of course I knew some of them already, but I’ve also learned quite a few new words here along the way and it’d be incorrect to say that I haven’t also gotten a better grasp of some of the words with which I was already familiar. Here’s how it works. A few of the assessment questions so far have been in my opinion really poor (allowing for multiple correct answers, only one of which is accepted as correct), but in general this seems like an extremely useful site and the site does allow you to provide feedback if you think a question is poorly worded.

Do note that average vocabulary sizes are really rather small, all things considered: “Most adult native test-takers range from 20,000-35,000 words”. I think that you can probably progress rather rapidly with a tool like this, if you use it consistently. Note that the site doesn’t completely stop asking you questions about the words you’ve ‘mastered’; brush-up questions are added occasionally to aid retention. The starting point is as far as I can remember based on educational background, so if you’re a graduate student you shouldn’t worry that the site will start out by asking you if you know the word ‘house’ or ‘cat’. I’m pretty sure even walking dictionaries will find plenty of words along the way that they are unfamiliar with.

I’ll probably stop going on about the site now, but I really like it at this point and so I figured I should post at least a few posts about it before letting it go. It’s a very neat tool.

ii. For the last two years I have been involved in a medical trial aimed at figuring out if a specific drug might be used to delay the development of retinopathy in diabetics. My participation in the trial ended this week. The trial was more or less a direct result of a smaller trial in which I also participated, which showed some promising initial results – here’s the relevant paper. The researcher conducting the trial I just participated in will publish a paper about it later on, and I’ll naturally blog that when it’s published. There has been talk about continuing the project (/…that is, starting a new project) for the participants who got the active drug – half of the people in this trial got placebo – in order to increase the follow-up period. If I got the active drug (whether or not I did is not clear at this point, but I’ll be told relatively soon) I’ll probably participate in the new trial as well. No, the person who’s going to analyze the data will not be told whether or not I got the active drug – I asked about this part, but the study design is such that the double blind aspect is not compromised; the researcher who’ll figure out whether or not I got the active drug is not involved in the data analysis at all.

Medical trials often have trouble finding participants and selection into such trials is far from random. If you live in Denmark, you should check out this site. I assume similar resources exist in other countries…

A couple more 60 symbols videos below. I’ve now watched most of the videos they’ve posted, and I really like this stuff:

“He was a very strange man. And yet he’s absolutely wonderful!” – I could easily have said something similar about him. I’d much, much rather spend time with someone like that than with a ‘normal’ (boring) person. (Here’s a related link. Also, this.)

iv. The Relationship between Anxiety and the Social Judgements of Approachability And Trustworthiness:

“The aim of the current study was to examine the relationship between individual differences in anxiety and the social judgements of trustworthiness and approachability. We assessed levels of state and trait anxiety in eighty-two participants who rated the trustworthiness and approachability of a series of unexpressive faces. Higher levels of trait anxiety (controlling for age, sex and state anxiety) were associated with the judgement of faces as less trustworthy. In contrast, there was no significant association between trait anxiety and judgements of approachability. These findings indicate that trait anxiety is a significant predictor of trustworthiness evaluations and illustrate the importance of considering the role of individual differences in the evaluation of trustworthiness. We propose that trait anxiety may be an important variable to control for in future studies assessing the cognitive and neural mechanisms underlying trustworthiness. This is likely to be particularly important for studies involving clinical populations who often experience atypical levels of anxiety.”

v. Mass extinction of lizards and snakes at the Cretaceous – Paleogene boundary:

“The Cretaceous–Paleogene (K-Pg) boundary is marked by a major mass extinction, yet this event is thought to have had little effect on the diversity of lizards and snakes (Squamata). A revision of fossil squamates from the Maastrichtian and Paleocene of North America shows that lizards and snakes suffered a devastating mass extinction coinciding with the Chicxulub asteroid impact. Species-level extinction was 83%, and the K-Pg event resulted in the elimination of many lizard groups and a dramatic decrease in morphological disparity. Survival was associated with small body size and perhaps large geographic range. The recovery was prolonged; diversity did not approach Cretaceous levels until 10 My after the extinction, and resulted in a dramatic change in faunal composition. The squamate fossil record shows that the end-Cretaceous mass extinction was far more severe than previously believed, and underscores the role played by mass extinctions in driving diversification.”

A little more:

“Survival at the K-Pg boundary is highly nonrandom. Small size has been identified as a determinant of survival (36), yet size selectivity is evident even among the squamates. The most striking pattern is the extinction of all large lizards and snakes. […] The largest known early Paleocene lizard is Provaranosaurus acutus. Comparisons with varanids suggest an SVL [snout-vent length, US] of 305 mm and a mass of 415 g (Dataset S1), compared with an estimated SVL of 850 mm and mass of 6 kg for the largest Maastrichtian lizard, Palaeosaniwa. The largest early Paleocene snake is Helagras prisciformis, with an estimated SVL >950 mm and a mass >520 g, compared with >1,700 mm and 2.9 kg for the largest Maastrichtian snake, Cerberophis. […]

Size selectivity may help explain why nonavian dinosaurs became extinct, suggesting that it was nonavian dinosaurs’ failure to evolve a diverse fauna of small-bodied species, rather than a decrease in the diversity of large-bodied forms, that ultimately sealed their fate. A number of small, nonavian dinosaurs are now known from the Late Cretaceous, including alvarezsaurids (37) and microraptorine dromaeosaurids (38), and taphonomic biases almost certainly obscure the true diversity of small dinosaurs (38, 39). However, the fact remains that during the late Maastrichtian, small dinosaurs were vastly outnumbered by other small vertebrates, including a minimum of 30 squamates, 18 birds (15), and 50 mammal species (40). Strikingly, birds—the only dinosaurs to survive— were the only dinosaurs with a high diversity of smallbodied (<5 kg) forms (15). In this context, a discussion of a decline in large dinosaur diversity in the Maastrichtian (9) is perhaps beside the point. A high diversity of large herbivores and carnivores in the latest Maastrichtian would have been unlikely to change the fate of the nonavian dinosaurs, because no animals occupying these niches survived. Instead, the rarity of small dinosaurs—resulting perhaps from being outcompeted by squamates and mammals for these niches —led to their downfall. […]

Extinction at the K-Pg boundary was followed by recovery in the Paleocene and Eocene. A number of new lizard lineages occur in the basal Paleocene, notably the stem varanoid Provaranosaurus, xantusiids, and amphisbaenians (27). These may represent opportunistic invaders that colonized the area in the aftermath to exploit niches left vacant by the extinction, as seen among mammals (10, 44). Despite this, early Paleocene diversity is considerably lower than late Maastrichtian diversity (Fig. 3). Subsequently, ecological release provided by the extinction allowed the survivors to stage an adaptive radiation, paralleling the adaptive radiations staged by mammals (6, 45, 46), birds (46, 47), and fish (48). The community that emerges in the early Eocene is dominated by groups that are either minor components of the Cretaceous fauna or unknown from the Cretaceous […] diversity does not approach Cretaceous levels until the early Eocene, 10 My later […] Unlike mammals, […] squamates appear to have simply reoccupied the niches they occupied before the extinction. This reoccupation of niches was […] delayed; by the middle Paleocene, lizards had yet to recover the range of body sizes and morphotypes found in the Maastrichtian (Fig. 5).”

October 4, 2013 Posted by | Biology, Ecology, language, Lectures, Medicine, Paleontology, Personal, Physics, Psychology, Studies, Zoology | Leave a comment

The Mating Mind: How Sexual Choice Shaped the Evolution of Human Nature (2)

Given the title of the post and some of the material covered, this post may by some be considered NSFW. I don’t know. Now you’re warned anyway.

I finished the book. My goodreads review reads as follows:

“Torn between two stars and three, I may still decide to give it two stars. First half was interesting (3,5 stars), second half was in my opinion very weak (1,5 stars). I was close to not finishing it. Very speculative, especially towards the end – it devolves into more or less pure storytelling.”

I’m quite disappointed. There’s good stuff in the second half, especially in the first part of the second half, but there’s a lot of crap too – chapter 9 was weak, and chapter 10 was bad too. Some of the stuff looked to me to be pretty much nothing but wild speculation supported by very little evidence, and bad evidence at that. Even worse, I get the distinct impression at least a few places that he seems to deliberately pick evidence that supports his views even though different evidence (and more relevant evidence) might very well lead to different conclusions – why would you use the vocabulary size of modern English speakers (60.000 words) to infer stuff about the language abilities and behaviours of our far ancestors, when it would presumably be much more informative to look at the vocabulary sizes of e.g. today’s Bushmen or Australian Aboriginals? And to which extent does it even make sense to make such inferences in the first place? On a different if related note he at one point spends a couple of pages to motivate why the reciprocity theory of courtship is obviously wrong, but what he’s actually arguing against is a straw-man that is very hard to take seriously and seems completely irrelevant to the validity of the model. He employs manipulative argumental strategies along the way more than once and when he does this it makes it hard for me not to jump to the conclusion that his arguments stink even though they may not actually do so – I don’t like it when I get the impression that someone is trying to manipulate me, and Miller comes off as occasionally quite manipulative to me in this book.

Anyway, some quotes from the last half as well as a few comments. I’ve mostly (but not only) quoted from the good stuff because I don’t want to spend a lot of time on the other stuff:

“When we see a human perceptual or cognitive ability that looks curiously sensitive to stimulation yet resistant to satisfaction, we should not assume that it is a poorly designed information processing system. It may be part of a system for sexual or social discrimination. […] Female orgasm seems poorly designed as a pair-bonding mechanism, but it is perfectly designed as a discriminatory system that separates the men from the boys.”

“It seems likely that male choice shaped breasts not to distinguish girls from young women, but to distinguish young women from older women. Here, the informative thing about breasts is the way they droop with the effects of age and gravity. There is a relatively narrow age window in which large breasts can appear pert before repeated cycles of pregnancy and breast-feeding causes them to sag. There were no bras or breast-lift operations in the Pleistocene. […] hominid males probably favoured younger women for their higher fertility. Any indicator of youth, such as large, pert breasts, would tend to be favoured by males. […] an attractiveness benefit in youth can often outweigh an unattractiveness cost in older age. This is why it can be in the interest of females to evolve youth indicators such as large breasts that tend to droop, fine skin that tends to wrinkle, and buttocks that tend to develop stretch marks. […] women with more symmetric breasts tend to be more fertile. […] The larger the breasts, the easier it is to notice asymmetries. […] The role of breasts as fitness indicators may help to explain why there is so much variation in breast size between women. […] fitness indicators do not tend to converge on a single size in a population. They maintain their variation indefinitely, due to the effects of genetic mutation and variation in condition.”

“Most evolutionary psychologists have viewed human morality as a question of altruism, and have tried to explain altruism as a side-effect of instincts for nepotism (kindness to those who may reciprocate). I think human morality is much more likely to be a direct result of sexual judgments today because our ancestors favored sexual partners who were kind, generous, helpful, and fair. We still have the same preferences. David Buss’s study of global sexual preferences found that ‘kindness’ was the single most important feature desired in a sexual partner by both men and women in every one of the 37 cultures he studied. It ranked above intelligence, above beauty, and above status.” (If not for the fact that he actually thinks this stuff is true, it’d be hilarious. Here’s a link. I’m pretty sure Buss’s study belongs in the “completely useless” category. This is just stupid.)

“Ecologists have long understood that the typical interaction between any two individuals or species is neither competition nor cooperation, but neutralism. Neutralism means apathy: the animals just ignore each other. If their paths threaten to cross, they get out of each other’s way. Anything else usually takes too much energy. Being nasty has costs, and being nice has costs, and animals evolve to avoid costs whenever possible. […] most of the violent competition happens within a species, because animals of the same species are competing for the same resources and the same mates. […] If we were typical animals, our attitudes to others would be dominated not by hate, exploitation, spite, competitiveness, or treachery, but by indifference. And so they are.”

“Verbal courtship can be viewed narrowly as face-to-face flirtation, or broadly as anything we say in public that might increase our social status or personal attractiveness in the eyes of potential mates. […] Verbal courtship in the broader sense explains why we compete to say interesting, relevant things in groups. Sexual choice permeates human social life, because anything that raises social status tends to improve mating prospects.” […] In cooperative communication, the receiver may be mildly skeptical about the information conveyed. In courtship, the receiver is extremely judgmental not only about the information, but about the signaller. When listening, we automatically evaluate whether what is being said makes sense, whether it is congruent with what we know and believe, whether it is novel and interesting, and whether we can draw intriguing inferences from it. But we also use all of these judgments to form an impression of the speaker’s intelligence, creativity, knowledge, status, and personality. We assess the information content of utterances not just to make inferences about the world, but to make attributions about the speaker.”

“People tend to socialize with friends and sexual partners who show roughly their own verbal ability level – their verbal compatibility has already determined which social relationships were formed. The majority of human conversation occurs between sexual partners and long-term friends. They have already chosen each other as mates or friends precisely because their first few conversations were mutually interesting, evoking mutual respect and attraction.”

“we present our lives in the best possible light. We mention our successes rather than our failures, impressive relatives rather than wastrels, dramatic trips more than solitary depressions, and palatable beliefs more than secret bigotries. Our life stories presents us as the heroes of the grand adventures that are our lives, rather than the Rosenkrantz and Guildenstern to someone else’s Hamlet. Nevertheless, because most people distort their life stories to more or less the same degree, they remain a valid basis for mate choice. Initially at least, our life stories will be compared not to the truth, but to the equally distorted life stories of our sexual competitors.” (No, honest signalling in this framework simply doesn’t make any sense. Lying isn’t optional.)

“How should we interpret the female superiority on language comprehension tests [“women comprehend more words on average, and this sex difference accounts for almost 5 percent of the individual variation in vocabulary size.”], given the greater male motivation to produce public verbal displays? The latter has not been so well quantified yet, but it is still obvious. Men write more books. Men give more lectures. Men ask more questions after lectures. Men dominate mixed-sex committee discussions. […] men can’t be quiet because that would give other men a chance to show off verbally. Men often bully women into silence, but this is usually to make room for their own display. ”

“Human courtship, like courtship in other animals, has a typical time-course. Courtship effort is low when first assessing a sexual prospect, increases rapidly if the prospect reciprocates one’s interest, peaks when the prospect is deciding whether to copulate, and declines once a long-term relationship is established.”

“People act differently when they’re in love with different people. We tend to match our expressed interests and preferences to those of a desired individual. […] In courtship, we work our way into roles that we think will prove attractive. […] Acting is not the prerogative of a few highly strung professionals, but a human birthright, automatically activated whenever we fall in love. In courtship, all the world became a stage, and all the proto-humans merely players.” (link in case you didn’t get the reference)

September 1, 2013 Posted by | Anthropology, Biology, Books, Ecology, Evolutionary biology, language, Psychology | 14 Comments


I thought I should update the blog even though these days I don’t do a lot of blogging-worthy stuff.

i. A blog I recently discovered: Empirical Zeal. There’s some interesting posts there, for example I liked this one on the state of Indian rural education (though the findings reported are not exactly worthy of celebration).

ii. The acquisition of language by children. From the introduction:

“Imagine that you are faced with the following challenge. You must discover the internal structure of a system that contains tens of thousands of units, all generated from a small set of materials. These units, in turn, can be assembled into an infinite number of combinations. Although only a subset of those combinations is correct, the subset itself is for all practical purposes infinite. Somehow you must converge on the structure of this system to use it to communicate. And you are a very young child.

This system is human language. The units are words, the materials are the small set of sounds from which they are constructed, and the combinations are the sentences into which they can be assembled. Given the complexity of this system, it seems improbable that mere children could discover its underlying structure and use it to communicate. Yet most do so with eagerness and ease, all within the first few years of life.”

It’s actually pretty wild, once you start thinking about it.

iii. The Null Ritual – What You Always Wanted to Know About Significance Testing but Were Afraid to Ask (via Gwern? I no longer remember how I found this.). An excerpt from the article:

“Question 1: What Does a Significant Result Mean?

What a simple question! Who would not know the answer? After all, psychology students spend months sitting through statistics courses, learning about null hypothesis tests (significance tests) and their featured product, the p-value. Just to be sure, consider the following problem (Haller & Krauss, 2002; Oakes, 1986):

Suppose you have a treatment that you suspect may alter performance on a certain task. You compare the means of your control and experimental groups (say, 20 subjects in each sample). Furthermore, suppose you use a simple independent means t-test and your result is signifi cant (t = 2.7, df = 18, p = .01). Please mark each of the statements below as “true” or “false.” False means that the statement does not follow logically from the above premises. Also note that several or none of the statements may be correct.

(1) You have absolutely disproved the null hypothesis (i.e., there is no difference between the population means). ® True False ®
(2) You have found the probability of the null hypothesis being true. ® True False ®
(3) You have absolutely proved your experimental hypothesis (that there is a difference between the population means). ® True False ®
(4) You can deduce the probability of the experimental hypothesis being true. ® True False ®
(5) You know, if you decide to reject the null hypothesis, the probability that you are making the wrong decision. ® True False ®
(6) You have a reliable experimental finding in the sense that if, hypothetically, the experiment were repeated a great number of
times, you would obtain a significant result on 99% of occasions. ® True False ®

Which statements are true? If you want to avoid the I-knew-it-all-along feeling, please answer the six questions yourself before continuing to read. When you are done, consider what a p-value actually is: A p-value is the probability of the observed data (or of more extreme data points), given that the null hypothesis H0 is true, defined in symbols as p(D |H0).Th is defi nition can be rephrased in a more technical form by introducing the statistical model underlying the analysis (Gigerenzer et al., 1989, chap. 3). Let us now see which of the six answers are correct:

Statements 1 and 3: Statement 1 is easily detected as being false. A significance test can never disprove the null hypothesis. Significance tests provide probabilities, not definite proofs. For the same reason, Statement 3, which implies that a significant result could prove the experimental hypothesis, is false. Statements 1 and 3 are instances of the illusion of certainty (Gigerenzer, 2002).

Statements 2 and 4: Recall that a p-value is a probability of data, not of a hypothesis. Despite wishful thinking, p(D |H0) is not the same as p(H0 |D), and a significance test does not and cannot provide a probability for a hypothesis. One cannot conclude from a p-value that a hypothesis has a probability of 1 (Statements 1 and 3) or that it has any other probability (Statements 2 and 4). Therefore, Statements 2 and 4 are false. The statistical toolbox, of course, contains tools that allow estimating probabilities of hypotheses, such as Bayesian statistics (see below). However, null hypothesis testing does not.

Statement 5: The “probability that you are making the wrong decision” is again a probability of a hypothesis. This is because if one rejects the null hypothesis, the only possibility of making a wrong decision is if the null hypothesis is true. In other words, a closer look at Statement 5 reveals that it is about the probability that you will make the wrong decision, that is, that H0 is true. Thus, it makes essentially the same claim as Statement 2 does, and both are incorrect.

Statement 6: Statement 6 amounts to the replication fallacy. Recall that a p-value is the probability of the observed data (or of more extreme data points), given that the null hypothesis is true. Statement 6, however, is about the probability of “significant” data per se, not about the probability of data if the null hypothesis were true. The error in Statement 6 is that p = 1% is taken to imply that such significant data would reappear in 99% of the repetitions. Statement 6 could be made only if one knew that the null hypothesis was true. In formal terms, p(D |H0) is confused with 1 – p(D). The replication fallacy is shared by many, including the editors of top journals. […] To sum up, all six statements are incorrect. Note that all six err in the same direction of wishful thinking: They overestimate what one can conclude from a p-value. […]

We posed the question with the six multiple-choice answers to 44 students of psychology, 39 lecturers and professors of psychology, and 30 statistics teachers […] How many students and teachers noticed that all of the statements were wrong? As Figure 1 shows, none of the students did. […] Ninety percent of the professors and lecturers also had illusions, a proportion almost as high as among their students. Most surprisingly, 80% of the statistics teachers shared illusions with their students.”

The article has much more.

iv. Diabetes in older Adults.

“More than 25% of the U.S. population aged [>65] years has diabetes (1), and the aging of the overall population is a significant driver of the diabetes epidemic. […] The incidence of diabetes increases with age until about age 65 years, after which both incidence and prevalence seem to level off”. I should have known the first number was in that neighbourhood, but somehow I had failed to realize that it was that high; most often prevalence estimates are calculated/reported using the entire population in the denominator, but of course such estimates can be deceiving if you do not think about how they are calculated and I clearly hadn’t. At least 1 in 4 in the above-65 age bracket. That’s a lot of people. The article doesn’t have a lot of data, it’s a ‘consensus report’ handling mostly various treatment guideline suggestions and similar stuff.

v. What is the most uncomfortable situation have you ever been put in- by a guy? Any kind of unwanted flirtation- or something of that nature (Reddit). Lots of really horrible stuff; reading stuff like this makes what might be perceived of as some females’ ‘somewhat overcautious’ behaviour towards members of the opposite sex easier to understand. An example from the link:

“The last stranger-danger moment I will share tonight was at an end-of-midterms party sponsored by the student union at a local bar. I was there with my best friend, and she’s very pretty and very friendly, so we’d very quickly attracted a group of four or five men who were hanging around with us for most of the night. I hadn’t seen any of them before, so I assumed they were students from a different department, and we end up getting a table together and talking for a while. Once my friend mentions that she has a boyfriend, most of them shift their attention to me, though there’s one who still seems interested in her. As I’m talking to them, I find that they’re not students at our university, but that they’re a group of friends visiting from the a couple towns over. Nothing too creepy, so far.

My friend finishes her drink, so the guy she’s talking to goes to buy her another. She’s a little suspicious, so she starts drinking it VERY slowly. Meanwhile, I’m getting distracted talking to one of the guys who works in the same field I’ll be entering soon, and we end up talking for a while about that. He keeps telling me that I’m very beautiful, which I keep brushing off because I knew he was interested in my friend initially, and I was interested in someone else at the time, anyway. Somewhere in the middle of all this, my friend has stopped drinking the drink that was bought for her, and someone asks if she’s going to finish it. She says no.

Eventually, the guy I’m talking to apologizes for his “bad” English, saying that he hasn’t really had to use it since he was in school, which was OVER TEN YEARS AGO. At about the same time, my friend is telling the guy she’s talking to that it’s funny that they decided to visit our city on that particular weekend, because this is a student end-of-midterm party, and he answers, “I know. That’s kind of why we came here.” Someone else asks my friend if she’s going to finish her drink, and she says no, but he can have it if he wants. The drink ‘accidentally’ gets spilled in the process, and she’s signalling me to get the fuck out of there, so I take the opportunity to drag her to the bathroom. I start to notice that she’s acting really fucked up – she can usually drink a ton more than I can, and she’d only had one drink of her own and maybe a third (probably less than that, actually) of the one that guy bought for her. She says she thinks the drink they gave her was drugged, and then she gets sick. I ended up staying the night at her place to keep an eye on her, but I didn’t think to take her to the hospital or anything, so I guess we’ll never know what exactly happened…”

Of course if you’re like me you don’t engage in risky behaviours like drinking with strangers and in that case it doesn’t really matter much if you’re male or female, but then again I’m not like normal people. Most males probably significantly underestimate how risky some of their behaviours – behaviours they would not ever even think of as ‘particularly risky’ – are when a female engages in them. Note that even males that fall into the “I can’t imagine you raising your voice”-category (a female friend said this about me in a conversation I had with her earlier today) are likely to be affected by the behaviours of the (type of) males described in the link; once a female has been through situations like the ones described at the link, she’s less likely to give males the benefit of the doubt and more likely to misinterpret behaviour and the motivations driving behaviour. Reading this stuff has made me believe that the behaviour of ‘overcautious’ females may be better justified and less ‘irrational’ than males tend to think it is.

vi. I haven’t commented on the new DSM-5 – let’s just say I’ve had better things to do. Here’s one take on it (“It’s arcane, contradictory and talks about invisible entities which no-one can really prove. Yes folks, the new psychiatric bible has been finalised.”). The most ‘relevant’ change to me is the fact that they’ll remove the Asperger Syndrome diagnosis, and instead merge it with other autism spectrum disorders. If you’re asking me what I think about that, the answer is that I don’t really care.

vii. Cheetahs on the Edge (via Ed Yong). A must-see:

“Using a Phantom camera filming at 1200 frames per second while zooming beside a sprinting cheetah, the team captured every nuance of the cat’s movement as it reached top speeds of 60+ miles per hour.

The extraordinary footage that follows is a compilation of multiple runs by five cheetahs during three days of filming.”

December 26, 2012 Posted by | autism, Biology, blogs, Diabetes, language, Psychology, Random stuff, Statistics, Zoology | Leave a comment

Wikipedia articles of interest

i. Silk Road.

“The Silk Routes (collectively known as the “Silk Road”) were important trade routes for goods of all kinds between merchants, pilgrims, missionaries, soldiers, nomads and urban dwellers from Ancient China, Ancient India, Ancient Tibet, the Persian Empire and Mediterranean countries for almost 3,000 years.[5] It gets its name from the lucrative Chinese silk trade, which began during the Han Dynasty (206 BCE – 220 CE).

Extending 4,000 miles (6,500 km), the routes enabled traders to transport goods, slaves and luxuries such as silk, satin, hemp and other fine fabrics, musk, other perfumes, spices, medicines, jewels, glassware and even rhubarb, as well as serving as a conduit for the spread of knowledge, ideas, cultures, zoological specimens and some non-indigenous disease conditions[6] between Ancient China, Ancient India, Asia Minor and the Mediterranean. Trade on the Silk Road was a significant factor in the development of the great civilizations of China, India, Egypt, Persia, Arabia, and Rome, and in several respects helped lay the foundations for the modern world. Although the term the Silk Road implies a continuous journey, very few who traveled the route traversed it from end to end. For the most part, goods were transported by a series of agents on varying routes and were traded in the bustling markets of the oasis towns.[6] […]

By the time of Herodotus (c. 475 BCE), the Persian Royal Road ran some 2,857 km from the city of Susa on the Karun (250 km east of the Tigris) to the port of Smyrna (modern İzmir in Turkey) on the Aegean Sea.[66] It was maintained and protected by the Achaemenid Empire (c.500–330 BCE), and had postal stations and relays at regular intervals. By having fresh horses and riders ready at each relay, royal couriers could carry messages the entire distance in nine days, though normal travellers took about three months. […]

The Mongol expansion throughout the Asian continent from around 1207 to 1360 helped bring political stability and re-establish the Silk Road (via Karakorum). It also brought an end to the Islamic Caliphate’s monopoly over world trade. Since the Mongol had dominated the trade routes, it allowed more trade to come in and out of the region. Merchandise that did not seem valuable to the Mongols was often seen as very valuable by the west. As a result, the Mongol received in return a large amount of luxurious goods from the West.”

The mongol? But those were just a small group of nomadic people living around the north-western borders of China, right – how come they had such a huge influence on world trade? Well, perhaps you know but a lot of people don’t: “[The Mongol Empire] is commonly referred to as the largest contiguous empire in the history of the world. At its greatest extent it spanned 9,700 km (6,000 mi), covered an area of 24,000,000 km2 (9,300,000 sq mi),[1][2][3][4] 16% of the Earth’s total land area”.

ii. House of Medici.

iii. Rosetta Stone (this is a featured article).

“The Rosetta Stone is an ancient Egyptian granodiorite stele inscribed with a decree issued at Memphis in 196 BC on behalf of King Ptolemy V. The decree appears in three scripts: the upper text is Ancient Egyptian hieroglyphs, the middle portion Demotic script, and the lowest Ancient Greek. Because it presents essentially the same text in all three scripts (with some minor differences between them), it provided the key to the modern understanding of Egyptian hieroglyphs.”

iv. RNA interference (this is also a featured article).

v. Timeline of Chinese history. It wouldn’t make sense to quote from this, but don’t miss it, at least go have a look. Here’s more.

vi. Blood type.

November 29, 2011 Posted by | Biology, Genetics, History, language, Medicine, Wikipedia | 1 Comment

Worth remembering (when comparing ‘the US’ to ‘Europe’)

People often note that it’s a bad idea to compare small European countries with a country that is so big that it is comparable in size to the continent that the small country is a part of. I’ll go into a bit more detail about the differences in this post.

So, in a comment I left over at MR I noted that:

‘The United States is 3 times as big as EU-15 used to be, and EU-15 included pretty much all of the countries in Western Europe that people from the US like to compare to their own country (Italy, Germany, Spain, France, UK, Sweden…)’

Here’s the map:

It’s not ‘completely true’, but it’s very close – the area of EU-15 was 3,367,154 km^2 (link). The area of the United States is 9.83 million km^2.

Some more random numbers, I used wikipedia’s numbers and I couldn’t be bothered to add links because it would have taken forever and nobody would follow them anyway – you can look it up if something sounds really wrong. Texas: 696,200 km^2. France: 674,843 km^2. (Metropolitan France – i.e. ‘France-France (+Corsica)’: 551,695 km^2). Spain: 504,030 km^2. California: 423,970 km^2. Germany: 357,021 km^2. Denmark: 43,075 km^2. Netherlands: 41,543 km^2.

The red bit in the picture below is larger than any country in Europe which is not Russia (or another way to visualize it: That bit is actually significantly larger than the Iberian Peninsula in the map above). Maybe the scales aren’t completely similar, but they’re actually not really that far off:

If you take a trip in Europe from Venezia, Italy to Amsterdam, Netherlands, you’ll travel ~1200-1300 kilometers depending on the route. The lenght and width of Texas are both in the neighbourhood of ~1,250 km.

Now, Arizona is another southern US state with an area of 295,254 km^2 and a population of 6,4 million people. The Netherlands’ population is estimated at 16.85 million. If you combine the populations of Netherlands (16,85), Denmark (5,5) and Belgium (11 mill), those 33 million people are distributed over an area of ~115.000 km^2. The (smaller) combined populations of Texas (25,1) and Arizona (6,4) have roughly a million square kilometers to deal with.

Does it make better sense to compare Texas with France? And those small countries with, say, the state of New York? It probably would. But it’s really hard to find good matches here, in particular due to the problem with population density differences. If you do find areas that match on this metric, odds are they don’t exactly match on other key metrics. The population density of the United States as a whole is 33,7/km^2. If you scale that up by a factor of ten, you get to the third most densely populated state, Massachusetts (324.1 /km^2). The population density of Massachusetts is somewhat lower than both Belgium’s (354.7/km^2) and Netherlands’ (403/km^2). The population density of Germany (229/km^2) is comparable to that of Maryland (229.7/km^2), which is in the US top five – Germany is almost 7 times as densely populated as ‘the US as a whole’. The population density of Great Britain is 277/km^2, comparable to Connecticut’s (285.0/km^2) – the state of Connecticut is btw. #4 on the US list. Italy is at 201.2/km^2, between Delaware and Maryland – it would be on the top 6 if it was a US state. Americans like to use the expression ‘France and Germany’, but at least in terms of population density, there’s a huge difference between these two countries that I’m not sure they’re aware of: The population density of France is much lower (116/km^2) than that of Germany, and rather more comparable to that of Spain (93/km^2). All US states outside the top ten have population densities well below 100/km^2, so note that even though Spain and France are relatively sparcely populated in a Western European context, France would be well within the top 10 and Spain just outside top 10 if the two countries were US states. The average population density of the entire European Union, including a lot of Eastern European countries most Americans couldn’t find on a map, is about the same as that of France, 116.2/km^2; 3.5 times as high as the US average.

The population density of Iceland is 3.1/km^2. As mentioned, the US average is 33.7/km^2 and Belgium’s density is 354.7/km^2. Remember these magnitudes. And yes, I know that the US population density is not homogenous and that a lot of it is almost empty. The population density of Europe isn’t homogenous either – to take an example, approximately one eighth of the German population – 10 million people – live in the very small Rhine-Ruhr metropolitan region (7,110 square kilometers, or less than 2% of the area). A fifth (12+ mill) of the French population live in the Paris metropolitan area. On the other hand, the population density of Norway, which even though she is a bit of an outlier is still very much a part of Western Europe, is 12,5/km^2, comparable on that metric to, say, Nevada (9.02/km^2) in the US.

If you look at differences in the US internally, when it comes to the 10 most densely populated states the one that is situated the most to the west of these is Ohio (the state border of which is still within 500 km of the Atlantic Ocean). Here’s a map:

Remember here that these numbers are people/sq mile, so to compare the numbers there with the rest of the numbers in this post you need to divide by ~2,6 or so. I found this comparable map of Europe convenient both because it gives density limits in sq. miles and because it’s a lot more fine grained than just data on the national level:

Last of all: Languages! Here’s the European map:

Let’s just say that a map of the US would look different. Yeah, a lot has been written about the Spanish/English-thing going on in the US. Well, intranational language barriers and -linguistic diversity aren’t exactly unknown phenomena in Europe either, despite the small size of the countries involved. A thing worth remembering here is also that in many of the bilingual regions of Europe highlighted here, English is the third language. If you’re a US tourist visiting some European bilingual region and you’re annoyed people don’t speak much English, ask yourself how many areas of the US you can think of where people can hold conversations in, say, English, Spanish and French.

Update: To the many visitors who followed Razib Khan’s link or the brownpundits link and have never seen this blog before – welcome! If you liked the post, take a look around – I’ve been blogging for 5+ years and it’s not unlikely that I’ve written other stuff that might be of interest. For instance, did you know that 90 percent of the human population lives on the Northern Hemisphere? I didn’t, before I wrote this.

November 17, 2011 Posted by | Data, Demographics, Geography, language, Wikipedia | 6 Comments

Wikipedia articles of interest

1. False friends. Not what you think. One of the examples from the article:

“In Swedish, Norwegian and Danish, gift means “poison” but also “married”.”

2. Hernán Cortés.

3. Coriolis effect. If you click the link, do note the number of links to articles on physical oceanography at the bottom of that post. Wikipedia is amazing.

4. Topographic prominence.

“In topography, prominence, also known as autonomous height, relative height, shoulder drop (in North America), or prime factor (in Europe), is a concept used in the categorization of hills and mountains, also known as peaks. It is a measure of the independent stature of a summit…”

5. Citric acid cycle. Here’s the not-quite-so-short-version (click to view in a higher res):

September 20, 2010 Posted by | Biology, Geography, Geology, History, language, Wikipedia | Leave a comment