12 October 2018

The Scream’s Clouds

Welcome to Warren’s Notice. On occasion, I’ve ventured into the world of art, where I have no background (among other blog posts Authenticating Artwork Computationally and Authenticating Artwork Addendum). A recent study of the painting The Scream by the Norwegian artist Edvard Munch (1863–1944) has me venturing again.

Edvard Munch’s The Scream
(1893), The National Gallery,
Oslo, Norway.
You’re probably familiar with the painting or at least the character portrayed, whether from reproductions, horror movies or Halloween costumes. But the study by researchers from the UK’s Oxford and London universities and Rutgers University focused on the sky, not the character.

Munch’s graphical depiction may be the earliest visual documentation of a type of cloud largely unknown to atmospheric science at the time.

The Scream
The dates of artwork can be important when trying to identify possible sources of inspiration. Unfortunately, Munch is known to have been indifferent about dating his work, in addition to producing many versions of the same painting.

There are four known versions of The Scream in paint and pastel. The National Gallery in Oslo, Norway, holds a painted version, dated 1893; the Munch Museum in Oslo holds a pastel version, dated 1893, as well as a painted version, undated but thought to be 1910; and a second pastel version, dated 1895, was sold for nearly $120 million in 2012. Munch also produced a lithograph version in 1895.

A glance at the painting suggests the character is screaming, yet the character was attempting to smother the sound according to Munch’s diary entry in 1892 and his later description of the image: “…the sun was setting, and the clouds turning blood red. I sensed a scream passing through nature; it seemed to me that I heard the scream. I painted this picture, painted the clouds as actual blood. The color shrieked…”

Possible Sources of Inspiration
Presuming that Munch’s painting captured the sky as he actually saw it, the researchers judge the event to have been either an abnormal or particularly striking sunset, a sunset affected by a volcanic eruption or some other meteorological phenomenon.

The volcanic sunsets caused by the August 1883 eruption of Krakatau in what is now Indonesia is often posited as the cause of Munch’s blood-red clouds. Munch’s whereabouts and the dates of Krakatau-affected sunsets over northern Europe narrow his possible observation to the winter months of 1883.

An alternative explanation, which the researchers favor over volcanic sunsets, was put forth in a 2017 study by a meteorological consultant from Norway and researchers from the University of Oslo and Norwegian Meteorological Institute. That study attributed Munch’s observation to nacreous clouds.
 

Photographs of nacreous clouds taken on 20 Jan 2008 from Leirsund, southern Norway, at times: (top left) 1508:56, (top right) 1532:47, (middle left) 1533:17, (middle right) 1534:20, (bottom left) 1546:35, and (bottom right) 1548:11 UTC. (photos by F. Prata from journals.ametsoc.org/doi/10.1175/BAMS-D-17-0144.1)
Nacreous clouds are seldom seen, filmy sheets, unbelievably bright with vivid and slowly shifting iridescent colors, curling and uncurling in the winter polar stratosphere at altitudes of 15,000–25,000 meters (49,000–82,000 feet). They are best seen within two hours after sunset or before dawn.

In Support of Nacreous Clouds
For the recent study, the researchers determined from the literature that nacreous clouds are sometimes observed during cold winter months in southern Norway. The clouds produce very dramatic skies, being most noticeable when the sun sets and clouds redden to what could be described as blood red.

They also established that the direction and location of the scene depicted in The Scream are compatible with the direction and location for nacreous cloud observations.

Going further, the researchers performed detailed analyses of the colors and patterns, comparing the sky and clouds in the painting to photographs of volcanic sunsets and nacreous clouds.
 

Comparison of sky in (a) 1910 and (b) 1893 versions of The Scream with photographs of (c) nacreous clouds and (d) a volcanic sunset. (from journals.ametsoc.org/doi/10.1175/BAMS-D-17-0144.1)
The waviness in the sky in The Scream is absent in the volcanic sunsets, while a uniform progression from red to deep blue seen in volcanic sunsets is absent from the painting. In contrast, The Scream’s alternating patterns of colors and eye-like structure are evident in the nacreous cloud photographs.

Wrap Up
Although The Scream might have been inspired by a particularly striking sunset, a volcanic sunset or simply by Munch’s mental state, the sky depicted in the painting is remarkably similar to that of nacreous clouds.

Reiterating, if Munch did observe then paint his sky with nacreous clouds, The Scream would likely be their first graphical depiction. This would be relevant to atmospheric scientists, particularly to those interested in the historical aspects of the development of cloud science. Thanks for stopping by.

P.S.
Study of the sky in The Scream in Bulletin of the American Meteorological Society: journals.ametsoc.org/doi/10.1175/BAMS-D-17-0144.1
Article on the study on ScienceDaily website: www.sciencedaily.com/releases/2018/07/180723142808.htm
2017 study of The Scream in Royal Meteorological Society’s Weather journal: rmets.onlinelibrary.wiley.com/doi/abs/10.1002/wea.2786
Nacreous clouds (type II polar stratospheric clouds):
www.atoptics.co.uk/highsky/nacr1.htm
weather.com/news/news/ozone-chlorofluorocarbons-cfc-nacreous-clouds-polar-vortex-stratosphere-reaction
en.wikipedia.org/wiki/Polar_stratospheric_cloud
The Scream:
www.edvardmunch.org/link.jsp
en.wikipedia.org/wiki/The_Scream
mymodernmet.com/edvard-munch-the-scream-painting/

05 October 2018

Waiting for Income

Save your money. (Barney Large
Coin Piggy Bank from
www.amazon.co.uk)
Welcome to Warren’s Notice. Today’s question is Why do some people make more money? If I may get personal, what factors had the greatest effect on your earnings? Go ahead, fill in the blanks.

Researchers from Temple University did. Along with the expected results, such as education and occupation, they found one interesting surprise: delay discounting ranked high as a predictor of future income.

What’s Delay Discounting?
If you had to choose between receiving $1 today or $2 tomorrow, would you take the $1? Those who take the smaller reward today rather than wait for the larger reward tomorrow are discounting the value of the future reward. Delay discounting refers to how much a person devalues future rewards compared to present rewards.

The classic studies of delayed gratification--the marshmallow experiment--were conducted at Stanford University in the late 1960s and early 1970s. Children were offered one reward (e.g., a marshmallow) immediately or two rewards if they waited about 15 minutes while the person administering the test left the room. Get this: Follow-up studies found children who waited longer tended to have better life outcomes.

Factors Related to Future Income
To improve upon earlier investigations of income attainment, the Temple researchers tested a large, diverse population: 2,564 racially and ethnically heterogeneous, male and female participants, 25 to 65 years in age, pre-high school to PhD in education, $10,000 to $235,000 in annual income and from over 1,700 zip codes.

In addition, they employed a novel analytic approach, using three machine-learning algorithms to model the relationship between income and key factors identified in earlier research--age, gender, ethnicity, height, race, zip code, education, occupation and delay discounting behavior.

Measuring Delay Discounting
Test participants were initially asked to choose between $500 immediately versus $1,000 at five different delays (1 day, 1 week, 1 month, 6 months, 1 year). If they chose the immediate reward, the next question offered an immediate reward midway between the prior immediate reward and zero. If they chose the delayed reward, the next question offered an immediate reward midway between the prior immediate reward and $1,000.

This narrowing pattern continued until participants’ choices converged on the dollar amount subjectively equivalent to the discounted delayed reward if the value were offered immediately. Lower dollar amounts indicated increased devaluation of delayed rewards in favor of immediate rewards.

Study Findings
Modeling with the three machine-learning algorithms, the researchers found that individual differences in income were explained by factors that could be ranked in a consistent manner.


Average ranking of factors according to how well they
predicted salary by three machine-learning algorithms.

(from www.frontiersin.org/articles/10.3389/fpsyg.2018.01545/full)
Occupation and education were paramount with each algorithm, and on average, zip code and gender were the next most important factors. The fifth most important factor was delay discounting, which was more predictive than ethnicity, height age and race.

One study shortcoming is that representation of African Americans and Hispanics in the sample population was only about half that in the U.S. population at large.

Wrap Up
As to why individual differences in discounting of future rewards predicts income attainment, the researchers speculate that it may be a consequence of the correlation between higher discounting and undesirable life choices.

Difficulties delaying gratification may also be affected by episodic future thinking, i.e., the ability to project oneself into the future to pre-experience an event. If people can vividly imagine themselves in the future with the larger rewards, they are more likely to be patient.

So, relax. As you’ve likely heard, all things come to those who wait. Thanks for stopping by.

P.S.
Study of delay discounting for income attainment in Frontiers in Psychology journal: www.frontiersin.org/articles/10.3389/fpsyg.2018.01545/full
Articles on study on ScienceDaily and ScienceAlert websites: www.sciencedaily.com/releases/2018/09/180903101741.htm
www.sciencealert.com/your-ability-delay-instant-gratification-predict-money-earn-delay-discounting-marshmallow-test
Marshmallow experiment: en.wikipedia.org/wiki/Stanford_marshmallow_experiment
Update study of children’s delay of gratification in Developmental Psychology journal: psycnet.apa.org/record/2018-29923-001?doi=1

19 September 2018

Vaccination Tweet Meddling

Welcome to Warren’s Notice. Every now and then, there’s an interesting study I’d like to review for this blog, but because mainstream media has covered the study extensively, I set it aside. On rare occasion, I revisit that decision and risk having you set the blog aside…like today.

Most Americans believe vaccinations are safe and effective, though you might get the impression from social media that the topic’s up for debate. Collaborating researchers from George Washington, Maryland and Johns Hopkins universities studied the Twitter discourse about vaccinations with two aims: (1) assess the impact of bots and trolls and (2) analyze the content of Russian troll activity.


Twitter bot tweets Twitter user.
(multiple websites)
To be sure we’re together, I’ll note that an internet bot (from “robot”) is a software application that performs automated tasks. A Twitter bot may autonomously tweet, re-tweet or direct message other Twitter accounts, promoting content. 

Internet trolls are people who misrepresent their identities with the intention of promoting discord with offensive, divisive or controversial comments.

A disguised internet troll uses
Twitter.
(from www.genbeta.com)


Testing Bot and Troll Vaccine-Related Tweets
The researchers reviewed nearly 1,800,000 tweets sent between July 2014 and September 2017 to quantify the effect of known and suspected Twitter bots and trolls.

To test if Twitter bots and trolls tweet about vaccines more frequently than do average Twitter users and if those tweets are more likely to be pro-vaccine, anti-vaccine or neutral, the researchers compared tweets sampled from known bot and troll accounts against tweets selected randomly.

Going further with the comparisons, they applied a machine-learning classifier (Botometer) to a random subset of vaccine-related tweets, scoring the likelihood that the tweet’s author was a bot from 0% to 100%.

In the course of their analysis, the researchers encountered vaccine-related tweets from accounts that NBC News had identified as Russian troll accounts. They examined 253 of those tweets to capture the major themes.

Impact of Bots and Trolls
The researchers collected 899 vaccine-related tweets to represent the activity of known bots and trolls and 9,895 vaccine-related tweets to represent the activity of assorted Twitter users. Scoring the latter found 5% were likely authored by humans, 3% by bots and 76% were of uncertain provenance; for various reasons, 16% could not be scored (e.g., accounts deleted).

The known bots and trolls were more likely to tweet about vaccination than did average Twitter users, but overall, the messages were no more polarized. In contrast, the accounts scored as being of uncertain provenance and those that could not be scored posted tweets that were significantly more polarized and anti-vaccine. (Similarly, content polluters--malicious accounts identified as promoting commercial content and malware--posted significantly more anti-vaccine content.)

The Russian troll tweets exhibited the same strategy as the social-media influence campaign waged during the U.S. election--promote discord by playing both sides. Of the 253 tweets, 43% were pro-vaccine, 38% anti-vaccine and 19% neutral, with messages and conspiracy theories often tied to U.S. politics and government (e.g., At first our government creates diseases then it creates vaccines…).


Example vaccine-related tweets from Russian
troll account identified by NBC News.

(from ajph.aphapublications.org/doi/10.2105/AJPH.2018.304567)
Wrap Up
Whether their tweets are pro- or anti-vaccine, Twitter bots and trolls have a significant presence in online communication about vaccinations. Unfortunately, the vaccine-related tweets may be from malicious actors with a range of hidden agendas. The Russian troll messages, for example, were clearly designed to sow society discord and erode public trust in vaccinations.

I hope you agree it was worth my reviewing this well-reported study. Thanks for stopping by.

P.S.
Study of Twitter bot and troll effect on vaccine discourse in American Journal of Public Health: ajph.aphapublications.org/doi/10.2105/AJPH.2018.304567
Example articles on study:
www.sciencedaily.com/releases/2018/08/180823171035.htm
www.cnn.com/2018/08/23/health/russia-trolls-vaccine-debate-study/index.html
www.washingtonpost.com/science/2018/08/23/russian-trolls-twitter-bots-exploit-vaccine-controversy/
www.theguardian.com/society/2018/aug/23/russian-trolls-spread-vaccine-misinformation-on-twitter
Bots and Trolls:
www.techopedia.com/definition/24063/internet-bot
en.wikipedia.org/wiki/Twitter_bot
www.techopedia.com/definition/429/troll

14 September 2018

Smile at Goats

Welcome to Warren’s Notice. Today’s blog post reviews a recent study that found goats prefer people with happy faces. That this will be the fourth time I’ve blogged about goats may come as a surprise to more than myself.

The first post probably doesn’t really count. It was only a parenthetical comment about a goat with a penchant for hanging out in a cattle trough (Roosters’ Crowing).


Fainting goat from 2006 video
by jimmywan87

(www.youtube.com/watch?v=we9_CdNPuJg)
The second had its origins at the Saturday morning coffee klatch, when one of the regulars told Vicki about goats that fainted. She relayed that to me, which, of course, led to a full-blown blog post about domestic goats, goat intelligence, goats and humans, and, yes, fainting goats (Looking at Goats).


Goats in argan tree, Morocco.
(multiple websites)
I figured that was it. And it was until I saw a study of how goats disperse seeds of the argan tree, which includes climbing the tree to reach fruit that hasn’t fallen (Goats in Trees).

Permit me to continue my never-ending saga of goats.

The Goat Experiment
This latest study was conducted by international collaborators led by researchers at Queen Mary University of London. They carried out their experiment in a temporary enclosure within the goats’ regular daytime range. Results were based on 20 goats that completed all training and test trials (8 females, 12 castrated males, ages 3 to 19 years, various breeds).

The trials involved presenting the goats two greyscale photographs of human faces of the same unfamiliar female or male; one face had a positive, happy expression, the other a negative, angry expression. The two photographs, placed 90 cm (about 3 ft) apart, were printed on white A3 paper, mounted on a square metal mesh at a height of about 60 cm (about 2 ft).

Training Trials
Training was designed to motivate the goats to approach the side of the enclosure that would display the photographs.

For training trials, the photographs were hidden. One experimenter stood between them, looking at the ground with a neutral facial expression, holding a food reward in each hand.

Another experimenter stood 5 m (16.4 ft) away with a goat on a leash, looking with a neutral expression away from the first experimenter. Once released, the goat had 30 seconds to get the food reward or be dropped from testing. The goat was subjected to three trials before every testing session.  

 
Set up for training trials, showing enclosure, experimenter E1 between locations where photographs will be displayed, and goat released by second experimenter E2.
(Graphic from rsos.royalsocietypublishing.org/content/5/8/180491)
Testing Trials
Immediately after training, the goat was returned to the starting point, while the first experimenter revealed the two photographs and exited the enclosure. The second experimenter then turned and released the goat toward the photographs. The goat was free to move around and interact with the two photographs.  
Goat being released in test trial to interact with photographs of angry and happy faces.
(Photo from video accompanying rsos.royalsocietypublishing.org/content/5/8/180491)
They tested each goat in four sessions, two weeks apart. Each session consisted of three training trials and one test trial.

For each test trial, half of the goats saw male faces, half saw female faces, half saw the positive face on their left side first, half saw it on their right side first--all in random order within and between goats.

The researchers videotaped all trials and analyzed all aspects of the goats’ behavior using a Simple Video Coder.

Wrap Up

The 20 goats that completed all trials preferred to approach happy faces first regardless of the gender of either the human faces or the goats.

In addition, the goats interacted first, more often and longer with happy faces when the faces were presented on the right side versus the left. This suggests a right-brain hemisphere dominance for processing negative emotions and a left-hemisphere dominance for processing positive emotions, which has been hypothesized for mammals.

As I described in a recent blog post (Horses Don’t Forget), many animals can recognize human faces; dogs and horses can also recognize human facial expressions. This study of goats provides evidence that the domestication histories of dogs and horses is not required for being able to distinguish human emotions based on facial cues. Is it true of other animals?

Thanks for stopping by.

P.S.
Goat study in online journal Royal Society Open Science: rsos.royalsocietypublishing.org/content/5/8/180491
Article on study in ScienceDaily website: www.sciencedaily.com/releases/2018/08/180828204901.htm