Google Trends: Gorman v. Gaga

I noticed something interesting about Americans’ Google search trends recently. These two Google search trends cover the last seven days.

For those who are out of touch, Amanda Gorman is the Youth Poet Laureate for America and recited a poem at Biden’s inaugural. She is black. Lady Gaga is a white singer and certainly better known than Gorman prior to January 20th. As for the second map, it seems almost reversed from the electoral map, with blue states colored red and vice versa, although of course there are exceptions. It seems Democrat-dominated states are more concerned with the insurrection while the Republican ones are more concerned with Trump’s impeachment.

Molly: The True Story of the Amazing Dog Who Rescues Cats by Colin Butcher

Molly: The True Story of the Amazing Dog Who Rescues CatsMolly: The True Story of the Amazing Dog Who Rescues Cats by Colin Butcher
My rating: 4 of 5 stars

Molly is a mischievous and adorable cocker spaniel trained to be a scent detection dog, specifically, to search for cats. Her owner, the author, runs a private detection business but specializes in finding missing pets. He bills himself as a pet detective. This book tells the story of how Molly was discovered, trained and her many adventures and misadventures finding pets. I can’t say the book is very well written. The editor needed a sharper blue pencil. It is crammed with treacle and puffery, but ultimately, its merit falls on the heart-warming stories of frantic owners being reunited with missing pets. No, not all the stories have a happy ending. I was most impressed with the amount of work that went into acquiring and training Molly and Butcher and the degree of difficulty required in many of these lost pet cases. Experience and knowledge of cat and human behavior were essential in many of the cases. Molly and Butcher are located in England, and there is a lot of British slang and local knowledge, such as London geography and familiarity with British TV shows, which can be charming to some, but at times is a challenge for the American reader. I think any dog or cat lover would enjoy the book if you can overlook a few stylistic peccadilloes.

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Don’t blame Trump; blame his voters

Let me clarify: Donald Trump is responsible for the insurrection in the Capitol and should be held criminally and civilly liable. In that sense he should be blamed. But he’s like a rabid dog. He can’t control himself. The ones to blame are the people who voted for him. They knew what he was and unleashed the rabid dog on the public.

Let’s examine what voters knew about Trump. Before he even ran for office he started the fake Birther movement even though he knew full well President Obama was born in the U.S. The details are well spelled-out in Michael Cohen’s book Disloyal, so I won’t do so here. In short, Trump is and was a white supremacist who couldn’t stand the idea of a black president. It was also clear that he was willing to lie to challenge the legitimacy of a fair and honest election. He was also so stupid (and so were his followers) that he/they thought it would make a legal difference if Obama was born in Africa. It wouldn’t. He was a natural born citizen since his mother was. Then Trump ran for president and his main slogan in referring to Mexicans was (exact quote): “They’re bringing in drugs. They’re bringing in crime. They’re rapists…” He also ranted about the Chinese, but not the Russians who were the more dangerous enemy (and also white). So voters knew already that he hated black, brown, and Asian people. A typical white supremacist.

Next he bragged about being able to shoot someone on Fifth Ave. and be able to get away with it. Shortly after that he said maybe the 2nd Amendment people would take care of Hillary. So he made clear that he was willing to use deadly force against his enemies, and in fact tried to get his opponent assassinated. This, too, is confirmed in Cohen’s book; just read the first page. It was no joke. He was emulating the New York mob bosses he admired. Don’t order a hit; just let your minions know what you’d like to see happen. That’s to avoid criminal prosecution. Just expect them to follow up. That technique goes back as far as King Henry’s  line “Will no one rid me of this turbulent priest,” thus sealing Thomas Becket’s fate, not that Trump is likely to know who Becket was.

Then came the Access Hollywood tape where Trump confessed to being a serial sex offender. He said he that liked to grab women he met by their “p****”.  Later he claimed this was “locker room talk” and “only words,” but multiple women have confirmed that it happened. Cohen describes at least one such incident that he had to take care of as Trump’s fixer. His close aide Omarosa has also confirmed Trump’s sexual predation in her book.

So even before the 2016 election voters knew he was a violent, white supremacist and sexual predator who tried to incite people to kill an elected government official and to hate and fear people of color. He wasn’t elected despite that; he was elected because of that.

Since he’s taken office he has called the Nazis of Charlottesville “very fine people” and called Haiti and Africa “sh**hole countries.” The only thing linking those two countries is that black people come out of them, so that certainly shows what he thinks black people are. I didn’t hear him say this myself, but both Adam Schiff and Kevin McCarthy have confirmed that he did and neither Trump nor any of the Republicans in the room have denied it, so I think it’s safe to believe. Cohen also says that Trump used to say things like that all the time in private.

Next came the child separation at the border. I didn’t believe it could be as bad as the news said at first, but I watched the documentary Immigration Nation on Netflix, a film made by White House approved documentary makers embedded with ICE and Border Patrol. The filmmakers were never heard on the film. All the dialogue was the ICE officials, immigrants , and people directly involved telling their own views in their own words. Two officials confirmed that they were ordered by the White House not only to separate the immigrant children from their parents but also to torture them so as to deter future immigrants. The word torture wasn’t used. The one official said the instruction was to “cause maximum pain,” but that’s a pretty good definition of torture. The separation from the parents was by itself torture to a young child, but they did a lot more than that, keeping the kids in open cages in 100 degree heat without adequate water or shade, telling them they would never be returned to their parents, that they would be sent to foster homes and never be loved or part of a family again. Despite a court ordering the return of the children to their parents, his administration is still holding over 500. I have two Mexican grandchildren I’ve never seen in person, only in photos and video. If Trump were to have been re-elected, it’s likely they couldn’t come to see me without risking being taken from their parents, tortured, and never returned. So in addition to everything else, voters knew he is a child torturer.

Then he ramped up the violence. When the Black Lives Matter demonstrations started, he encouraged his followers to believe the demonstrators were violent. To be sure, some looters and vandals were in the crowd. But the only killers were the Boogaloo boys hiding in the crowd who shot three officers: two federal officers in Oakland and one Santa Cruz policeman. Two of  them died. One shooting took place on the steps of the Oakland federal building, a place I worked on a few occasions. That could have been me on those steps if I was still in the FBI. The killers were caught and confessed that they did the shootings to support Donald Trump. They were trying to fulfill the false narrative Trump was spouting, hoping the public would fear the peaceful protesters rather than the real killers: Trump supporters.

There’s so much more I could cite: the draft dodging, hiring someone to take his SAT, the “anti-terrorist” bill he signed January 31 last year banning immigration from six nations whose people were all people of color (who’d never had a terrorist act against the U.S.), the bankruptcies, the pardons of criminal cronies, the phony investigation of Hillary, ad infinitum. He also made clear throughout his presidency that he would never admit he lost an election and that he would never agree to a peaceful transition of power. So his voters knew in 2020 that he was a serial sex offender who tried to get an opponent assassinated, encouraged cop killers, tortured children, and would use violence to keep from leaving office. Millions of people voted for him anyway, or, more likely, because this is what they wanted. Hillary Clinton grossly underestimated when she said half his followers were deplorables. Double that. And people pretended to be surprised when he incited the mob to attack the Capitol when he lost the election. Don’t buy it. His voters expected it, wanted it, and still want it.

I will never see a Trump voter and see anything other than someone who thinks my grandchildren are drug smugglers and rapists and wants them tortured. You will never be my friend.

 

Cryptic clues explained

First, understand the conventional rules that govern cryptic crossword clues. Every clue must contain a true definition or equivalent of the word or phrase in the puzzle grid, and that must be either at the beginning or the end, not the middle. However, that definition may be obscure and will usually be given in a misleading way by the rest of the clue. The remaining parts of the clue also provide a valid definition of or clue to the word, but in a non-standard way, such as by an anagram, by breaking the word into parts, etc. With some exceptions for readability, every word in the clue should be pointing to something to help you solve the grid word. See the examples below to understand how this works. These are the answers and explanations to the puzzle in the previous post. The format is Answer (i.e. word in grid); Clue given; explanation of the clue.

Across

9. ADELPHI; Hip deal unraveled private New York University. Adelphi University is a private school in New York, so the last four words are the real definition. Hip deal is an anagram of adelphi. Unraveled is what is known as an indicator or anagrind. It signifies that what comes before or after is an anagram. Any word that suggests a mixing or incorrect spelling, such as wacky, strained, etc.,  can indicate an anagram.

10. LULLABY; Bull lay carelessly, heard soothing music. Bull lay is the anagram, carelessly the indicator, soothing music is the real definition. Heard is an extra word this time to pull the rest together.

11. IFOLLOW; Got it! Oil flow is interrupted. Got it! is the definition, i.e. a synonymous phrase. Oil flow is another anagram with the last two words the anagrind. Note that the word lengths (1,6) are shown in the clue when it’s more than one word. I’ve followed that rule in this puzzle, but it’s not always followed by others. Some publishers show it even if it’s one word, others, never.

12. NATASHA; Russian woman has a tan, unexpectedly. Russian woman is the definition, has a tan the anagram, unexpectedly is the anagrind. Now let’s move on to different clue types.

13. COPYRIGHT; Replicate just to get form of protection. Replicate = copy; just = right. Put them together to get a form of protection, the definition of copyright. Defining the individual parts in this way is very common in cryptics, often splitting a word into smaller groups, not at natural breakpoints like here.

15. ECOLI; Severe colic: it could make one very sick. The last six words provide the true definition. The word itself appears hidden in the phrase severe colic. This is another common cluing technique, and using lots of irrelevant words as camouflage is considered legitimate. I chose to treat ecoli as one word since that has become common usage.

16. FRIABLE; Crumbly snack can be cooked in oil, it sounds like. Crumbly is the definition. The phrase “it sounds like” is another type of indicator. It means the adjoining word or phrase is a homonym of the real word, or in this case sounds like it should mean capable of being fried – i.e. fryable, although there may not be such a word. Look for indicators like “they say” or “I heard”. The word snack is irrelevant, there to connect the parts sensibly.

19. NAIVETE; Savvy Kenai veteran eschewed credulity. Credulity is the definition. The word appears in Kenai veteran.

20. ADDLE; Sidesaddle designed to confuse. Addle appears in the word sidesaddle and to confuse is the definition.

21. ALONGSIDE; Beside the hypotenuse. Beside is the definition while the hypotenuse is a legitimate definition of “a long side,” an alternate reading of the letters.

25. TRUNNEL; Passage through mountain takes right, Peg. A trunnel is a wooden dowel or peg used in construction, so Peg is the definition. Passage through mountain defines tunnel, “takes” is an indicator that one thing is contained in another. Here the word right represents the letter R, which often signifies right as opposed to left. Using one word to stand for a single letter in this way is also quite common in cryptics. Look for other indicators of containment like swallows, protecting, surrounds, enters, etc.

26. TAFFETA; Heavy returned cheesecloth; Heavy = fat. Returned is an indicator to read in reverse, i.e. TAF. Other indicators of this type are words like back, reversal, or in the case of vertical words, up, skyward, etc. Feta is a cheese. Here the legitimate definition, cloth, is connected to part of the alternate definition for additional misdirection, but it is there at the end, so it is fair.

28. POLECAT; Staff kitty is a real stinker. Since a polecat is another word for skunk, real stinker is the definition. Staff = pole; kitty=cat.

29. PIEBALD; Multi-colored pizza with no topping. Multi-colored is the definition. Pizza=pie; with no topping = bald.

Down

1. MANIAC; A crazy man I accept. A crazy man is the definition. Maniac appears in the clue. Note that the word man appears both in the real definition and in the alternate one.

2. RECOUP; Obscure couple regain what was lost. Recoup appears. Final four words define.

3. OPAL; I hear German car is a real gem. I hear is a homonym indicator (of Opel, a German car), the rest defines opal.

4. BIGWIG; Dolly Parton? This type of clue is called a double definition. Dolly is indeed a bigwig in music/show business. A big wig is also one of her defining characteristics. Reportedly, when asked how long it takes to do her hair, she replies “I don’t know. I’m not there when it happens.”

5. PLANKTON; Exercise heavyweight protozoa. Plank = an exercise; ton = a heavy weight; protozoa is the definition.

6. BLITHERING; Carefree call to be kind of idiot. Blithe = carefree; ring = call. A blithering idiot is one kind we’ve all heard of. This is probably my favorite clue in this puzzle.

7. GASSTOVE; Vast egos cooked only on a kitchen appliance. Vast egos is the anagram; cooked is the anagrind. The rest defines. Note the two word lengths are indicated with the clue.

8. DYNAMITE; Boomer made tiny composite. Boomer = definition (it does go boom, you know). Made tiny = anagram; composite = anagrind.

14. RUBBERNECK; Observe masseuse kiss and cuddle. Observe = definition; masseuse = rubber (one who rubs); kiss and cuddle = neck.

16. FLATTOPS; Haircuts popular in 50’s aircraft carriers. Double definition. Flattops were a popular style for boys in the 50’s and aircraft carriers are also called flattops.

17. INDOUBLE; Adjust one; build twice as much. Adjust = anagrind. One build = anagram. Twice as much = definition.

18. EPAULETS; Driving sleet overwhelming most of apostle wearing ornamental shoulder pieces. Driving is the anagram of sleet which “overwhelms” Pau_, most of apostle Paul. Shoulder pieces = definition. This clue has two indicators: one for the anagram and one to indicate a word inside another. Using the L in both sleet and Paul is generally considered unfair. Each letter or group of letters in the alternate definition should be separately treated.

22. OCTOPI; I coopt spineless creatures. I coopt = anagram. Spineless creatures = definition. The word spineless may double as an anagrind, or perhaps the clue doesn’t have one. They are usually, but not always, provided. Some puzzle makers don’t use them at all.

23. IPECAC; Ripe cactus can be used as a purgative. Ipecac is contained in clue. Purgative = definition.

24. ELANDS; Horny Africans slander recklessly without initial regret. Elands are African antelope with large horns, so the first two words are the definition. Slander is the anagram (with an extra R); recklessly = anagrind. Without initial regret is the indicator to remove the initial letter of the word regret from the anagram. You will also see indicators like “last of” or “center of”.

Cryptic Crosswords Explained … again

I’m a big fan of wordplay. I work the cryptic crosswords in The Guardian nearly every night. I know that many people, especially Americans, are mystified by them, so I thought I’d provide you with one of my own making and give a full explanation for each clue. Every word/clue combination is a little wordplay puzzle to be solved. I’ve posted on this topic before, but I’ve never given a complete explanation of every clue. I’m going to do the explanation in my next post, which I’ll post at the same time, so you don’t have to wait. For now, if you just want to solve it first, click on the puzzle below to take you to the interactive online puzzle. There’s a link there to the PDF version, too, if you want to work it on paper.

Another Cryptic

Click the right arrow below to see the answers and explanations of the clues.

The Guest List by Lucy Foley

The Guest ListThe Guest List by Lucy Foley
My rating: 5 of 5 stars

If there’s such a thing as the perfect whodunit, this is it. I absolutely loved this one. It’s got everything: suspense to the very end, deliciously complex characters with mysterious motives, a lavish and exotic setting, and terrific writing. The setting is an island “wedding venue” off the coast of Ireland where a handsome movie star groom is about to marry a gorgeous posh publisher/website  owner bride. It begins with an investigation underway, something about a “body” only it’s not clear if a murder has taken place or even a dead body found. Perhaps someone only reported seeing a body or someone went missing.

Then the back stories begin. We learn the groom and most of his ushers are all “Trevellians,” having attended the same prep school, one of those bully-filled Lord of the Flies type places. The rather dim best man did too, but he was there on a rugby scholarship and wasn’t “one of the boys,” being too rough and from a poor background. The bride and her sister have a strained relationship. The sister seems to have a screw loose and is a cutter. The bride demands everything be perfect and is more than a little demanding. Something bad happened at the stag party but we don’t know what. The wedding planner, an attractive woman who runs the venue, seems mismatched to her fat husband but is the soul of efficiency. There’s way too much drinking, some dangerous peat bogs, a raging storm, crumbling cliffs. What could possibly go wrong?

The stories are told by all the characters in turn and we learn that not all is right beneath all the lavish perfection. We begin to learn who the likely candidates are for victim and who has motives against each. The author skillfully manages to keep from us whether anyone died, and, if so, who it might be until almost the very end. The responsible party or parties for whatever happened is revealed only at the absolute end, and it caught me by surprise. The suspense was delicious.

This belongs to that genre of mystery that is not quite a locked-room mystery since the crime doesn’t seem impossible, and it’s not a pure whodunit where we follow along with an investigator. It resembles the classic game Clue where a body is found and the suspects are all together in a closed location like, for example, Murder on the Orient Express, but without the Poirot equivalent. The characters/suspects/victim tell the story themselves. I listened to the audiobook and the actors were just marvelous.

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The Running Key Cipher

The Running Key Cipher is very simple in concept, but very difficult to decipher. It is not a genuine cipher since it cannot be deciphered uniquely. Rather, it should be thought of as a puzzle. However, it has a real cryptographic use, because the ability to decipher a Running Key cipher is what allowed American counter-intelligence people to decrypt Soviet messages during the Cold War (see the Venona Project).

To create a Running Key Cipher, take your message (plaintext) and break it in half. Add an extra letter if necessary if there’s an odd number of letters. Use the first half as a key to encipher the second half in a Vigenere cipher. The resulting ciphertext will always be half the length of the original plaintext. Here’s an example:

THISORGANIZATIONANDITSSYSTEMSPLI
TTHEAMERICANGRAPHOLOGYWORLDINTWO
MAPWODKRVKZNZZOCHBOWZQOMJEHUFIHW

The top row is the key (and first half of the plaintext) and the second row the rest of the plaintext. The third row is the ciphertext. Now try to decipher that ciphertext without knowing any of the text. I’ve written a program that uses brute force to decipher all possible combinations of key and plaintext for the first eight letters (MAPWODKR) to see what makes sense. Here are some of the pairs of valid decryptions that resulted.

THESAMER TTLEORGA, HANDAMON FACTORWE, THESOLID TTLEASCO, THISISCO TTHEGLID.

All of these pairs, and many others, are valid looking possible sentence beginnings and midsections. It takes skill and judgment to pick out the correct decryption. Note how any given letter or word, even if valid, can be either part of the key or the other half. This is why Running Key cipher problems in the American Cryptogram Association are usually presented only with generous cribs. If you want to try your hand at a few to hone your skills or just pass the time, I’ve provided a few for you below. They can be fun diversions.

ULLWLPXCZQWLQHXVHIGSZBEQUPD (crib: succeeding)

FWBTAFOIKDMCHBS (crib: swill)

FWYJIFWDECKGIXMVBXNOSAMS (crib: theproof)

Afterland by Lauren Beukes

AfterlandAfterland by Lauren Beukes
My rating: 3 of 5 stars

Nicole (Cole) and her 13-year-old son Miles are South Africans stranded in the USA due to an apocalyptic pandemic three years earlier. The disease killed off almost all the males, so Miles, apparently immune, is a rare and precious commodity under government protection. All Cole wants is to get back home. They break out and begin a journey to the East Coast with Miles disguised as a girl. Meanwhile, her devious sister Billie wants to sell Miles or at least his sperm, for the big bucks. She teams up with some thugettes to chase them cross-country.

The author’s style is charitably described as irreverent, but more accurately as in-your-face. She writes almost as though challenging the reader, like we are unwelcome eavesdroppers. The 90-page plot is stretched into 400 pages of irrelevant anecdotal digressions suspiciously resembling filler. The dialogue is peppered with gratuitous cursing, always a sign of a lazy author. The plot is wholly illogical but the book is all about style, not substance.  Some will find the author’s prose amusingly sardonic. Me, not so much, but she is at least imaginative. The basic concept is a new twist on the post-apocalyptic genre.

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Review of YouTube TV

We recently cut the cord with our cable provider (AT&T U-verse) and signed up with YouTube TV (YTTV) – one of Google’s streaming TV options. YouTube TV costs about half of what U-Verse does in our area. That’s its biggest advantage. So what are the pros and cons?

Pros:

Without question, the biggest advantage is cost. If you already have wi-fi, there is only the subscription cost, which may be half of the cable or satellite subscription cost. It has all the major broadcast network channels – Fox, ABC, CBS, ABC, PBS – and all the major cable ones, too – ESPN, CNN, Hallmark etc. The lineup of channels can change, so check what’s currently being offered if you have a favorite cable channel.

The main screen shows three options: Home, Library, and Live in the center top. You will start with the Home option highlighted and you move to your choices with your remote. In the far upper right is an hourglass to search. The search function works well. I found I rarely need it. Library consists of your recorded shows. Select the Library button on the screen and then down the left side is a menu display. You can choose New in Your Library, scheduled, most watched, “shows”, and sports among the top options. The screen shots to the right of each option show you the shows available there. Once you select one, say New In your Library you move to the right, look at all recordings ordered from most recent on the left and choose one. It will show you screen shots of all the recordings (up to thirty days worth, I think) of that program. Recordings you’ve already watched are labeled as such. All are labeled with recorded time (e.g. “6 hours ago”). I find this a bit different, but no more cumbersome than choosing on U-verse. If the show is still being recorded, you are given the option of starting from the beginning or joining live. If you’ve paused a show or turned off the TV and come back to it, when you select it again, the icon on the selection screen will have a red line at the bottom to show how far in you’ve already watched, and it will start in the same place you left off.

It has a nice feature for sports coverage. For NFL and college football games it gives you the option of watching key plays either as a quick highlights reel after the game is over, or as we sometimes use it, to catch up to live action. For example, we usually record a game and only start watching it a half hour or hour after it has begun. That’s usually so we can fast forward through the time outs, ads, etc. If a game gets too one-sided or dull for any reason, or if we just don’t have time to watch an entire game, we can select the watch key plays to catch up to live time and then watch the end of the game in live time. I don’t know if it has this feature for other sports. Another really nice sports feature is that you can just name a team you follow and it will record all broadcasts, regardless of channel. You no longer have to look up the schedules and channels. This is true for all pro sports, I think, and for Division I college football at least. I don’t know if this feature is available for non-sports, like following a favorite actor or singer.

For the Live option, the menu set up is similar, with a list of channels on the left and on each line a display of screen shots as to what’s playing now and in the next few time slots. It’s pretty straightforward, although a bit more cumbersome to choose than on cable where you just press channel up/down or enter the channel number on the remote.

The picture quality is generally excellent. There are occasional pixellated strips that go across the screen fleetingly. This used to happen with cable and with both our current and previous TV, so I suspect the problem is with the network feed or our wi-fi provider (U-verse), not YouTube TV.

Cons:

Probably the biggest negative is that you may need a new TV. Our old Samsung smart TV was one generation too early and couldn’t run it. We bought a new Samsung television just to be able to make the switch. We figure we’ll earn the cost back through savings in less than a year and have a bigger, newer television to boot. Be sure to check with YTTV’s website for the model you want to use. Another irritation is that there is a lot more buffering of the signal than on cable. I don’t think it’s a router speed problem because U-verse used the same router, although I suppose AT&T may give preferential bandwidth to their own service over Google’s. More likely, the problem is on Google’s end. I find the picture freezes while buffering sometimes, too, and won’t unfreeze unless I press rewind or fast forward. This can be irritating and interrupts the flow of a program. It seems to happen more with recorded live shows, especially ones where we’re catching up to live time.

The most noticeable shortcoming for me is the way it fast forwards or reverses. Unlike cable where you can see a more or less continuous stream of speeded up video as you scroll forward or back, with YTTV you get only still screen shots every fifteen seconds of recording. At times you only get a black screen, so you can’t tell whether you’ve reached the point you are seeking. On the plus side, though, the timing is precise per click so that I’ve learned how many clicks it takes to get to the right point for most ad breaks and between football plays. It’s often faster than cable scrolling for some shows, but overall it’s easier scrolling on cable.

Accessing closed captioning is slower and clunkier than with cable. On my old cable remote a single button would turn closed captions on or off. With YTTV you have to push buttons at least four times, assuming you remember the correct sequence. The exact sequence depends on the app, i.e. YTTV, Netflix, Prime, or your television manufacturer or sometimes whether the show is dubbed or pre-captioned by the producer. It’s slower starting up YTTV, at least on the model of TV I have. Samsung does not ship with the YTTV app installed, at least my model didn’t have it. I had to go to the app store (it’s an Android based system) and download the free app. Samsung installed it along with a whole row of other pre-loaded apps, e.g. Netflix, Prime, Hulu, etc. along the bottom of the home screen. The only problem is that it’s not visible unless you scroll all the way to the right. Samsung does not allow you to delete any of those other apps, even though you don’t use or want them, nor can you shift positions of the icons around. So every time I turn on the TV I have to wait several seconds for the boot up process, then scroll all the way to the right, past a dozen or so icons, until I get to YouTube TV at the far right end, then select it. This is not exactly Google’s fault, although I’d bet that if they paid Samsung what Netflix and Hulu do, they could get a better spot on the home screen and have it pre-installed.

Another feature some people might or might not like is that YTTV features alternate services to the one you prefer. For example, we normally watch NBC Nightly News through our local NBC station. We have that on regular record and YTTV does record it just fine. But when you go to recorded shows and select that choice, it displays first NBC News Now, which is a streaming service, not the regular over-the-air broadcast signal. That is a prepackaged set of stories recorded in an earlier edition of the news using only the national feed. I can still choose the local station one icon off to the right, but it seems to me that should be the first choice. The advantage of the local one is that it’s more current by an hour or three since I’m on the west coast and the News Now service is mostly taken from the east coast version of the news. Also, if there is a breaking local story important enough, the local station version will have broken into the national feed only on the local station feed, not the pre-recorded News Now. Similarly the PBS station feed on YTTV is from a station hundreds of miles away instead of the local one. However, I think the News Now or similar news streaming services have fewer ads, although I can’t guarantee that and you may or may not be able to fast forward through them. Some ad breaks even on Amazon Prime shows are now non-skippable, but it may happen on YTTV network shows.

In short, navigation in general is more cumbersome than with cable and you are dependent on being able to retrieve streaming content quickly from the cloud instead of your local DVR. None of these drawbacks has made me regret the choice to switch, but there is a learning curve.

 

Vaccine interest across the U.S.

If you have been following the Covid-19 news, you know that the Pfizer vaccine has been approved by the FDA and is being administered in the U.S. right now. You probably also know that the Moderna vaccine has been submitted to the FDA and is expected to be approved within the week. The vaccines are similar according to reports, but the big difference is that the Pfizer one requires super-cold freezers to store the vaccine and dry ice packing to preserve it during shipping or for storage. The Moderna one can use conventional freezers and trucks.

This led me to take a look at which of these vaccines is of most interest to the public. Here are two charts taken from Google Trends. The top one shows the searches between the two company names over the last year. The bottom one shows where people are searching for dry ice over the last thirty days.

Bear in mind that the top one takes in a long period when it was uncertain which company’s vaccine would become the first to market. Once Pfizer was approved first, both in the U.K. and the U.S., searches for Pfizer greatly outnumbered Moderna, so the top one would be all blue for almost any shorter time frame. It will be interesting to see if that changes in a week or two. I find it interesting that for the most part it was the more populated states that had more interest in Moderna. I have no explanation for that, nor for the fact Wyoming joins them.

The bottom chart makes more sense to me. The dark blue states are where the interest was greatest on a relative basis. The greatest interest seems to be in more rural states with low population density. I expect those states have few of the special freezers needed for the Pfizer vaccine and have greater need for dry ice to store and transport it. Hospitals and nursing homes in those states are probably scrambling to see where they can obtain sufficient dry ice. This trend, too, could change once the Moderna vaccine is approved and begins shipping.

Grace Is Gone by Emily Elgar

Grace Is GoneGrace Is Gone by Emily Elgar
My rating: 3 of 5 stars

The setting is a small Cornwall village. Cara goes to her friend Grace’s house to find the severely disabled teenage girl missing and her mother killed. The chief suspect is Grace’s father, Simon, who is mentally unstable and estranged from the family. Cara is determined to find Grace. She is aided by Jon, a journalist who took Simon’s side in an article years earlier about the family tragedy and has suffered the calumny of the town and the press for it. Jon, tritely, is also having marital troubles and neglects his parental duties as he delves deeper into the case.

It seemed like a good setup, but I can barely squeeze out three stars for it. None of the characters are likeable and the writing is pedestrian at best. The police seem to be doing almost nothing while Jon and Cara more or less stumble about and somehow figure out what’s going on but without any real sleuthing. Grace’s diary plays a big role, yet the police totally miss it in their crime scene search. Entries from it appear normally at first, i.e., one of the characters reads the page and they are printed so we can see them, but later entries from the diary just appear amid chapters without explanation and apparently without the characters becoming aware of the content. I found this clumsy and confusing.

There is a “big reveal” about two-thirds of the way through the book, but the author telegraphed it so heavily beforehand that it would be hard to be surprised. I was planning a two-star review until the very end when the author partially redeemed herself. She added a twist that made the story both more credible and  somewhat more nuanced.

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The Whitest and Blackest Names in America

I was looking at United States Census data again recently and noticed some interesting ways of examining or analyzing it. You can download this data yourself direct from the Census Bureau here: Surnames occurring 100 or more times in the 2010 Census. The 2020 data won’t be out for quite some time. I sorted it by race (self-identified) and here are the surnames that had the highest percentage white and at least 10,000 individuals. All were 96.99% white or higher.
STOLTZFUS
BYLER
HERSHBERGER
TROYER
YODER
BURKHOLDER
HOSTETLER
GRABER
MAST
ROUSH

The dominance of German- and Jewish-sounding names on this list continued for several hundred more entries. Now for the blackest names by percentage, again with a cutoff of at least 10,000 individuals:
WASHINGTON
BANKS
JOSEPH
JACKSON
WILLIAMS
ROBINSON
COLEMAN
HARRIS
SIMS
DIXON

These percentages range roughly from 39% to 87% black. Presumably both these lists are formed largely by the history of slavery, with colonial slaveholders giving their slaves their own surnames, or possibly in some case, freed slaves taking the surname of a well-known white person. If I restricted the list only to the 1,000 most common names, some Irish names like O’Connell appeared in the whitest list, but most were still Germanic. Germans and European Jews tended to arrive in the U.S. in large numbers only after slavery ended and generally settled in free states or territories.

You can also use the data to find out how common your surname is and that of your mother’s and grandmother’s maiden names.

Parsing plaintext concluded

One more post on the problem of dividing plaintext and then I’ll leave the topic. I decided to try two more ways to divide up text into words. The first method was a total failure: hillclimbing. That consisted of randomly choosing dividing points and then testing to see how many valid words there were between the spaces, followed by a series of trying one or two random changes, checking to see if more words were produced, and either keeping the new spots or going back to the previous set. I won’t discuss the details, but take my word for it: it bombed.

The other method is to start at the beginning and reduce the string down until you have a word left at the beginning. For example, if the text you are parsing is “mydogatemylunch’, the program first checks the whole string to see if it’s a word. Since it isn’t, it crops the last letter, tests again, and so on until it has left only “my” which is a valid word. It saves that, then it starts with the next letter, d in this case, and does the same thing until all the letters are used or, if no word is found, the letter is saved as a “word”, but skipped over.

Simply put, the method I described in the previous two posts is to start with valid words from one of more lists and checking to see if they are in the subject text. This new method is to take sections of the subject text and see if they are valid words. Neither method is perfect. After testing numerous trial texts, it is clear to me that the previous version (Method A) is better than this new one (B). There are some texts where B performs better, some where they’re equally good or bad, but most cases have A outperforming B. Here are some examples.

Both A and B got this perfect: oneostricheggwillfeedtwentyfourpeopleforbreakfastthejoyofcooking

A got this one perfect: slowandsteadywinstherace. B’s result: slow ands tea d y wins the race. (“ands” is a valid word as in “no ifs, ands, or buts”).

Both got this wrong, but differently: wedrinkallwecantherestwesell
A: we drink all we c anther est we sell. B: we drink all we cant heres t we sell

Lastly, one where B outperformed A:  asinthesongfreebirdcouldyou
A: a sin the …   B: As in the …

This exercise has given me a new appreciation for those pros who write autocorrect software. Of course they use AI and have massive data troves to mine, while I used just a few dozen test sentences. One good thing about trying this new method is that I learned how to determine whether a string is a valid word much more quickly than before. In the past I was just taking a file of words and sequentially checking to see if each matched my test string. That’s reasonably fast if the word is early in the list, but not otherwise. I was using lists ordered by frequency so that the most-used words would be found fast, but it still involved a lot of unnecessary test matches. For this new method I discovered a search method that is probably old hat to programmers, but new to me. Basically you start in the middle of an alphabetized word list, compare strings, and if the test string is less than the list word, you do the same with the first half of the list, otherwise with the second half, and continue to cut the search space in half, and repeat until you match or can’t shrink any farther.
 

Parsing undivided plaintext

In my last post I gave a few examples of my attempts at writing a program to divide up undivided text into words. Since then, I’ve been working on the program. It’s doing better. Here are examples from that post and how the program divides them now.

what is christmas it is tenderness for the past courage for the present hope for the future.

they were indeed a queer looking party that assembled on the bank the birds with draggle d feathers the animals with their fur clinging close to them and all dripping wet cross and uncomfortable

Not perfect, but much better. So how did I approach this task? I’m not going to provide code, just discuss my thinking process. I decided to start with long words first since it is relatively rare for long words to accidentally appear, that is by juxtaposition with smaller words. The opposite is clearly not true. Small words appear in longer words all the time. Separating out small words like to and in first would break up almost every sentence incorrectly.

I used a word list to go through the text and inserted spaces before and after every found word starting with length 24. Whenever it found a word, it would effectively blank out that stretch so it could not be used in searching for words farther down the list. I also used word lists that were ordered by frequency so that it found the words most likely to appear before obscure words took up that space. In my first iteration, that’s about all I did and the examples I gave in my last post show the limitations of such an approach.

My next step was to identify common errors that this approach produced, such as “I twill” instead of “it will.” Twill is a five-letter word, so it’s found before the more common word will, and that leaves only the letter i. That breaking looks fine to the program since I and twill are both valid words. I created a list of such examples, mostly involving very small words such as “ha snot= has not”, “o four = of our” and so forth. The program checks that list after its initial parsing and fixes anything occurring there. Creating that list was a time-consuming process and is still ongoing. The only way to do it is to test many examples using the program and judge by eye. It’s not always easy. For example, is “a man” better than “am an”? Should it be changed or not? I use Google Ngram as guidance for such hard cases. I call this my “fixit” list.

This improved things, but many errors still appeared. Most common were those where the “S form” of a word (i.e. the plural of a noun or third person singular of a verb)  was found when the correct form is without the final S. I wrote a routine to find and try to correct such case. One class that was easy to find was words with a final S. I went through the separated text pair by pair. Whenever word 1 ended with an S, I tested the frequency of that word followed by word 2, then removed the S from the first word and tacked it onto word 2 and tested the frequency of that pair. Which ever scored best, I saved. The data for such word pair frequencies can again be obtained from Google Ngram. This doesn’t always work. For example “westernsquare” initially breaks into “westerns qua re,” all valid words. Swapping the S to the qua yields “western squa” not square, so the parsing does not change. “Collisionsport” breaks up as “collisions port” without this step, but the program successfully changes it to “collision sport.”

Lastly, I did the same thing for every low-scoring pair, but with an additional test. I set an arbitrary limit, X, and tested every successive pair. If the frequency was below X, I tried shifting the last letter of the first word to the beginning of word 2 to compare, and I also shifted the first letter of word 2 to the end of word 1 and whichever of the original and two variations scored highest, I kept. The improvements have been subtle, but real. The downside is that it slows down parsing tremendously. Without this final word pair improvement step, the parsing is essentially instantaneous.  With it, a sentence often takes ten or fifteen seconds. I will continue to fiddle with the value of X. The higher I put it, the more word pairs get tested and the longer the program takes. I have to weigh speed versus accuracy.

I’ll continue to add common errors to the fixit list, and to add missing words to my lists, including proper nouns, but longer lists add time. I also found it necessary to remove some words, like “doth.” It’s a valid word, but rarely used today and it causes parsing errors with “do -the -they -those,” etc.

Programming utilities humor(?)

To fill the time during these pandemic times, I’ve been conjuring up small programming projects. The latest is something useful to me in my cryptanalysis hobby – a program that splits up undivided text into words. The ciphers that I solve are all standard types for the American Cryptogram Association, and most of them, when solved, produce plaintext that is run together without spaces or punctuation. For the sake of readability, it is handy to break up that text. I threw together a program, but I’d call it just a first draft. It’s more than enough for my purposes, but I may try to refine it just for the fun of it. It definitely breaks in the wrong places from time to time. I thought I’d share some of these examples with you for whatever entertainment value they may have.

i see a frightful mystery involved in all this it i snot the crossbeam it i snot t hero om what do you suspect the innkeeper the most honest ma ninth e world and belonging toon e oft he oldest families inn ur ember g

what is christmas it is tenderness forth e past courage forth e present hope forth e future wonderful

bald maestro conducted richly chromatic harmony of a gust a v ma hler symphony for vast crowd who went wild shouting bravo

adults are kids who owe money i work forty hours a week to bet hi spoor

stratosphere is the only major casino o nth e strip located within las ve gas city limits all others a rein the unincorporated townships of winches te rand paradise

time is the single most used no u ninth e english language and yet there is a venerable strain of intellectual history that proclaims timed oe snot exist

they were indeed a queer looking party that assembled o nth e bank the birds with draggle d feathers the animals with their fur clinging closet o thema nd all dripping wet cross and uncomfortable

you cants hoo tamale in the taillike a quail for a man maybe hot but hes not when hes shot so true

an unmanned satellite called solar max was launched from c a pecan aver alto study the physics of solar flares for more than a year

It seems clear the program has problems with small words, especially “is” and “not”, as well as words not in the word lists I use, especially proper nouns.

The Prague Sonata by Bradford Morrow

The Prague SonataThe Prague Sonata by Bradford Morrow
My rating: 4 of 5 stars

An old musical manuscript, a piano sonata, falls into the hands of Meta, a young woman musicologist, but it’s incomplete. She sets about to unite the piece she has with its other parts. She travels to Prague where she meets characters both benign and less so. This novel blends mystery, arts, and romance with music and music history. The story arc is all too predictable, but it’s a satisfying, entertaining read. My biggest complaint is that there’s way too much music history and music scholarship for the average reader. I find the raptures of ecstasy the characters fall into over the score a bit over-the-top, too, but maybe classical music mega-fans really do get that excited. The author skillfully weaves in an aura of impending disaster to add suspense for those of us who crave a bit more oomph to a story.

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Ultimato Cliff Knowles Mystery #11

For those of you who are desperate for more reading during these upcoming self-isolation months, here is something to read: the latest Cliff Knowles mystery.

Hardkorps is a video blogger, memorializing his three-year quest for the Ultimato Challenge geocache on his vlog. Success means big money and big fame. But not all is as it seems. A shocking surprise leads to a death and an FBI investigation. When Cliff Knowles comes to believe his wife Ellen, the FBI agent on the case, is helping to prosecute the wrong man, he steps in. Cliff and Ellen find themselves working on opposite sides of the case. Only their mutual knowledge of geocaching can lead to discovering the truth.

Amazon Kindle link: Ultimato

I will have a free copy available on my Cliff Knowles Mysteries website in the next few days. For now only the Kindle version is available. The paperback book is being processed by Amazon and should also be available in a few days.

The Movie Lover’s Tour of Texas by Veva Vonler

The Movie Lover's Tour of Texas: Reel-Life Rambles Through the Lone Star StateThe Movie Lover’s Tour of Texas: Reel-Life Rambles Through the Lone Star State by Veva Vonler
My rating: 5 of 5 stars

This charming book, written by a university lecturer on writing and confessed movie devotee, combines literary panache with homespun folksiness. The book is divided into seven sections, each devoted to one region of Texas. In each are descriptions and reviews of specific movies, focusing on the sites and features that are real-life Texas. It’s a combination travelogue/movie review book. If you’re planning a driving trip through some part of Texas, this book would be an excellent companion. In addition to pointing out movie locations, it identifies local points of interest and the best places to eat and stay, especially in some of the small towns.

You aren’t going to want to read this book straight through. The content in each section is much the same, although on different movies and towns. If you’re a fan of old westerns, this book could serve as a source for finding a gem you overlooked. Maybe you can find it on Netflix or your local library. The indexes in the back are helpful. There’s one on movie titles and another on location names.

Full disclosure: the author is my son-in-law’s mother.

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New stuff

It’s been two weeks since I posted, so I suppose I should post something. The election and Biden’s victory have certainly changed the national dialog. I hope things return to normal, or as normal as possible in the middle of a pandemic. Maybe now my grandchildren won’t have to worry about being thrown into cages and tortured if they try to cross the border, although that’s closed to non-essential travel right now.

We just bought a new stove. The cooktop is induction, so we have to get rid of all our non-magnetic cookware, such as the copper-bottom pans. We also got a new television. It’s only slightly larger than the old one, but it’s a newer generation and can run YouTube TV, which we signed up for. U-verse was getting ridiculously expensive. These are new things requiring getting used to.

The End of October by Lawrence Wright

The End of OctoberThe End of October by Lawrence Wright
My rating: 4 of 5 stars

This mid-apocalyptic sci-fi novel is remarkably prescient about a global pandemic. The one in the book is more severe than COVID-19, but the idiocies of the U.S. and other governments is amazingly like what has come to pass in real life. This book is yet more proof that the current pandemic was foreseeable and its effects largely preventable. Although this book was published in April 2020, just after the start of the COVID pandemic, it was clearly written many months or years before, yet the course is so accurately described you would think it was ripped right from today’s headlines. Many will put a political spin on the book, but I think the author wasn’t trying to be partisan or even political, beyond a general warning that we should be well-prepared for a pandemic.

The book is an entertaining read for those of us who enjoy science fiction, but it would actually be more fun if it didn’t adhere so closely to what comes across on the evening news. It can give you the willies to think about it. The author writes well and the plot holds together. I do think it was overly long, but that’s a minor fault.

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