#Anne with an E Predictions

[pyramidsoul]

The Dahmer Case and The Cannibalism Topic

“Cannibal” was the adjective used by media to refer Dahmer the most as they learnt of the man’s gruesome acts. It was synonymous of terror and horror at that time, the name of Jeffrey Dahmer echoed not only in the city of Milwaukee but also around the entire world. It was unusual to hear of a criminal who eat his victims, it was a shocking news, and the name of Jeffrey Dahmer was remembered under the name of "The Milwaukee Cannibal”. But what was behind this name? What did it mean for Dahmer and where's cannibalism come from?

Jeffrey Dahmer in 1991

The Cannibalism for Jeffrey Dahmer

The cannibalism act didn’t occur immediately but it happened later with his sixth victim Raymond Smith (aka Ricky Beeks). Jeffrey Dahmer just moved in his new apartment in Milwaukee, at 924 N. 25th St., and he was ready to live by himself after leaving his grandma's house. It was already some years that Dahmer decided to attend gay clubs, where he frequently had encounters with strangers for one night stands. It was 1990 and Dahmer already doped and raped many boys, killing five of them too. But it was starting to not be enough, Dahmer was unsatisfied and he needed more. Cannibalism presented itself as a "simple" next step for Dahmer: after experiencing gay sex, to then having an unconscious body on his hands, on wishing to preserve all that pleasure, and seeing the people as objects, cannibalism subsequently followed as a inevitable action.

Dahmer's desire was to keep people with him, to do not forget the experiences he had with them. The previous attempts as doping the person or seeking for a corpse were a way to feel people close to him at his complete availability for Dahmer, motionless. He thought about the next step: "I began to feel that I needed more of a rush. I thought to myself, I want more. I wanted to keep this one, but I wanted him in me. I wanted him to become a part of me. That's when the idea of eating part of his body occurred to me." (- s. Grilling Dahmer). Dahmer's act wasn't a way to feel more evil or powerful, this was an action of a man who wanted to feel his victims closer. It happened again on his act on cutting and wearing the victims' skin, he wanted to become one with them, wrapped on their skins. At the end he also had the idea of "creating" living zombies willing to follow his orders and to stay with him forver.

The first article ever published on July 23, 1991, on The Journal, written by reporter Anne E. Schwartz, the first and only reporter to come to the scene visiting Dahmer's apartment.

Public’s Take on Dahmer’s Cannibalism

Predictably, people's reaction to Dahmer's cannibalism was shock. Local Milwaukee citizens didn't expect something like Dahmer's case to happen, Milwaukee was a pretty quiet city in Wisconsin where nothing like that ever happened. Soon the morning after Dahmer's arrest, Oxford apartments were already printed in the first page of The Journal, and Jeffrey Dahmer's case was already in people's mouth.

The most concerning, disgusting and shoking element on the case was surely the cannibalism, as already expressed before. At the beginning the cannibalism was an unverified uncertain information, and the reporters had to confirm it by looking at the confession, but soon after that it quickly became a first page topic. Dahmer’s cannibalism was printed on the first pages of newspapers, aimed at shocking people even more. For this reason journals of that time looked for the most unconcerning news, making fake news at times as well. Cannibalism became a topic of so much discussion, almost distorted, the main Dahmer’s case object to be so overused that journalists kept inventing fake news just to shock people even more. They made Dahmer appear like a sadistic monster who felt pleasure when eating all his victims, while the story was quite different as expressed in the paragraph before. Even Dahmer himself had fun with these kind of articles: “Isn't it amazing what they come up with?” he said.

(1)(2)Two articles taking about Dahmer’s cannibalism. (1) Courtesy of jdapt213. (3) Dahmer showing the fake news in court, 1992.

Specialists talking about Dahmer's cannibalism

Psychiatrists and experts tried to give an explaination on Dahmer’s cannibalism. Writer Brian Masters develops an interesting point when talking about infantile play, of parents pretending to be animal ready to devour them and the kids responding to be ferocious cannibal animals. Dr Morrisons also says: "Jeffrey Dahmer was not the only individual who was a cannibal or bit his victims, using his teeth as a weapon. If you remember about infancy, if we go purely psychologically, the only way an infant interacts with the world around him is to touch, feel and teeth, and this is a way that babies explore their world with their mouths. That’s what they use, that’s how they relate to the world. What is evident in all the serial murders is this trait of very oral or mouthing or biting or eating, ingesting, which is very infantile. But it seems a way in which they can be with their victim.”

Even through sexual acts, mouth is an important way to express love. Activities as biting or oral sex rekindle the childish instinct where loving and eating are bounded together. “The adult who prefers oral sex above other sexual experiences indicates an infantile need for nourishment, a wish to recreate the moment of being mothered.” Brian Masters writes. If we look back at Dahmer’s infancy, we notice some early behaviours which indicates some connections to his cannibalism. As already expressed before, cannibalism was just a consequence which came after as Dahmer’s needs continued to evolve. Yet Dahmer always had a lack of social skills, he had difficulties on creating bounds with other people and he was often so isolated. His father Lionel was out bacause of his job, while his mother Joyce struggled with her mental health. Jeffrey found himself alone with the mother's unconscious body some times, there it might have been the moment where he put his hear on his mother's chest to check if her heart was still working, action which was subsequentially repeated with his classmates in highschool and later with his victims. People always left, he was alone, and his lack of social bonds brought him to be even more introvert. Eating an individual is the deepest connection a person can ever get, it removes the feeling of alienation since the victim will live inside them forever and become a permanent part of themselves.

Jeffrey Dahmer's drawing project on creating a shrine where to put his victims' skulls and skeletons, a place to remember and collect his thoughts (Dahmer - 1993 interview).

Cannibalism in history and religion

In modern society cannibalism is almost seen as a taboo, something vile and inhumane. However, this isn't an exact definition, and cannibalism is deeply rooted in our origins. During Europe’s Age of Exploration distant people were often portrayed as cannibals, almost rapesented as bestial creatures. Instead, during 20th Century, the figure of the cannibal was studied more, the new approach wanted to explain more of this behavior, inserted into a certain context. The reasons that lead people to a person could be multiple: a warrior could eat the heart of his opponent to feel more powerful and take his power; a person can eat a relative body to express love and grief for the loss; or again some people can eat a human body as a necessity to survive.

The firsts reports on cannibalism can be found in ancient Greek times with the epic poem The Odyssey by Homer or Histories by Herodotus, but anthropologists suggest that cannibalism dates back to prehistoric times. Moving on, the discovery of cannibals by Cristoforo Colombo in America made people question about the topic on Christian doctrine of the resurrection for example. For that reason Christianity is probably the best example to take in consideration: one fo the most diffused religion in the world, the tenet of paganism, has a mystic ritual of "eating and drinking" the flesh and blood of Christ. For love, the person can be ate, based on this religion. In other cultures, the Iroquois and Fijians ate the flesh of their defeated enemies in order to absorb their power; for peoples of Papua New Guinea ate the heart or brains of their deceased elders to honour them; In medieval and modern European culture the practice of eating human was prevalent for religious or medicinal purposes. About medicinal purposes again, Chinese compounds included human organs as well as nails and hair, while, in early Greece, human blood was thought to treat epilepsy.

The Sons of Pindorama, Cannibalism in Brazil in 1557 as described by Hans Staden. Gravure de Théodore de Bry, 1562.

Cannibalism around the world

Dahmer was obviosly not the first criminal cannibal, names as Albert Fish, Issei Sagawa and Andrei Chikatilo are still remembered for their crimes and their cannibalism. As said before, the reason of cannibalism change based on the person and his deeds- the cannibal Armin Meiwes (aka Rotenburg Cannibal) ate 20 kilograms (44 lb) of human flesh of his victim, after that this last one agreed and wanted to be slaughtered, for sexual pleasure; Joachim Kroll (aka The Ruhr Cannibal) had a practical view and consumed his victims’ meat to save on his grocery bills, because meat was expensive. Albert Fish, on the other hand, eating the meat of the victims was like a trophy and liked to describe how the kids tasted to their parents.

Today, cannibalism among the population is rare, but still exists. Because of poverty, people living in Olinda slum are usual to consume human meat. Otherwise, there are tribes and cultures where cannibalism is still present. In Western New Guinea there’s a tribe called Korowai, whose tribesmen believe mysterious deaths are attributed to a demon, and their duty is to consume the dead’s meat in order to take revenge. In Fiji (previously named “Cannibal Island”) was famous for cannibalism, even if now this practice almost died out in the recent years. In India there’s a sect of Indian Monks called Aghori, whose few remaining members are used to drink from human skulls and cover their body in burnt human remains. There are also rumours of some cannibalism acts happened in The Democratic Republic of The Congo, Cambodia, Nuku Hiva and Liberia.

In animals cannibalism is common as well, mostly in invertebrates and fishes, but it occurs in other animal groups too. The filial cannibalism (usually when the young can’t last much because is sick, deformed or the mother can’t provide enough food, it becomes nutrient for the parent) is present in major species as leopards, African lions, Tonkean Macaques and fishes. The infanticide (males killing infants who aren’t theirs) is present in North American red squirrels, lions and chimpanzees. The matriphagy is when the mother is ate by the infants, another cannibalism form diffused within insects and arachnids. At last but not least, cannibalism can be diffused way earlier with eggs. The Burton’s Mouthbrooders carry their eggs in their mouths, and sometimes more than three-quarters eggs are been ingested. The female sharks instead, carry hundreds on eggs inside them, while they’re mating with multiple male sharks. Inside the womb, developing sharks will eat the unfertilised eggs and their siblings, leaving at the end only two unborn sharks, each one for each uterus.

(1) Tadpoles eating another tadpole, picture by Georgette Douwma, Nature Picture Gallery. (2) Korowai tribesmen, picture by Kristian Cabanis.

Sources: The Shrine of Jeffrey Dahmer; Grilling Dahmer; Monster: The True Story Of The Jeffrey Dahmer Murders; Britannica; Anthroencyclopedia; Jeffrey Dahmer trails on Court.tv; NBC; The Sun; National Geographic.

[shadowtriovibes]

break a sweat: chapter two

Pairing: Sebastian Sallow x f!MC

Chapter Rating: T [Fic Rating: E]

Word Count: 2.4K

Summary:

“Just between us,” you ask Anne quietly, “Do you think he’s really got a chance at making the team?” “Oh, he’ll make the team,” Anne says easily. “He’s really a brilliant athlete, but don’t tell him I told you that.” “Really?” you ask, surprised. “I suppose I never thought about him that way. He always seemed so… scholarly.” “He is,” she says fondly. “Just like our parents, really, but… after they passed, he decided he didn’t want to go down that same path. All the books, all the research – it can be stifling. He’d much rather be a hundred feet in the air than stuck in a cellar.”

AO3 permalink: break a sweat

September 10, 1892

As Sebastian had predicted, Imelda Reyes had assumed the captaincy of the Slytherin Quidditch team, along with one of the Chaser positions. The morning after the start-of-term feast, she’d posted a notice in the common room formally announcing tryouts.

Sebastian was practically buzzing as soon as he’d read that the Seeker position was available.

“Will you tell the others I’ll be late to dinner?” he asked you casually as he gathered up his practice robes and his broomstick. “I’m going down to the pitch for a bit.”

(The way he said “the others” made something warm and a bit possessive twist in your stomach, but you’d just nodded without a word.)

Two weeks later, you link arms with Anne and Ominis to walk down to the Quidditch pitch and watch the Slytherin hopefuls face Imelda’s famously brutal tryouts. With the September sun shining down, you’re tempted to shed your cloak before you’ve even settled in the stands.

Ominis looks quite smug as the two of you lead him toward the pitch.

“Now that I’ve got a brilliant witch on each arm, I suppose I won’t be needing my wand to get around,” he teases.

“As it happens, I know a thing or two about that wand of yours,” Anne replies. “Last summer I spent a full month reading books on wandcraft that Sebastian brought me from the library. If I had to guess, I think you can probably ‘see’ more clearly than either of us can. It’s very powerful.”

“I’ve no idea what you’re talking about,” Ominis demurs. “I’m just naturally perceptive.”

When you arrive at the pitch, the three of you take seats in the back row of the spectator stands alongside some of your housemates. The crowd begins to whisper excitedly when the aspiring Slytherins begin to take the field, brooms in hand.

You spot Sebastian quickly, even among nearly two dozen others in green and silver practice uniforms circling for warmups on their brooms. Compared to how strong he’d looked at the start of term in just his school robes, he looks powerful now – equipped with pads across his shoulders, forearms, and shins that only accentuate his muscular form.

Being Sebastian, of course, he’d declined a helmet. (Despite his newfound bulk, he’s still the same exasperatingly headstrong boy for whom you’ve held a candle for nearly your entire school career.)

“Just between us,” you ask Anne quietly, “Do you think he’s really got a chance at making the team?”

“Oh, he’ll make the team,” Anne says easily. “He’s really a brilliant athlete, but don’t tell him I told you that.”

“Really?” you ask, surprised. “I suppose I never thought about him that way. He always seemed so… scholarly.”

“He is,” she says fondly. “Just like our parents, really, but… after they passed, he decided he didn’t want to go down that same path. All the books, all the research – it can be stifling. He’d much rather be a hundred feet in the air than stuck in a cellar.”

You watch Sebastian take laps high above the grassy pitch with a joyous smile on his face, and you think you understand exactly what Anne means. He’s free here.

“In that case,” you sigh. “What position, do we reckon?”

Anne smirks. “Truthfully I think he’ll have his pick, unless Imelda wants to humble him on purpose.”

“Which one would be humbling?” you ask, bemused.

“Probably Chaser,” she muses. “He’d be an excellent Chaser, of course, but it’s his least favorite.”

“I’d like to see him become a Beater,” Ominis chimes in. “It would serve him well to have some sort of outlet for his intensity.”

“Fine, then I’ll say… Keeper,” you say, smiling to yourself. “That way he’ll get to stay in one place the whole game and know that everyone’s eyes are on him.”

Anne snickers and extends her hand for you to shake, sealing your first wager of the day.

—

After tryouts conclude, the hopefuls and spectators return en masse to the Slytherin common room to await the captain’s decision. Imelda immediately sequesters herself in the seventh-year girls’ dormitory to put together her official roster, and the majority of Slytherin’s upperclassmen start passing around Butterbeers while they settle in wait.

Sebastian is inarguably the center of attention, casually leaning against a table in the corner with Anne seated at his side. A flock of fifth-year girls crowds around him to listen intently as he talks about the impressive diving save he’d made during a Seeker drill, capturing the Snitch just feet from the ground.

“He’s going to be insufferable now,” Ominis groans while the two of you observe from across the room. “There’s barely enough room for his ego in this friendship as it is.”

“Come now, we’ve had plenty of practice keeping him in line,” you laugh. “And now we’ve got Anne as well.”

“It really is good to have her back,” Ominis agrees softly, smiling to himself when he hears Anne’s voice through the noise as she starts to loudly tell Sebastian’s lovesick fan club how he’d attempted a similar save over the summer and ended up crash-landing in an abandoned poacher camp.

You glance sidelong at Ominis’ private smile, noticing that his pale cheeks have gone a bit pink.

However, before you can spend too much more time thinking about Ominis and Anne, you hear the noise in the room reach a crescendo as Imelda saunters down the stairs with a rolled-up piece of parchment in her hand.

“Who’s ready to meet the new Slytherin Quidditch team?” she calls out, and the entire room bursts into excited cheers.

You and Ominis weave through the crowded common room to stand by Sebastian. On the outside, he seems to be perfectly calm, but by now you can recognize that telltale tension that lingers in his jaw when he’s nervous. Anne holds one of his hands to reassure him, looking a bit anxious herself.

You discreetly take his other hand and gently squeeze it; he squeezes back without a word.

Imelda starts to read off from her list, allowing brief pauses for applause after each name. While she works her way down, the four of you learn that Sebastian has not been named Slytherin’s Keeper. He’s not a Beater either, nor is he ultimately a Chaser.

“Lastly, your newest Seeker…” Imelda teases as she reaches the end of the list. “Congratulations, Sebastian Sallow!”

Sebastian beams brilliantly while Anne leaps to her feet and pulls him into a tight hug. Ominis smiles and murmurs his congratulations to his friend, assuring him he always knew he’d make the team.

There are several other girls who are eager to offer their congratulations as well, so you wait for the crowd around him to subside and for Anne to escort Ominis to get more Butterbeers before you sidle up next to Sebastian and nudge your shoulder against his.

“Excellent work, Bash,” you murmur. “I have to say, that was quite a show you put on earlier.”

“It was only because you were watching,” he flirts back, and you roll your eyes fondly.

Since the start of term, he’s been relentless with his play-flirting. You’ve tried to resist it as much as you can, but it always makes your heart race when he calls you “love,” or offers to carry your books for you, or even charms little notes poking fun at your classmates into tiny birds that gracefully land on top of your desk.

(You haven’t had the heart to ask him to stop, because even though you know he doesn’t mean it the way you would, it still feels nice to be the center of his attention.)

“Then I’ll have to come to see you start in next week’s match,” you offer. “Especially if you only play that well when I’m watching.”

“You can be my good luck charm,” he jokes. “Felix Felicis is prohibited, but you are not.”

“Merlin, that was awful,” you laugh, but Sebastian just grins proudly.

“I have a brilliant idea,” he says after a moment. “We should make a bet.”

“A bet?” you ask. “What, that you’ll win?”

He shakes his head. “That’s too easy. We’re playing Hufflepuff, we’ll obviously win. I meant something more challenging.”

“You’re very confident,” you laugh. “Fine, what are your terms?”

He considers his offer for a moment and then says, “I’ll bet that I can catch the Snitch in under thirty minutes. I’ll even let you be the official timekeeper, since I’ll be a bit preoccupied.”

“Under thirty?” you ask skeptically. “That’s nearly professional, Sebastian. Ominis told me most games last at least an hour.”

“I’ve been practicing all summer,” he insists. “Anne would release a Snitch and I’d even let it have a five-minute head start, but I never let one get further than the far side of Marunweem Lake.”

“Careful, Sebastian, you sound a bit cocky,” you murmur, and you think you see Sebastian’s gaze dip down to your mouth for a split second.

“I am,” he agrees. “In fact, I’ll even let you pick your prize first, for if you win.”

“Alright,” you laugh. After taking a beat to consider, you suggest, “When I win, I want… for you to write my History of Magic assignments for the next month.

“That’s it?” he says with a scoff. “You could have anything you desire from me, and you want me to write your essays?”

“I didn’t start studying magic with the rest of you lot, and I don’t know a lot of the foundational things that Binns wants us to reference,” you remind him. “You know your history much better than I do, and I need to bump my ‘Acceptable’ up to ‘Exceeds Expectations’ by the time N.E.W.T.s roll around.”

“Love, I would’ve done them for you anyway,” Sebastian says dismissively, and you bite the inside of your cheek to keep from grinning at the nickname. “Why don’t you pick something fun?”

“Fine,” you reply. “I want…”

You mull over your options for a moment, trying to think of something that isn’t obscene or pathetic. Finally, you have an idea.

“There is one thing I’ve been thinking about,” you tell him, a secret smile on your lips.

Sebastian perks up, leaning in closer. “Go on, then.”

“I want you to help me convince Anne and Ominis that they should be a couple,” you say carefully, watching him for any signs that he’s about to throw a fit.

He just blinks at you, bewildered. “...What.”

“I think they would make a lovely pair,” you croon. “And I know that she’s your sister and you’re rather, er...”

“I’m what?” he demands.

“You’re very protective of her,” you say tactfully. “But we’re all adults now, or at least we’re close enough, and I think they really understand each other. I want you to help me convince them that they should give it a chance.”

Sebastian is quiet for several long moments.

“Well,” he finally murmurs. “I would prefer if Anne never dated anyone so I wouldn’t have any more reasons to worry about her, but I suppose if she must, Ominis is a good man.”

You shout excitedly and wrap your arms around his impossibly broad shoulders, pulling him in for a hug. He easily allows it, fondly pressing his nose to your hair.

“I suppose it doesn’t really matter though,” he murmurs against your temple. “Seeing as you won’t win and I’ll never have to aid you in your scheming.”

You lean out of the hug just enough to see Sebastian’s face, not yet ready to pull away entirely. “Speaking of which, what prize will you not be winning?”

Sebastian lets his hands drop down to your hips as he murmurs, “I actually have something in mind.”

You force yourself not to get distracted. “Do tell.”

“When I win, I’d like to take you to the Room of Requirement after the game,” he says, and the way he grips your sides through your skirt ensures you have no way of misunderstanding what he’s suggesting.

“O-oh?” you ask softly, squirming a little in his grasp. “Just me?”

“Just you,” he confirms.

His eyes are dark, and despite the cacophony of the room, he’s focused solely on you.

“And what exactly would we be doing in the Room of Requirement?” you ask softly.

He doesn’t dignify your question with a response. Instead, he deliberately drags his thumbs across your hips, raking his gaze down your body and back up with a pointed look.

Countless generations have come of age at Hogwarts, and much like those who came before you, students in your year are beginning to discover that the castle’s myriad of secret rooms and hidden corridors can be useful in exciting new ways.

You know precisely what it means to be asked to join Sebastian somewhere private – and on top of that, somewhere so entirely yours that you can be sure he’s never asked another girl to join him there.

“Do you mean it?” you ask him quietly. “You aren’t just teasing like earlier?”

“When was I teasing?” Sebastian asks, amused.

“This whole time, since the start of term,” you insist, fidgeting nervously with the laces at the front of his Quidditch robes he’s still proudly wearing. “All the flirting, all this back-and-forth. You’re just winding me up, aren’t you?”

“I’m not,” he says quietly. “I thought about you all summer, love. Nearly drove Anne mad with how pathetic I was over you, and I… I sincerely want you, if you’ll have me.”

Merlin.

Some bold, sensual part of you encourages you to crowd in a little closer so you can lean up to his ear and ask, “Are you sure we shouldn’t simply go to the Room of Requirement right now?”

You hear Sebastian swallow and sharply exhale.

“N-not now,” he answers. “After the match. I just…”

He doesn’t have the words to articulate it, but he wants to earn your affection. He has to prove he’s worthy first – that you aren’t making a mistake by letting him turn your close friendship into something more.

“Alright,” you acquiesce, gently brushing your lips against his cheekbone before taking a step out of his embrace. “Just don’t get too distracted and fall off your broom, because I really want you to win.”

“The match or our bet?” he asks in a low voice.

Before you disappear into the crowd to rejoin your friends, you murmur, “Wouldn’t you like to know, Bash?”

[bethanydelleman]

Would you do a poll on worst Jane Austen heroine? I know most people hate Emma, but for me Marriane is the worst Austen heroine. EVERYONE indulged her till the end, and I do not see her temperament improving in the end. It's just that she ultimately fell in love with a rich guy, so going forward no one would provide any resistance to her ideologies and vanities and indulgences. I wish Elinor and Edward would transfer to some other clergy. Eh, but I digress.

So no, I will not make or reblog that poll. Mostly because I find it boring. I know the answer. The least liked heroines are Emma Woodhouse, Fanny Price, and Marianne Dashwood. People also dislike Catherine Morland for being "stupid" though her book is read less so she'll be in the middle. The most admired heroines are Elizabeth Bennet, Anne Elliot, Jane Bennet, and Elinor Dashwood.

But also, this here is a Emma, Marianne, Catherine, and Fanny defense blog. And, more importantly, Elinor loves Marianne. The reconciliation between the two sisters is a beautiful part of Sense & Sensibility! They love living beside each other. And Marianne is going to keep maturing, she's only seventeen when we have her last quoted speech.

Also, this sounds like a much more mature and less selfish Marianne, "Marianne found her own happiness in forming his." The ending of Sense & Sensibility is beautiful in that the sisters find their love of each other:

Between Barton and Delaford, there was that constant communication which strong family affection would naturally dictate; and among the merits and the happiness of Elinor and Marianne, let it not be ranked as the least considerable, that though sisters, and living almost within sight of each other, they could live without disagreement between themselves, or producing coolness between their husbands.

As for indulging her, Mrs. Jennings makes fun of Marianne's behaviour, Elinor occasionally calls her out on it, and if Mrs. Dashwood doesn't it's because they are very similar people and their father/husband died like 6 months ago. If Marianne is indulged, it's because she is young and pretty harmless. She doesn't usually insult people to their face, she just stays silent if she disagrees with them or dislikes them. And honestly, Elinor is a saint for not punching her brother and/or SIL in their stupid faces.

I also will not make or reblog polls of favourite Austen novel (P&P wins, MP loses, yay...), favourite hero (it's always Darcy), least favouite hero (Edward or Edmund), or least favourite pairing (either E&F because of the first cousin thing or one of the big age gaps, because of age gap). Not only is it completely predictable, it's not even fun to discuss.

[lizziebeanz]

10 Books Read in My 27th Year:

1. 'Interview With The Vampire' by Anne Rice

4.75/5 stars

We all know it and love it, a classic tale of gay vampires. Of course. The film is one of my absolute favorites (Haydn's Piano Sonata No. 59 in E-Flat (a.k.a 'Lestat's Sonata') is my wake up alarm), so naturally; I wanted to read the book and I loved diving deeper into not only Louis' story, but Lestat's, Claudia's, and Armand's stories. It helped to understand more everyone's motive. Not only that, but it was just as prosaic as the film. Truth be told, I think the TV show managed to follow more closely to the book than the film.

Definitely planning to read her other works in this series.

.25 stars deducted because it's just walls of text.

2. 'Psycho' by Robert Bloch

5/5 stars

Another classic! The writing of this book was fantastic, I would recommend to everyone. The descriptions were vivid, yet succinct, and I felt like I was really in this world. I literally finished reading it in two days, it was that good. I needed more after reading so decided to watch 'Bates Motel'.

3. 'Sappho' translated by Mary Barnard

4.5/5 stars

I enjoy poetry, and felt like this was a good jumping off place to start getting into more poetry. Oftentimes I felt I needed to know more about Sappho or just have more knowledge of ancient Greece to understand better Sappho's poems; but, I took solace in reading the notes in the back of the book explaining that these were most likely just little observations of her everyday life. There were many poems I felt a connection to, and I think that's a beautiful thing to feel a connection to someone who lived over a millennia ago.

4. 'all about love: new visions' by bell hooks

5/5 stars

I love reading bell hooks' writing and this book helped me to see love in a completely different light. Helped me to further embrace loving not only myself but others. I'm on a journey of self-healing and self-love this year; although it is difficult work, and, although this journey must continue on throughout the rest of my life, this book has helped tremendously with this journey. I highlighted passages that I felt a connection with and plan to re-read it in the future to see what else I can learn.

This book is such a revolutionary idea of how love can and will change the world. I have thought about a lot of the passages within this book almost daily and have tried to keep in mind these ideas and to practice love in my daily life.

5. 'Mexican Gothic' by Silvia Moreno-Garcia

4.25/5 stars

This was a really good book, I finished it pretty quickly because every chapter left me wanting to know more. It's got everything: mushrooms, creepy houses, incestuous families, murder...

Deducted .75 stars because either the story was too predictable, or the foreshadowing was too foreshadow-y.

6. 'Five Quarters of the Orange' by Joanne Harris

1/5 stars

I was actually kinda disappointed with this one because the author wrote 'Chocolat' and the reviews were praising the book. The narrator begins the book talking about how she and her family did something awful in Nazi-occupied France but what that something was is not disclosed until the last 20 pages of the book! Some may say that's "suspense", but to me that's just unnecessarily dragging something out. I guess I just did not like the main character and narrator, and maybe that was the point.

7. 'Night of the Living Rez' by Morgan Talty

5/5 stars

This book is a mixture of warmth and sorrow and fear and wonder all wrapped up in one. It's an amalgamation of stories that force the reader to truly see how certain events in one's life can alter the trajectory of life itself. There are stories of childhood friendships and curiosity. There are stories of the love shared between siblings and of love shared between parents and children. There are heartbreaking stories of loss, of pain, of trauma. And the question you will keep coming back to is, "How did we get here?".

8. 'Rebecca' by Daphne du Maurier

4.8/5 stars

Fantastic writing! I can say that this novel altered my working vocabulary. The writing was so good, in fact, I didn't even mind that it was an English romance novel (I've learned I'm not too fond of classic English literature). I did guess at the ending fairly early on (and was right!); however, the ending had so many twists and turns I wasn't expecting, making for a thrilling suspense! The only reason I deducted .2 stars is because I did not like our narrator.

9. 'Murder on the Orient Express' by Agatha Christie

5/5 stars

Holy shit. That's all I have to say. I understand why people love this book now, I was getting whiplash at the end!

10. 'Here Goes Nothing' by Steve Toltz

3.5/5 stars

I loved the philosophical questions posed in this book and I also enjoyed visualizing a different idea of what the afterlife could possibly be (love hearing different theories); but, straight out the gate: I did not like one of the main characters. So...point deducted for THAT. Read it, or don't!

[the-bone-queen]

Recently finished Translation State by Ann Leckie, which always makes me think about the way autistic people are often robot and/or alien coded. Yet, those books make me feel seen.

Full poem under the cut.

Translation: Human

by E. Smith Umland

It’s the wires that are wound wound/ing

threaded with bone//

does the autonomy keep you up at night?

how do you digitize / decay </close

enough to open> your stomach

to make an entrail/ed prediction

[[de/carbonization of the body

]] shot through with electricity

ending up in the land //fill/>

matter of swelling matter of

sweating. <water drunk//

sun sought/ > [does the autonomy

// come from

you?]

[shadowfaxnews]

Shadowfax Rolls Out AI-Backed Address Intelligence System For Seamless Deliveries

SUMMARY

Shadowfax launches SF Maps, an AI-powered address intelligence system for accurate deliveries.

2. The new system predicts customer locations with over 90% accuracy within 100 meters, reducing cancellations by 10%.

3. SF Maps uses artificial neural networks and real-time data integration to navigate India’s complex addressing system.

Shadowfax, India’s leading provider of cutting-edge e-commerce logistics solutions, proudly introduces SF Maps, an advanced AI-based address intelligence system designed to enhance delivery accuracy and efficiency. This innovative tool predicts customer locations with unparalleled precision, setting a new industry standard with over 90% accuracy within 100 meters of the intended destination. SF Maps greatly improves navigation for delivery partners, thereby assisting e-commerce platforms and Direct-to-Consumer (D2C) brands in reducing cancellations due to address inaccuracies on their platforms.

In contrast to standardized address formats prevalent in Western countries, Indian addresses often lack structure, are susceptible to language and understanding-based gaps, and are highly prone to input error posing challenges in pinpointing exact locations during delivery. SF Maps addresses these complexities by leveraging a sophisticated AI/ML model trained on a vast dataset of Shadowfax’s past deliveries and pickups exceeding 1.5 billion data points. This model adeptly handles incomplete addresses, ambiguous area names, reliance on distant landmarks, and inaccurate pincodes, ensuring smoother operations. Further, precise navigation to customer addresses enables seamless deliveries without the need for additional calls, effectively reducing instances of missed deliveries and improving overall efficiency. Since the introduction of SF Maps, Shadowfax has achieved a significant reduction in customer cancellations or RTOs (Return to Origin) by almost 10% and boosted customer Net Promoter Score (NPS) by 25%.

Vaibhav Khandelwal, Chief Technology Officer at Shadowfax, “SF Maps represents a significant leap forward in our mission to optimize the delivery speed and elevate customer experience while solving fundamental problems in last-mile logistics. This innovative AI model trained on our vast set of historical delivery data drives significant operational efficiencies for us. We deeply understand the problems that arise due to incomplete addresses and how it hinders further innovation and hence we aim to make this AI model generally available for research in the future.”

Under the hood, SF Maps uses an in-house Artificial Neural Network (ANN)-based embedding model, trained using a Siamese Network architecture. The generated embeddings are fed into VectorDB and the extracted locations are passed through H3 geospatial indexing, further fine-tuning location intelligence. This custom-built model captures complex contextual relationships between address components and their geographical associations, leveraging deep learning algorithms to discern intricate patterns for more accurate location-based intelligence. The underlying algorithms and design architecture allow SF Maps to be a self-correcting engine that captures changing ground operations realities. The feedback loop is powered by real-time delivery partner geolocations that Shadowfax captures every 5 seconds while they are on their platform. Shadowfax also deploys a WhatsApp-based conversational bot that interacts with customers and gathers address information for improved results and error correction.

For more information, visit https://www.shadowfax.in/

[robbierants]

Anne With An E Rant❤️

My fav AWAE Season Is Season 3

Moira Walley-Beckett, creator of the show, weaves a tapestry of both the nostalgic and contemporary. The result is a masterpiece, with the idyllic and charming small town life of Avonlea a perfect contrast for the weighty issues the show tackles, issues that are particularly relevant today. The young but talented cast, led by Amybeth McNulty as Anne, Dalila Bela as her best friend Diana Barry, and Lucas Jade Zumann as Gilbert Blythe, bring the story of Anne of Green Gables to life.

The major theme of the show is its message of acceptance, beginning with titular character Anne Shirley’s struggle to be seen as something other than a ragged orphan who is up to no good.

When Matthew and Marilla Cuthbert (played by R.H. Thomson and Geraldine James respectively) take Anne into their home, they are unprepared for what’s coming. Her big ideas, matched in size only by her big heart, take the little town of Avonlea by storm at first. But the Cuthberts, along with the rest of the town, soon grow to appreciate Anne’s imagination, creativity, and kindness.

Not stopping there, Walley-Beckett introduces Queer characters, Aunt Josephine Barry, and Season 2 newcomer Cole (I fucking love him sm), a classmate of Anne’s. When Cole is shunned by his classmates and family for who he is, he contemplates suicide. It is only Anne’s intervention that saves him from a terrible fate. He eventually finds his place living with Aunt Josephine in Charlottetown, a more progressive town than Avonlea.

Walley-Beckett goes on to bring racial prejudice into the mix as well, with the introduction of Bash, a funny and lovable man who hails from Trinidad, and befriends Gilbert Blythe, Anne’s love interest, while they work aboard a steamer together. Bash goes on to become Gilbert’s business partner, and moves to his farm. It is Gilbert, Anne, and the Cuthberts who make him feel welcome in Avonlea, despite the initial rejection he faces by the rest of the town.

The fight for women’s equality comes into play as well, in the form of Miss Stacy (MY QUEEN) , the new schoolteacher, whom Anne calls a ‘kindred spirit’. An independent woman with radical ideas, Miss Stacy scandalizes Avonlea by donning trousers and refusing to wear a corset.

Season three is as funny and charming as it is heartbreaking. Taking place right when Anne turns sixteen and is busy preparing for the Queen’s College entrance exams, the season deals with acceptance once more: of our fellow man, of identity, and of growing up. Anne’s desire to find her birth parents speaks to all of us who have wondered where we come from. Marilla’s fear that Anne will leave her if she finds out about her blood relatives rings painfully true. It is here that Walley-Beckett teaches us that family is family, by blood or otherwise.

The racial prejudice theme is prevalent once more in Season Three. Bash, his wife Mary, and their child Delphine try to find their place in Avonlea, who is quick to spurn them based on the color of their skin. A new storyline featuring a Native American tribe, the Mi’kmaq, living in the area, sheds even more light on racial issues. The townspeople view them with disdain and fear. Predictably, Anne does not follow their example, and befriends Ka’kwet, a young indigenous girl. (I love their dynamic sm 💕)

With the Mi’kmaq storyline, Walley-Beckett does not gloss over the more unsavory parts of history, but instead brings things out into the open with Ka’kwet’s enrollment in a new school set up by the government for Native American children. What follows is a glimpse into the shocking events that occurred in that era, with the violent kidnapping of these young children, and their forced assimilation. The school turns out to be nothing short of a prison, where Ka’kwet’s beautiful braids are chopped off, and her Mi’kmaq heritage ripped away from her and her fellow classmates, starting with their being rechristened with English names, and forbidden to speak their language. Ka’kwet eventually escapes, but is taken back by force. Her desperate parents are threatened and shot at when they try to get her back.

Anne and her classmates stir up controversy in the town when they fight for freedom of the press after Anne writes a strongly worded editorial about equality. When Josie rejects Billy’s sexual advances, he spreads false rumours about her to ruin her reputation. When nobody looks at him as being in the wrong, Anne is indignant enough to write an editorial about the events that occurred. She comments on the double standards that seem to exist when it comes to gender, and the importance of spoken consent. The town board is infuriated, and retaliates by giving the paper a pre-approved list of appropriate topics to write about. They stipulate that the newspaper will be shut down unless they follow these guidelines, and fire the instigator of the controversy, Anne, from the paper. I'm proud that Anne did this.

Anne brings her classmates together to protest, and in a moving scene, they stand together, mouths gagged by handkerchiefs, and silently hold up a hand painted sign emblazoned with their message: Freedom of speech is a human right.

With this storyline, Walley-Beckett succeeds in addressing many of the issues we discuss today; freedom of speech, media censorship, consent, and gender equality, all without seeming too forced or unrealistic. There is no magical solution for all the problems, but small triumphs recognized as steps to making a major change that the world will one day be ready for. It is richly satisfying and simultaneously accurate for the time period, as women back then still had a long way to go in the fight for equality.

Finally, Anne and her classmates face their biggest challenge: entering the adult world, and dealing with the heavier problems that comes along with. Plans for the future are discussed, preparations made, and farewells exchanged. Matthew Cuthbert struggles to deal with Anne’s leaving for college, a familiar concept to any parent. Anne is left with second thoughts about leaving Green Gables, and cries in Marilla’s arms for the childhood she leaves behind. Diana Barry, meanwhile, makes the decision to attend Queen’s College, rebelling against her parents’ plans for her to go to finishing school in Paris. The right to and the importance of education for women as well as men is addressed here. Diana is eventually successful, and comes to join her classmates at Queen’s.

And finally, Gilbert and Anne confess their feelings for each other. They wave goodbye to each other as they go off to their respective schools, and the credits roll at last.

With all the topics Anne with an E fearlessly broaches, it is as surprising as it is dismaying that the show has been canceled. The season ended off with hints of a burgeoning romance between Miss Stacy and Bash, a multi-racial couple, and the beginnings of a possible public exposing of the nefarious nature of the indigenous school.

Ka’kwet is left languishing in the classroom, while her parents set up camp in the nearby woods to wait for an opportunity to get her back.

We are left with the promise of more that will not come, thanks to the show’s cancellation. Poor viewership was blamed as the cause, though outraged fans have already started petitions to keep the series running. In 2020, with corrupt government, fake news, and a general outcry for change, Anne With An ‘E’, with its messages of acceptance and truth, is more important than ever.

The show had a mere three seasons, consisting of less than 30 episodes, whereas medical dramas like Gray’s Anatomy, and sci-fi shows such as Supernatural, have well over 300 episodes. The Simpsons is in its 30th season, despite declining viewership over the years. But ‘Anne With An E’ is gone. Which leads me to wonder: Is the world not ready to speak about the truth?

[queenlua]

i’ve always had a soft spot for “hacker origin stories,” but writer origin stories can be extremely fun & charming too:

5. How did you get started writing sex stories?

The newsgroups back then were these huge topic-sorted bulletin boards, where you could talk on just about any subject in threaded forums. It wasn't like today, where are lots of different places you can go to participate in discussions -- while there were other more private bulletin boards, the newgroups were by far the most well-known and popular. Everyone on-line stopped by there, and people being people, everyone stopped by the sex newsgroups eventually. Just to check them out, you know.

So, like everyone else, I visited alt.sex and learned a lot from the discussions there, like which brand of condoms offered the best combination of sensitivity and reliability, or what happens to the way a man tastes when he eats cucumbers. I visited alt.sex.stories and rec.arts.erotica too (I was an English major, after all, and loved stories), and was just stunned at how bad these stories were. Bad on a level I had never encountered before -- incoherent grammar, impossible spelling, and plots that made no sense at all. I found myself thinking, "I can do better than that!"

It was a very freeing experience -- I had spent so many years reading good stories and great stories and had never encountered truly bad ones. I had thought of writers as almost demigods, with these magical skills. Now I realized that at this level, writing was something I could do. And at least I knew how to spell!

So I wrote a story. A dreadful story, actually, "American Airlines Cockpit." It was just as predictable as it sounds from the title, but at least there was nothing wrong with the grammar. I posted it on the newsgroups and got some enthusiastic e-mail in response. Well, I've always responded well to praise, so I wrote another, "Season of Marriage" (a sweet little arranged marriage love story, which would later become the seed of Bodies in Motion). More raves in e-mail. I wrote more stories. In that first year, I think I wrote about twenty stories (most of them less than 2000 words long) -- probably the most prolific I've ever been. It was a sheer delight, and the wonderful e-mails I got in response were tremendously motivating.

I did try writing a few stories without much sex, and posted them to rec.arts.prose, but nobody seemed to actually read that newsgroup, so they didn't engender any response. I was hooked on those appreciative e-mails, so I kept writing about sex. :-) So in a sense, I really fell into sex writing, almost accidentally. But once there, I found other reasons to stay with it.

(from Mary Anne Mohanraj)

[deltaswapjevil]

Secret Boss 13 I think

This is the most recent art I have but it's not in the usual format

This is part of a project where I make what I called "posters" for my secret bosses with specific songs in mind

This is Radiola with the song a Good Song Never Dies

Radiola is my chapter 3 secret boss prediction with a theme of radio being replaced by television. She also has a theme of beauty within which is why I made her conventionally unattractive. But the beauty within her is a bunch of robot spider legs. I have more info for her but I'm too tired to put it all here

So to make up for it here's some bonus drawings of the previous secret boss Cara Carrie!

This one is based on my favorite portion of The Ballad of Sara Berry:

P is for Patricia drinking Poisoned Punch! R is for Raquel dashed on a Rock...CRUNCH! "O" is what Anne said when Cara bludgeoned her brains! M is for Marianna's Marinated remains! But! But! Q is for Quiara Quiet drowned in the pool! U is for Eunice's pieces spread round the school! But Es are for the Easy way in 5 minutes tops...A one legged girl can bring an N for End by calling the cops...What a bitch! Now what's that spell? P R O M Q U E E N!

(remember to click it to see full image)

Here's an idea for an Omega Carrie and my generic description I sent to my friends

OMEGA CARRIE

I GOT THE SILVER KRIS! I GOT THE CROWN

I GOT THESE BLOODY ROSES AS HANDS

SPOILED SASH AND SCEPTER FOR ONE FINAL DANCE

KNEEL TO THE QUEEN OF HIGHSCHOOL LAND!

Cara has ascended to plantness. She's got a paper fortune teller holding her scepter and the heads of her victims watching from above. Six victims....Six souls....Now all she needs is one more

[whatdoesshedotothem]

Wed[nesday] 15 May 1833

8 5/..

11 3/4

P

L

rain for ab[ou]t an h[ou]r till 9 - found very gentle signs of my cousin an hour preparing

two napkins etc  put one on between three and four in the afternoon F[ahrenheit] 56° at 10 1/4 at w[hi]ch h[ou]r br[eak]f[a]st -

skim[me]d ov[e]r the courier - dawd[le]d away the morn[in]g as us[ua]l - saunt[ere]d out a lit[tle] ab[ou]t 1 alone and read[in]g a few of Volt[aire]s let[ter]s vol[ume] 2

Eliz[abe]th Dalton left us ab[ou]t 2 - so[me]ti[me] d[o]wnst[ai]rs and th[e]n w[i]th IN- [Isabella Norcliffe] in h[e]r r[oo]m and th[e]n co[me] to my own

bef[ore] 4, and wr[ote] out Mon[day] yest[erday] and so far of today till 4 1/2 - the parc[e]l arriv[e]d th[i]s morn[in]g fr[om] Shibd[e]n

forward[e]d fr[om] Edin[burgh] - sm[all] pap[e]r box cont[ainin]g 2 p[ai]r woollen kneecaps and 1 p[ai]r d[itt]o socks fr[om] Miss

Walker (knitt[e]d for me by her) and no[te] fr[om] h[e]r dat[e]d ‘Udale 2 Ap[ril] 24th 1833’ - she seems no better

in mind and surely there neither is nor perhaps out to be any prospect of our being toge

ther tho’ I shall of course expect some answer to my letter to her this day week from York -

Miss W- [Walker] begs to hear fr[om] me bef[ore] my leav[in]g Eng[lan]d ‘when do you leave Eng[lan]d? where are you go[in]g fr[om]

‘Paris? w[i]th wh[o]m do you cross the channel? - I can[no]t tell you an[y]th[in]g really fav[oura]ble of my own mind,

‘I am gett[in]g qui[te] stout, b[u]t I feel th[a]t I am n[o]t improv[in]g in health of mind, and evils seem to increase up[on]

‘me, I ha[ve] n[o]t yet been ab[le] to form one resolut[io]n as to my ret[ur]n ho[me] tho’ my a[un]t says she wishes it

but I dread the idea of returning to greater evil  all your predictions  or I ought to say your warnings

appear to have been realized in me and I get deeper in the mire every day if you saw me now I am sure you

would say I was changed and you would observe it with regret and I begin to fear that my hopes of meeting

you again renewed in heart and body to which I have hitherto faintly clung will never be fulfilled

my sister and Captain Sutherland beg me to say everything that is kind from them with their very kinds regards  accept all that friendship can

offer from myself  pray let me hear from you for I shall not forget you and whatever befalls

me you will hear of either from myself or your aunt  thro’ her at least I can gain intelligence

of you ever believe me yours faithfully and affectionately Ann Walker - dress[e]d - din[ner] at 5 1/4

made notes fr[om] Norc[liffe]s’ tour - upst[ai]rs at 10 50/.. - F[ahrenheit] 67° at 11 3/4 p.m. - an h[ou]r’s r[ai]n till 9 a.m. th[e]n fine

till ev[enin]g - rainy, windy night -

[diptanshukashyapofficial]

B-6 : Oscars 2023 - Predictions vs Reality

The 95th Academy Awards, a.k.a. The Oscars® took place today. The ceremony was full of obvious wins (and some unexpected ones too). The best part was - this year’s Oscars telecast had zero incidents (as the host Jimmy Kimmel points out in the end).

Amid all of this, here's a look at the predicted winners and the actual winners (in order of their presentations):-

Best Animated Feature Film

Prediction: Guillermo del Toro's Pinocchio (Guillermo del Toro, Mark Gustafson, Gary Ungar, and Alex Bulkley)

Reality: Guillermo del Toro's Pinocchio (Guillermo del Toro, Mark Gustafson, Gary Ungar, and Alex Bulkley)

Best Supporting Actor

Prediction: Ke Huy Quan (Everything Everywhere All at Once)

Reality: Ke Huy Quan (Everything Everywhere All at Once)

Best Supporting Actress

Prediction: Angela Bassett (Black Panther: Wakanda Forever)

Reality: Jamie Lee Kurtis (Everything Everywhere All at Once)

Best Documentary Feature Film

Prediction(s): All the Beauty and the Bloodshed (Laura Poitras, Howard Gertler, John Lyons, Nan Goldin, and Yoni Golijov)/A House Made of Splinters ( Simon Lereng Wilmont and Monica Hellström)

Reality:  Navalny (Daniel Roher, Odessa Rae, Diane Becker, Melanie Miller, and Shane Boris)

Best Live Action Short Film

Prediction: An Irish Goodbye (Tom Berkely and Ross White)

Reality: An Irish Goodbye (Tom Berkely and Ross White)

Best Cinematography

Prediction: All Quiet on the Western Front (James Friend)

Reality: All Quiet on the Western Front (James Friend)

Best Makeup & Hairstyling

Prediction: Elvis (Mark Coulier, Jason Baird, and Aldo Signoretti)

Reality: The Whale (Adrien Morot, Judy Chin, and Anne Marie Bradley)

Best Costume Designing

Prediction: Elvis (Catherine Martin)

Reality: Black Panther: Wakanda Forever (Ruth E. Carter)

Best International Feature Film

Prediction(s): All Quiet on the Western Front (Germany - Edward Berger)/Argentina, 1985 (Argentina - Santiago Mitre)

Reality: All Quiet on the Western Front (Germany - Edward Berger)

Best Documentary Short Film

Prediction(s): The Elephant Whispers (Kartiki Gonsalves and Guneet Monga)/The Martha Mitchell Effect (Anne Alvergue and Beth Levison)

Reality: The Elephant Whispers (Kartiki Gonsalves and Guneet Monga)

Best Animated Short Film

Prediction: My Year of Dicks (Sara Gunnarsdóttir and Pamela Ribon)

Reality: The Boy, the Mole, the Fox and the Horse (Charlie Mackesy and Matthew Freud)

Best Production Design

Prediction: Elvis (Production Design - Catherine Martin and Karen Murphy; Set Decoration - Bev Dunn)

Reality:  All Quiet on the Western Front (Production Design - Christian M. Goldbeck; Set Decoration - Ernestine Hipper)

Best Original Score

Prediction(s): The Banshees of Inishrein (Carter Burwell)/Babylon (Justin Hurwitz)

Reality: All Quiet on the Western Front (Volker Bertelmann)

Best Visual Effects

Prediction: Avatar: The Way of Water (Joe Letteri, Richard Baneham, Eric Saindon, and Daniel Barrett)

Reality: Avatar: The Way of Water (Joe Letteri, Richard Baneham, Eric Saindon, and Daniel Barrett)

Best Original Screenplay

Prediction(s): The Banshees of Inisherin (Martin McDonagh)/Everything Everywhere All at Once (Daniel Kwan and Daniel Scheinert)

Reality: Everything Everywhere All at Once (Daniel Kwan and Daniel Scheinert)

Best Adapted Screenplay

Prediction: Women Talking (Sarah Polley - based on the novel by Miriam Toews)

Reality: Women Talking (Sarah Polley - based on the novel by Miriam Toews)

Best Sound

Prediction: Top Gun: Maverick (Mark Weingarten, James H. Mather, Al Nelson, Chris Burdon, and Mark Taylor)

Reality: Top Gun: Maverick (Mark Weingarten, James H. Mather, Al Nelson, Chris Burdon, and Mark Taylor)

Best Original Song

Prediction: "Naatu Naatu" (RRR - Music by M. M. Keeravani; Lyrics by Chandrabose)

Reality: "Naatu Naatu" (RRR - Music by M. M. Keeravani; Lyrics by Chandrabose)

Best Film Editing

Prediction: Top Gun: Maverick (Eddie Hamilton)

Reality: Everything Everywhere All at Once (Paul Rogers)

Best Director

Prediction: Steven Spielberg (The Fabelmans)

Reality:  Daniel Kwan and Daniel Scheinert (Everything Everywhere All at Once)

Best Actor

Prediction(s): Austin Butler (Elvis)/Colin Farrell (The Banshees of Inisherin)/Brendan Fraser (The Whale)

Reality: Brendan Fraser (The Whale)

Best Actress

Prediction(s): Cate Blanchett (Tár)/Michelle Yeoh (Everything Everywhere All at Once)

Reality: Michelle Yeoh (Everything Everywhere All at Once)

Best Picture

Prediction: The Fabelmans

Reality: Everything Everywhere All at Once

Which categories met your expectations? Don’t forget to share them in the comments below.

[credenceresearchdotblog]

The Tax Management Market is projected to grow from USD 20845 million in 2024 to an estimated USD 45337 million by 2032, with a compound annual growth rate (CAGR) of 10.2% from 2024 to 2032. Tax management has emerged as a critical business function in today's globalized economy. With the rise of complex tax regulations, digital transformation, and globalization, businesses are increasingly prioritizing tax management systems to ensure compliance and optimize financial operations. The tax management market is growing rapidly, driven by the convergence of technological innovation and the ever-evolving tax landscape.

Browse the full report at https://www.credenceresearch.com/report/tax-management-market

Market Overview

The tax management market encompasses solutions and services designed to help businesses handle tax compliance, reporting, planning, and auditing. These include software solutions for income tax, goods and services tax (GST), value-added tax (VAT), and corporate tax, as well as advisory services to navigate the nuances of international taxation. In 2023, the global tax management market was valued at over USD 16 billion and is projected to grow at a compound annual growth rate (CAGR) of approximately 11% from 2024 to 2030.

Key Drivers of Growth

Increasing Complexity of Tax Regulations Governments worldwide frequently revise tax codes, requiring businesses to adapt quickly. The adoption of digital taxation systems, such as e-invoicing mandates and digital filing requirements, has added to this complexity. Businesses must implement robust tax management solutions to meet these compliance challenges.

Digital Transformation The integration of artificial intelligence (AI), blockchain, and cloud computing into tax management solutions has revolutionized the market. AI-powered analytics provide insights into tax-saving opportunities, while blockchain ensures secure and transparent transactions. Cloud-based solutions offer scalability and flexibility, especially for multinational corporations (MNCs) operating in multiple jurisdictions.

Globalization and Cross-Border Trade As companies expand globally, they face a maze of cross-border tax regulations. Effective tax management ensures compliance with international laws, preventing penalties and maintaining operational efficiency.

Adoption by Small and Medium Enterprises (SMEs) SMEs are increasingly adopting tax management solutions due to affordability and the availability of cloud-based options. These solutions help smaller organizations maintain compliance and streamline operations, even with limited resources.

Emerging Trends

Rise of Tax Technology (TaxTech) TaxTech startups are disrupting the traditional tax advisory and compliance market with innovative platforms that automate tax filing, reporting, and analytics. These technologies cater to both small businesses and large enterprises.

Environmental, Social, and Governance (ESG) Integration ESG-focused tax policies are pushing companies to track and report their sustainability-related tax benefits, such as renewable energy credits. Tax management solutions are increasingly incorporating ESG modules to address this demand.

AI and Machine Learning Applications Advanced algorithms predict tax liabilities, detect anomalies, and optimize tax planning strategies. These features reduce human error and improve decision-making.

Real-Time Tax Reporting Governments are moving towards real-time tax reporting, requiring businesses to submit tax data continuously. Tax management platforms are evolving to provide seamless integration with government systems, ensuring real-time compliance.

Challenges in the Market

Despite its rapid growth, the tax management market faces several challenges:

Regulatory Changes Constant changes in tax laws and policies make it difficult for companies to stay updated and compliant.

High Implementation Costs While cloud-based solutions are more affordable, the initial cost of implementing comprehensive tax management systems remains a barrier for smaller organizations.

Data Security Concerns With the increasing reliance on digital platforms, ensuring the security of sensitive financial data is a pressing issue. Cybersecurity measures must be robust to prevent breaches.

Limited Skilled Workforce The demand for professionals proficient in both taxation and technology exceeds the available talent pool, creating a gap in the market.

Future Outlook

The future of the tax management market is promising, with technological advancements and increasing awareness driving adoption. Governments and businesses are expected to invest heavily in digital tax infrastructure, further expanding the market.

Moreover, the rise of ESG-focused taxation and the integration of AI and blockchain are set to transform how businesses manage taxes, providing opportunities for innovation and growth. Organizations that embrace these technologies will gain a competitive edge in navigating the complexities of modern tax landscapes.

Key Player Analysis:

Automatic Data Processing

Avalara

Blucora

CrowdReason

H&R Block

Intuit

Outright

SAP

SAXTAX

Shoeboxed

Thomson Reuters

Wolters Kluwer

Segmentation:

By Component:

Software

Services

By Deployment Mode:

Cloud

On-premises

By Organization Size:

Small and Medium-sized Enterprises (SMEs)

Large Enterprises

By Tax Type:

Indirect Tax

Direct Tax

By Vertical:

Banking, Financial Services and Insurance (BFSI)

Information Technology (IT) and Telecom

Manufacturing

Energy and Utilities

Retail

Healthcare and Life Sciences

Media and Entertainment

Others

By Region

North America

U.S.

Canada

Mexico

Europe

Germany

France

U.K.

Italy

Spain

Rest of Europe

Asia Pacific

China

Japan

India

South Korea

South-east Asia

Rest of Asia Pacific

Latin America

Brazil

Argentina

Rest of Latin America

Middle East & Africa

GCC Countries

South Africa

Rest of the Middle East and Africa

Browse the full report at https://www.credenceresearch.com/report/tax-management-market

About Us:

Credence Research is committed to employee well-being and productivity. Following the COVID-19 pandemic, we have implemented a permanent work-from-home policy for all employees.

Contact:

Credence Research

Please contact us at +91 6232 49 3207

Email: sales@credenceresearch.com

[musingsofabookworm1]

My First Six Reads of Summer

This is the officially my tenth day of summer break, and I finished my sixth book yesterday. Not bad!

One Perfect Couple by Ruth Ware - This was a three-star read most of the way through, but I would rate it a three and a half overall as I did like the ending. The title of the book is nearly the name of a reality show (The Perfect Couple) that the thirty-something virologist protagonist and her younger boyfriend (wannabe actor) go on as part of an attempt to boost his pathetic acting career. The show takes place on a a brand new resort on an island in the Indian Ocean. Once there, they will compete with four other couples for a hefty cash prize. Once contestants are elminated, their partner is allowed to spend the night with any other contestant. Protagonist Lyla hopes that she can just be eliminated and boyfriend Nico can stay and win the money. Obviously for the sake of the plot, that does not happen. Things get even worse when a violent storm leaves them without power or any access to the mainland (the show took their phones). Aliances are made for survival purposes. But who will survive? Ware's writing is always fast-moving. Her protagonists are likable. This one got a little too long, but I did enjoy the end. Rounded up to four stars on Goodreads.

The House that Horror Built by Christina Henry - I had been saving this for nearly a month to be my first book of summer until the previoius book came in at the library. No matter. This was not Henry's best effort. Good characters. Good pace. Mediocre plot. Single mom Harry gets a job cleaning the mansion of a recluse. But not just any recluse: a horror film director who is hiding from the public eye after his son and wife disappeared years ago. While cleaning, Harry hears noises. She tries to ignore them but can only do so for so long. Even though this was average at best, I will eagerly await Henry's next book.

The Housemaid is Watching by Frieda McFadden - Another one I was waiting for. That I bought. But oly $4.99 on Kindle. And it wasn't even worth that. Two stars. Nothing happened for most of the book. I figured out what was going to happen and then was disappointed when that was, actually, what happened. I think I enjoyed the narration in the previous two installments of this series, but the narration annoyed me in this one. Disappointment.

Daughter of Mine by Megan Miranda - This book takes place in North Carolina during an unprecendented period with no rain. Miranda really uses rain as its classic symbolism in literature when the end arises. Protagonist Hazel returns to her small town for the sudden death and funeral of her father. As expected with any return to a small town, secrets emerge regarding Hazel's family including her long-lost mother. This book was pretty average. Fast-moving. Good dialog to prose ration. I didn't predict the entire ending. So not bad.

Chain Gang All-Stars by Nana Kwame Adjei-Brenyah - So many people I know loved this book that I couldn't wait any longer. The hold came in quickly, but it just wasn't for me. It was more character driven which always makes a had read for me. The title characters are part of gladioator-style entertainment which allow prisoners to fight to the death to win their freedom. There are a lot of characters to keep straight all with sad stories which, as a reader, you know are the stories of real people. Some of these stories are told in the footnotes: real and fictional. The footnotes slowed me down, but I was pleased with some of the new information I learned. The writing style wasn't a style I enjoy due to minimal dialog. I should have made this a DNF. But I did enjoy the very end. Two stars.

The Boy Who Loved Anne Frank by Ellen Feldman - I bought this as a cheap e-read as a number of people mentioned its worth on FB book groups I'm part of the day it was on sale. Sadly, this one ended up as three stars as well. And that was up from two stars in the first half. This book tells the story of Peter Van Pels (van Daan in the Anne Frank's famous diary and consequent play) if he survived the Holocaust. We find him married with two children in America living a comfortable suburnan life and hiding his wartime history and his Judaism. Things are going quite well until the book version of Anne's diary makes it into his own home via his wife. The first half was insanely slow. The character building was, sadly, not engaging. But the plot did pick up some in the second half. However, not enough that I'd recommend it.

[evoldir]

Fwd: Conference: Edinburgh.ComplexTraitsGenetics.Jun28

Begin forwarded message: > From: evoldir@evol.biology.mcmaster.ca > Subject: Conference: Edinburgh.ComplexTraitsGenetics.Jun28 > Date: 15 June 2024 at 05:12:47 BST > To: rdmpage@gmail.com > > > The Edinburgh-based Alliance for Complex Trait Genetics, generously > sponsored by the Genetics Society, will hold its 19th meeting on 28th > June. Details below. > > If you would like to attend please do so here: > https://ift.tt/ec1H20d > > Josephine Pemberton > > Edinburgh Alliance for Complex Trait Genetics > 19th Meeting - Friday 28th June 2024 > Royal Society of Edinburgh > 22-26 George Street, EH2 2PQ > > From  13.30 Arrival & registration > > Session 1 Chair: Smaragda Tsairidou (Global Academy of Agriculture > and Food Systems) > > 14.00 welcome > > 14.05 Athina Spiliopoulou (Usher Institute) > > Identifying core genes for complex diseases through genome-wide > aggregation of trans-effects. > > 14.30  Rongrong Zhao (Roslin Institute) > From human to cattle: Using machine learning to identify functional > variants across species > > 14.55  Luke Holman (Napier University) > Phenome-wide variation in the response to sex-specific selection in > Drosophila. > > 15.20 > Daniel Garrick > (The Helical Company Ltd and School of Agriculture and Environment > Massey University, NZ) Helical: building blocks for every step of > genomic prediction. > > 15.45 Tea and Coffee > > Session 2 Chair: > James Prendergast (Roslin Institute) > > 16.15 Lizy Mittell (Institute of Ecology and Evolution) > The missing fraction problem when measuring selection. > > 16.40  Meenu Bhati (Roslin Institute) > Impact of sex on gene expression and regulation across cattle tissues. > > 17.05 Mark Adams (Psychiatry) > From hypothesis-free to hypothesis-driven depression genetics. > > 17.30  Drinks and nibbles. > > The University of Edinburgh is a charitable body, registered in Scotland, > with registration number SC005336. Is e buidheann carthannais a th' > ann anOilthigh Dhùn Èideann, clàraichte an Alba, àireamh clàraidh > SC005336. > via Email June 15, 2024 at 06:32AM

[govindhtech]

Define machine learning: 5 machine learning types to know

Machine learning (ML) can be used in computer vision, large language models (LLMs), speech recognition, self-driving cars, and many more use cases to make decisions in healthcare, human resources, finance, and other areas.

However, ML’s rise is complicated. ML validation and training datasets are generally aggregated by humans, who are biased and error-prone. Even if an ML model isn’t biased or erroneous, using it incorrectly can cause harm.

Diversifying enterprise AI and ML usage can help preserve a competitive edge. Distinct ML algorithms have distinct benefits and capabilities that teams can use for different jobs. IBM will cover the five main categories and their uses.

Define machine learning

ML is a computer science, data science, and AI subset that lets computers learn and improve from data without programming.

ML models optimize performance utilizing algorithms and statistical models that deploy jobs based on data patterns and inferences. Thus, ML predicts an output using input data and updates outputs as new data becomes available.

Machine learning algorithms recommend products based on purchasing history on retail websites. IBM, Amazon, Google, Meta, and Netflix use ANNs to make tailored suggestions on their e-commerce platforms. Retailers utilize chat bots, virtual assistants, ML, and NLP to automate shopping experiences.

Machine learning types

Supervised, unsupervised, semi-supervised, self-supervised, and reinforcement machine learning algorithms exist.

1.Supervised machine learning

Supervised machine learning trains the model on a labeled dataset with the target or outcome variable known. Data scientists constructing a tornado predicting model might enter date, location, temperature, wind flow patterns, and more, and the output would be the actual tornado activity for those days.

Several algorithms are employed in supervised learning for risk assessment, image identification, predictive analytics, and fraud detection.

Regression algorithms predict output values by discovering linear correlations between actual or continuous quantities (e.g., income, temperature). Regression methods include linear regression, random forest, gradient boosting, and others.

Labeling input data allows classification algorithms to predict categorical output variables (e.g., “junk” or “not junk”). Logistic regression, k-nearest neighbors, and SVMs are classification algorithms.

Naïve Bayes classifiers enable huge dataset classification. They’re part of generative learning algorithms that model class or category input distribution. Decision trees in Naïve Bayes algorithms support regression and classification techniques.

Neural networks, with many linked processing nodes, replicate the human brain and can do natural language translation, picture recognition, speech recognition, and image generation.

Random forest methods combine decision tree results to predict a value or category.

2. Unsupervised machine learning

Apriori, Gaussian Mixture Models (GMMs), and principal component analysis (PCA) use unlabeled datasets to make inferences, enabling exploratory data analysis, pattern detection, and predictive modeling.

Cluster analysis is the most frequent unsupervised learning method, which groups data points by value similarity for customer segmentation and anomaly detection. Association algorithms help data scientists visualize and reduce dimensionality by identifying associations between data objects in huge databases.

K-means clustering organizes data points by size and granularity, clustering those closest to a centroid under the same category. Market, document, picture, and compression segmentation use K-means clustering.

Hierarchical clustering includes agglomerative clustering, where data points are isolated into groups and then merged iteratively based on similarity until one cluster remains, and divisive clustering, where a single data cluster is divided by data point differences.

Probabilistic clustering group’s data points by distribution likelihood to tackle density estimation or “soft” clustering problems.

Often, unsupervised ML models power “customers who bought this also bought…” recommendation systems.

3. Self-supervised machine learning

Self-supervised learning (SSL) lets models train on unlabeled data instead of enormous annotated and labeled datasets. SSL algorithms, also known as predictive or pretext learning algorithms automatically classify and solve unsupervised problems by learning one portion of the input from another. Computer vision and NLP require enormous amounts of labeled training data to train models, making these methods usable.

4. Reinforcement learning

Dynamic programming dubbed reinforcement learning from human feedback (RLHF) trains algorithms using reward and punishment. To use reinforcement learning, an agent acts in a given environment to achieve a goal. The agent is rewarded or penalized based on a measure (usually points) to encourage good behavior and discourage negative behavior. Repetition teaches the agent the optimum methods.

Video games often use reinforcement learning techniques to teach robots human tasks.

5. Semi-supervised learning

The fifth machine learning method combines supervised and unsupervised learning.

Semi-supervised learning algorithms learn from a small labeled dataset and a large unlabeled dataset because the labeled data guides the learning process. A semi-supervised learning algorithm may find data clusters using unsupervised learning and label them using supervised learning.

Semi-supervised machine learning uses generative adversarial networks (GANs) to produce unlabeled data by training two neural networks.

ML models can gain insights from company data, but their vulnerability to human/data bias makes ethical AI practices essential.

Manage multiple ML models with watstonx.ai.

Whether they employ AI or not, most people use machine learning, from developers to users to regulators. Adoption of ML technology is rising. Global machine learning market was USD 19 billion in 2022 and is predicted to reach USD 188 billion by 2030 (a CAGR of almost 37%).

The size of ML usage and its expanding business effect make understanding AI and ML technologies a key commitment that requires continuous monitoring and appropriate adjustments as technologies improve. IBM Watsonx.AI Studio simplifies ML algorithm and process management for developers.

IBM Watsonx.ai, part of the IBM Watsonx AI and data platform, leverages generative AI and a modern business studio to train, validate, tune, and deploy AI models faster and with less data. Advanced data production and classification features from Watsonx.ai enable enterprises optimize real-world AI performance with data insights.

In the age of data explosion, AI and machine learning are essential to corporate operations, tech innovation, and competition. However, as new pillars of modern society, they offer an opportunity to diversify company IT infrastructures and create technologies that help enterprises and their customers.

Read more on Govindhtech.com

[doyouknowthisbook-poll]

FINAL RESULT: The majority of voters have read this book before and like it! 💖

Anne of Green Gables is a 1908 novel by Canadian author Lucy Maud Montgomery (published as L. M. Montgomery). Written for all ages, it has been considered a classic children's novel since the mid-20th century. From Wikipedia: “Set in the late 19th century, the novel recounts the adventures of 11-year-old orphan girl Anne Shirley sent by mistake to two middle-aged siblings, Matthew and Marilla Cuthbert, who had originally intended to adopt a boy to help them on their farm in the fictional town of Avonlea in Prince Edward Island, Canada. The novel recounts how Anne makes her way through life with the Cuthberts, in school, and within the town.

In writing the novel, Montgomery was inspired by notes she had made as a young girl about two siblings who were mistakenly sent an orphan girl instead of the boy they had requested, yet decided to keep her. She drew upon her own childhood experiences in rural Prince Edward Island, Canada. Montgomery was inspired by the ‘formula Ann’ orphan stories (called such because they followed such a predictable formula) that were popular at the time, but distinguished her character by spelling her name with an extra ‘e’.

Since its publication, Anne of Green Gables has been translated into at least 36 languages and has sold more than 50 million copies, making it one of the best-selling books worldwide. It was the first of many novels; Montgomery wrote numerous sequels, and since her death another sequel has been published, as well as an authorized prequel titled Before Green Gables. This prequel was written in 2008 by Budge Wilson to celebrate the 100th anniversary of the book series. The original book is taught to students around the world.

The book has been adapted as films, television films, and animated and live-action television series. Musicals and plays have also been created, with productions annually in Canada, Europe and Japan.”

Do you know which book this is from?

Please reblog the polls, but KEEP IT SPOILER-FREE to make people read the excerpt with an open mind 💖📚 Title and author will be revealed after the poll's conclusion.