#$0.44

[mtg-cards-hourly]

Scavenging Ooze

In nature, not a single bone or scrap of flesh goes to waste.

Artist: Austin Hsu TCG Player Link Scryfall Link EDHREC Link

#mtg #magic the gathering #tcg #$0.44 #austin hsu #scavenging ooze #commander 2011 #creature #ooze

[trans-cuchulainn]

love that neither hr nor my manager nor i actually know what my goddamn salary is

#am i 0.43 or 0.44. nobody fucking knows. what's full time anyway. #what point in the salary scale am i. are we counting the august 1st increase in our calculations yet. what the hap is fuckening. in general #househunting while away from all your paperwork is like. NOT FUCKING GREAT #i would also not recommend househunting with multiple jobs where the majority of your income is self-employment #because oh boy the referencing system does NOT like that #they will not let me upload contracts / proof of future earnings #only past earnings. and my past earnings are not high enough to rent this house #WHICH IS WHY I WAS NOT PREVIOUSLY RENTING THIS HOUSE #BUT NOW THEY ARE GOING UP I CAN AFFORD THE HOUSE #THAT'S HOW THESE THINGS WORK #i'm going to kill someone #personal

[astrometrych]

Astronomy #Space #Espace #Astrometry

#Planet : Mars Day of the year : Day 3 Year progress : 0.44% [_________________________________________________]

[anonymouscapybara]

people say the worst SI unit is the mole. "ohhh but it's just a number it doesn't even have anything attached it doesn't deserve to be an official unit" BZZZ WRONG

the worst unit is the candela. the candela is stupid.

what's the candela, you ask? well, it measures the brightness of light

"oh that sounds reasonable" you say, "just measure the energy or power emitted!" nope. they would not do anything nearly so simple. a lightbulb emitting a watt of yellow light is more candelas than a lightbulb emitting a watt of red light.

"ok that's weird" you say, "but maybe they're adjusting for that somehow? maybe it measures number of photons?" again, that would be far too reasonable. a lightbulb emitting a fixed rate of yellow-light photons is more candelas than the same rate of purple-light photons.

but what are they even measuring then? what else is there to measure? clearly they ran out of ideas while making up units, because what they're actually measuring is the SUBJECTIVE BRIGHTNESS OF LIGHT TO THE HUMAN EYE. the candela is STUPID

a reasonable question to ask is: how would you even measure the brightness of light to the human eye? aren't a lot of human eyes different? don't different things look bright in different circumstances? aren't there colorblind people in the world?

surely the General Conference on Weights and Measures, which spent millions precisely calibrating magnetic quantum flux to avoid basing the kilogram on a random block in France, has a clever solution!

no. no they don't. the candela is stupid.

as far as I can tell, what you do is you first measure how much light of each wavelength comes in. Then you multiply each measurement by a "luminosity function", which measures brightness to the human eye:

you will notice that there are multiple functions shown in this diagram. the SI system has five of these, for different lighting conditions. do your lighting conditions not exactly follow one of the Five Official Standardized Lighting Conditions? guess you're out of luck then.

and whose eye are we using? why, the Official Standardized CIE Photometric Observer, of course: the "ideal observer having a relative spectral responsivity that conforms to a CIE-defined spectral luminous efficiency function for human vision"

(and no I can't show you this function because the fine people of the ISO put it BEHIND A PAYWALL. who puts measurements determining a fundamental SI unit BEHIND A PAYWALL. the candela is stupid)

all right, so we're measuring a fundamental unit using a (nonexistent) idealized observer in one of five random lighting conditions. how did they find the values for this? i'm...not entirely sure. but here's a glimpse, based on a few of the most recent studies I found used for this:

"...heterochromatic (minimum) flicker photometric data obtained from 40 observers (35 males, 5 females) of known genotype..."

"To obtain an estimate of the mean L-cone fundamental, we weighted [weird variables] according to the ratio of 0.56 L(S180) to 0.44 L(A180) found in the normal, male Caucasian population...and averaged them together"

that's right, our Official Objective Brightness Unit is probably sexist and racist. none of the other SI units have a chance to be sexist and racist. a meter is a meter in every country on Earth. 6.022*10^23 For Women is still 6.022*10^23. but the candela is-- probably-- the white man's candela, because you can absolutely bet that genetic drift around the world gives different values for this stuff.

in summary: my opinion, as you might have guessed, is that the candela is stupid. hopefully you agree with me after reading this that we need to completely eradicate it from the planet. failing that could we at not give it the same level of officialness as the meter or the kilogram?

#physics #math #rant #units #candelas #stupid stupid candelas #science

[carsthatnevermadeitetc]

Peugeot VERA 01, 1981. The first of a series of Vehicule Econome de Recherche Appliquee concepts designed to maximise economy. The VERA 01 was based on the Peugeot 305 but has aerodynamic modifications that reduced the car's  0.44 CD down to 0.32. It was fitted with an experimental 1306cc 62hp 4 cylinder turbodiesel engine and was capable of travelling 91.2 miles on a gallon of fuel.

#Peugeot #Peugeot VERA 01 #experimental car #research vehicle #prototype #turbodiesel #1981 #aerodynamic #Peugeot 305 #VERA

[watashinooinarisannisawaranaide]

なんで欧米に必ずと言っていいほどスラムがあるか考えてみるといい 超貧困を少数押し付けるのが欧米、少数だけ極端に低いから貧困率は高くなりにくい 日本は逆で割と保護や還元が低所得者向けになっとるし健康保険とか最たる例 ジニ係数も税還元考慮無しだと0.44と高い方から10番以内だが、税還元考慮有りだと0.34と先進国最下位級 平均年収の10倍以上の人口比なんて日本は欧米の1/2以下しかないし 平均年収と中央値の差も92%とG20で最小なんよ、欧州85～75%、アメリカ67%だからな。 ただし日本のシステムはみんなで均等に貧困を負担して押し付けないから、貧困率が上がってしまう 日本も弱者切り捨ててスラム化させてしまえば貧困率改善するぜ？やっちゃならん事だとは思うが

アメリカの低所得者「貧乏過ぎて電気代も家賃も払えない、食料購入にも苦労している」米国でも広がる格差 | FX2ちゃんねる｜投資系まとめ

[uncharismatic-fauna]

Going Batty for the Little Brown Bat

The little brown bat (Myotis lucifugus) is a species of mouse-eared bat that lives throughout North America, from northern Canada to the southern United States. They are most commonly found in deciduous forests, but they also roost in man-made structures or caves; anywhere warm and dark.

M. lucifugus is aptly named, as it’s a relatively small bat. At most, individuals weigh 12.5 g (0.44 oz) and have a wingspan of 27 cm (10.6 in). Females are typically larger than males. The color of their fur can range from tan or red to dark brown, though the fur on their stomachs is lighter than the rest of their body. In addition to their large ears, which gives them a great hearing boost, the little brown bat has exceptional eyesight and is sensitive to ultraviolet light. However, they lack a Jacobson’s organ, which in other animals is used to detect moisture-borne odor particles.

Like other bats, the little brown bat is primarily nocturnal, emerging at dusk and feeding intermittently throughout the night. Individuals emit about 20 calls per second while in flight, and use the corresponding information to avoid obstacles and detect prey. They feed exclusively on insects, including mosquitoes, beetles, and flies, and in a single night an individual may consume over 2/3 of its body weight in food. Because their source of food is generally seasonal, little brown bats are only active in the warmer months of the year. When the temperature drops to 0 °C (32 °F), individuals will enter a state of torpor, in which their heart rate may drop as slow as 8 beats per minute.

Mating takes place in the fall, just before the hibernation season. Males and females gather together in large groups to roost, in a behavior known as swarming. During this period, colonies average around 9,000 individuals; the largest recorded had over 180,000. Both sexes mate with multiple partners, and homosexual pairings are relatively common. This behavior continue throughout the hibernation period, and individuals will pair indiscriminately with active and torpid bats. Once mated, female bats store their sperm for the following spring; they then carry their pregnancies for 50-60 days. Each female gives birth to only one pup, which weighs about 30% of her body weight.

Pups grow rapidly, opening their eyes and ears within a few hours of being born and becoming completely weaned at 26 days old. After this, young transition to feeding solely on insects, though they may receive help from their mothers while learning the best techniques for catching prey. Females are sexually mature at only one year old, and males mature at two years old. Once they reach maturity individuals will leave to form their own roosting groups. In the wild, a little brown bat can live up to 34 years; however, many bats are predated upon by owls during the active season, and by raccoons while hibernating.

Conservation status: The IUCN has rated M. lucifugus as Endangered. Their primary threat is a fungus-caused disease known as white-nose syndrome; this disease is particularly harmful to the little brown bat due to their large congregations during the mating and hibernation period.

If you like what I do, consider leaving a tip or buying me a ko-fi!

Photos

Jason Corbett

Joseph Johnson

Rick Reynolds

#little brown bat #Chiroptera #Vespertilionidae #mouse-eared bats #microbats #bats #mammals #deciduous forests #deciduous forest mammals #urban fauna #urban mammals #caves #cave mammals #North America #queer animals #queer fauna

[gemville]

Ring by Yael Designs In 18k White and Yellow Gold Featuring A 5.02 Carat Green Tourmaline and 0.44 CTW Diamonds

Photo Courtesy: Yael Designs

Source: jckonline.com

#yael #yael designs #green tourmaline #diamonds #18k white gold #18k yellow gold ring #green tourmaline and diamond ring #high jewelry ring #contemporary high jewelry #fine jewelry #luxury jewelry #fine jewellery pieces #gemville

[mtg-cards-hourly]

Pestilence Demon

"I have schemed too long to be supplanted by dead gods. If I cannot have this world, no one can."

Artist: Justin Sweet TCG Player Link Scryfall Link EDHREC Link

#mtg #magic the gathering #tcg #$0.44 #justin sweet #pestilence demon #commander 2014 #creature #demon

[livingonthesands]

0.44.

[ <<prev ] [ first ] [ next>> ]

patreon - kofi

#tw: violence #poor handsome feller #fallout #fallout comic #fallout fanart #living on the sands #one heck of a party #fallout fancomic #fanfiction #vault life #vault tec #post apocalyptic #0

[zuko-always-lies]

ATLA Book 2 Character Stats

One thing I have been wondering for a while is how many lines of dialogue each character has in ATLA. I recently figured out an easy way to calculate it, so here are the stats for Book 2. You can find the stats for Book 1 here.

There are 3186 total lines of dialogue in the season. They are divided up as follows:

Sokka 499 lines, 15.66% Aang 492 lines, 15.44% Katara 412 lines, 12.93% Toph 242 lines, 7.60% Iroh 181 lines, 5.68% Zuko 169 lines, 5.30%(this increases to 194 and 6.08% if you include "Young Zuko") Azula 92 lines, 2.89% (this increases to 103 lines and 3.67% if you include "Young Azula") Jet 60 lines, 1.88% Long Feng 46 lines, 1.44% Kuei 40 lines, 1.26% Pathik 37 lines, 1.16% Chong 33 lines, 1.04% Suki 31 lines, 0.97% Joo Dee 29 lines, 0.91% Ty Lee 29 lines, 0.91%(This increases to 31 lines and 0.97% if you include "Young Ty Lee") Mai 28 lines, 0.88% (This increases to 29 lines and 0.91% if you include "Young Mai") Xin Fu 27 lines, 0.85% Zei 27 lines, 0.85%

With the more obscure characters below

Young Zuko 25 lines, 0.78% Fong 22 lines, 0.69% Young Azula 21 lines, 0.66% Yu 19 lines, 0.60% Ursa 18 lines, 0.56% Wan Shi Tong 18 lines, 0.56% Jin 17 lines, 0.53% Lee 17 lines, 0.53% Smellerbee 17 lines, 0.53% Tong 17 lines, 0.53% King Bumi 16 lines, 0.50% Lao 14 lines, 0.44% Guard 13 lines, 0.41% Tho 13 lines, 0.41% Due 12 lines, 0.38% Ghashiun 12 lines, 0.38% Ticket lady 12 lines, 0.38% Ying 11 lines, 0.35% Huu 10 lines, 0.31% Song 10 lines, 0.31% Yung 10, 0.313873195% Captain 9, 0.282485876% Dai Li agent 9, 0.282485876% General Sung 9, 0.282485876% Gow 9, 0.282485876% Oyaji 9, 0.282485876% Gansu 8, 0.251098556% Hakoda 8, 0.251098556% Kenji 8, 0.251098556% Shuzumu 8, 0.251098556% Fung 7, 0.219711237 General How 7, 0.219711237 Male student 7, 0.219711237 Pao 7, 0.219711237 Than 7, 0.219711237 The Boulder 7, 0.219711237 Trainer 7, 0.219711237 Mongke 6, 0.188323917 Quon 6, 0.188323917 Sela 6, 0.188323917 Tycho 6, 0.188323917 Ukano 6, 0.188323917 Fire Nation Man 5, 0.156936598 Lily 5, 0.156936598 Michi 5, 0.156936598 Moku 5, 0.156936598 Old man 5, 0.156936598 Ozai 5, 0.156936598 Roku 5, 0.156936598 Blue dragon 4, 0.125549278 Broadsword man 4, 0.125549278 Customer 4, 0.125549278 Earth Kingdom soldier 4, 0.125549278 Kyoshi 4, 0.125549278 Macmu-Ling 4, 0.125549278 Merchant 4, 0.125549278 Merchant #1 4, 0.125549278 Merchant #2 4, 0.125549278 Old Sweepy 4, 0.125549278 Pong 4, 0.125549278 Poppy 4, 0.125549278 Qin 4, 0.125549278 Scary prisoner 4, 0.125549278 Soldier 4, 0.125549278 Villager 4, 0.125549278 Azulon 3, 0.094161959 Fire Sage 3, 0.094161959 Florist 3 ,0.094161959 Guard one 3, 0.094161959 Ladies 3, 0.094161959 Male student #2 3, 0.094161959 Man 3, 0.094161959 Sha-Mo 3, 0.094161959 Ticket woman 3, 0.094161959 University student 3, 0.094161959 Unnamed Fire Nation boy 3, 0.094161959 Bato 2, 0.062774639 Brainwasher 2, 0.062774639 Cabbage merchant 2, 0.062774639 Captured agent 2, 0.062774639 Commander 2, 0.062774639 Girl with umbrella 2, 0.062774639 Guest 2, 0.062774639 Head of the Dai Li 2, 0.062774639 Huge round angry face 2, 0.062774639 Joo Dee replacement 2, 0.062774639 Joo Dees 2, 0.062774639 Koko 2, 0.062774639 Kyoshi Warrior #1 2, 0.062774639 Li 2, 0.062774639 Lo 2, 0.062774639 Oracle 2, 0.062774639 Pakku 2, 0.062774639 Pet store owner 2, 0.062774639 Sensitive ruffian 2, 0.062774639 Servant 2, 0.062774639 Song's mother 2, 0.062774639 Store owner 2, 0.062774639 Villager #2, 2 0.062774639 Villager #3, 2 0.062774639 Young Ty Lee 2 ,0.062774639 Adult guest 1, 0.03138732 Agent 1, 0.03138732 Audience 1 ,0.03138732 Boy's mother 1, 0.03138732 Earthbender guard 1, 0.03138732 Engineer 1, 0.03138732 Farmer 1, 0.03138732 Flyer distribution man 1, 0.03138732 Guard #2 1, 0.03138732 Guard two 1, 0.03138732 How 1, 0.03138732 Iio 1, 0.03138732 Katara (flashback) 1, 0.03138732 Kyoshi Warrior #2 1, 0.03138732 Lady on stage 1, 0.03138732 Lo and Li 1, 0.03138732 Longshot 1, 0.03138732 Lu Ten 1, 0.03138732 Man in the bar 1, 0.03138732 Old woman 1, 0.03138732 Older guest 1, 0.03138732 Palace woman 1, 0.03138732 Peasant girl 1, 0.03138732 Princess Yue 1, 0.03138732 Prisoner #2 1, 0.03138732 Red dragon 1, 0.03138732 Resistance fighter 1, 0.03138732 Resistance fighter #1 1, 0.03138732 Resistance fighter #2 1, 0.03138732 Royal messenger 1, 0.03138732 Sandbender #1 1, 0.03138732 Sandbender #2 1, 0.03138732 Second Engineer 1, 0.03138732 Shop owner 1, 0.03138732 Star 1, 0.03138732 Tea seller 1, 0.03138732 Team Avatar 1, 0.03138732 Terra Team leader 1, 0.03138732 Terra Team member 1, 0.03138732 The Hippo 1, 0.03138732 Third girl 1, 0.03138732 Train conductor 1, 0.03138732 Villagers 1, 0.03138732 Waiter 1, 0.03138732 Warrior 1, 0.03138732 Water Tribe warrior 1, 0.03138732 White Lotus member 1, 0.03138732 Young guest 1, 0.03138732 Young Mai 1, 0.03138732 Younger guest 1, 0.03138732

#ATLA #avatar the last airbender #ATLA stats #ATLA lines #ATLA stat #Avatar #Aang #Katara #Zuko #Sokka #Iroh #book 2: earth #Toph #Azula #Jet #Ty Lee #Suki #Mai #Long Feng

[destinationtoast]

Toastystats preview: F/F vs. M/M tagging

I discovered something unexpected while doing stats comparing F/F and M/M on AO3. One thing I was initially looking for was whether M/M fanworks were more likely than F/F fanworks to tag dark themes or explicit sex acts. It seemed like yes, they were -- but then I found out that, more generally, M/M fanworks use more tags on average than F/F fanworks. And given that, it's not too surprising that M/M is more likely to use most of the common AO3 tags than F/F is (whether the tag is dark, fluffy, or otherwise).

Still, I found a few AO3 tags that F/F was more likely to use than M/M. And I sorted a bunch of common AO3 tags from "Most likely to be used by M/M" to "Most likely to be used by F/F", shown above. The middle line indicates that a tag is equally likely to be used by M/M and F/F. Some of the darker and more explicit tags do indeed seem to be further toward the mostly-M/M end of the spectrum, but some of the ordering surprised me. (E.g., F/F is more likely to use "Smut," while M/M is more likely to use "Plot What Plot/Porn Without Plot." And F/F and M/M are nearly equally likely to use "Trauma" and "Coercion.")

I have a whole lot more F/F vs. M/M data to share soon, but I have questions for y'all first about this data:

does the above visualization makes sense? I'm worried it might be hard to interpret, so if you're confused, can you share anything about why?

are you are surprised by anything about the data?

any thoughts/theories/questions this data raises for you?

Below the cut -- additional explanations that might be useful when theorizing (e.g., about possible factors like background ships), along with raw data for the above graph.

A couple notes on interpretation: we shouldn't have to worry about the fact that F/F is often tagged when F/F is actually a background ship -- I tried to weed out all cases where the F/F or M/M tag of interest could possibly have referred to a background ship. Also, all of the above tags are used at least 1000 times on F/F works and at least 17K times on F/F and M/M combined... so these numbers shouldn't be *too* prone to the noise of really small numbers.

Data used to make the chart

Header: tag name | % F/F using tag | % M/M using tag | A/A is X times more likely to use tag as B/B (A/A uses it more than B/B)

Whump | 0.16% | 0.39% | 2.4

Protectiveness | 0.85% | 1.81% | 2.1

Hurt | 0.93% | 1.94% | 2.1

Kinks | 1.12% | 2.30% | 2.1

Crack | 0.87% | 1.67% | 1.9

Torture | 0.46% | 0.84% | 1.8

Children | 0.56% | 0.99% | 1.8

Gore | 0.23% | 0.40% | 1.7

Plot What Plot/Porn Without Plot | 2.25% | 3.72% | 1.7

Not Beta Read | 1.76% | 2.63% | 1.5

Falling in Love | 1.12% | 1.62% | 1.4

Self-Harm | 0.63% | 0.90% | 1.4

Abuse | 1.82% | 2.57% | 1.4

Incest | 0.93% | 1.31% | 1.4

Cuddling & Snuggling | 1.56% | 2.15% | 1.4

Humor | 3.63% | 4.99% | 1.4

Birthday | 0.38% | 0.51% | 1.4

Supernatural Elements | 2.16% | 2.93% | 1.4

Badass | 0.37% | 0.50% | 1.4

BDSM | 3.94% | 5.32% | 1.4

Awkwardness | 0.65% | 0.86% | 1.3

Dark | 0.44% | 0.58% | 1.3

Marriage | 1.78% | 2.36% | 1.3

Light-Hearted | 3.13% | 4.12% | 1.3

Hatred | 0.51% | 0.66% | 1.3

Mythical Beings & Creatures | 2.01% | 2.58% | 1.3

Love | 5.95% | 6.74% | 1.1

Friendship | 5.01% | 5.64% | 1.1

Alternate Universe | 19.27% | 21.27% | 1.1

Holidays | 1.90% | 2.09% | 1.1

Trauma | 1.43% | 1.56% | 1.1

Coercion | 0.37% | 0.39% | 1.1

Horror | 0.45% | 0.47% | 1.0

Comfort | 0.95% | 0.97% | 1.0

Fluff | 23.98% | 24.17% | 1.0

Flirting | 1.20% | 1.20% | 1.0

Hugs | 0.38% | 0.37% | 1.0

Crossovers & Fandom Fusions | 1.56% | 1.52% | 1.0

Alternate Canon | 4.89% | 4.71% | 1.0

Polyamory | 0.71% | 0.67% | 1.1

Smut | 7.04% | 6.48% | 1.1

Slow Burn | 2.54% | 2.26% | 1.1

Post-Canon | 2.32% | 2.03% | 1.1

Romance | 6.42% | 5.49% | 1.2

Drabble | 2.59% | 2.21% | 1.2

Prompt Fill | 0.70% | 0.59% | 1.2

Pre-Canon | 0.77% | 0.59% | 1.3

One Shot | 3.85% | 2.66% | 1.4

LGBTQ Themes | 7.77% | 4.44% | 1.7

Gender Related | 3.52% | 1.45% | 2.4

#fandom stats #femslash #wlw #mlm #F/F vs. M/M #ao3 #toastystats #questions for the tumblmind #op #50 #100

[everyscavever]

also scav 2281. this guy looks VERY distressed

SCAVENGER I.D #2281

Hex codes

Eyes: # ff6a4c #1f0d12 Head/hand: # 1f0d12 Body: # 210e0a Belly: #2f1611

Personality traits

Aggression: 0.01

Bravery: 0.02

Dominance: 0.26

Energy: 0.04

Nervousness: 0.52

Sympathy: 0.44

Other traits

Dodge: 0.46

Mid: 0.06

Melee: 0.09

Block: 0.00

Reaction time: 0.26

#rw scavenger #scavenger #every scavenger ever #rainworld #rain world game #rw downpour #rain world #rain world downpour #rain world slugcat

[wonho-net]

Most Replayed Parts: ↬ Losing You (0.44)

#wonho #lee hoseok #malegroupsnet #dailybg #kpopco #kpopedit #ceeblr #isaishi #usermarnyia #tuserose #danablr #usershri #useratz #gif #replayed #flashing tw #e:losing you #wenee #m:mau

[mapsontheweb]

Road traffic death rate in the US vs Europe

by u/flyingcatwithhorns

Source:

https://www.iihs.org/topics/fatality-statistics/detail/state-by-state

https://transport.ec.europa.eu/news/preliminary-2021-eu-road-safety-statistics-2022-03-28_en

https://www.who.int/data/gho/data/themes/topics/topic-details/GHO/road-traffic-mortality

Edit: Found the data for a few countries for fatality rate per 100 million vehicle kilometres travelled (higher = worse)

Iceland 0.21

Norway 0.21

Sweden 0.26

United Kingdom 0.34

Germany 0.37

Switzerland 0.39

Slovenia 0.40

Ireland 0.41

OECD median 0.41

Australia 0.44

Finland 0.46

Canada 0.47

France 0.50

New Zealand 0.66

United States 0.83

Czech Republic 0.99

https://www.bitre.gov.au/sites/default/files/documents/international_comparisons_2020.pdf, page 20/34

#maps #flyingcatwithhorns #eu vs us #accidents #deaths

[moonlit-trolls]

i like seeing recipe channels on youtube. and it's like

"You can make this for 5 dollars :)"

BITCH WHERE DO I FIND 0.44 DOLLARS OF RICE. Oh yeah lemme go and fucking buy 0.20 USD of potatoes. i don't think that's possible bitch.