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asoulunbound · 6 months

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M Y T H O L O G Y

Amphitrite(hc based / nereid / pinar deniz fc / bisexual)

Perses(hc based / titan / daniel henney fc/ straight)

Peitho(hc based / oceanide / aubrey plaza fc/ pansexual polyamorous)

Hecate(hc based / titaness / anya charlotra fc/ ace)

Mnemosyne(hc based / titaness / sarah pauslon fc/ pansexual)

Crius(hc based / titan / danny pino fc / straight)

Epimetheus(hc based / titan / daniel brühl fc/ bisexual)

Iaptus(hc based / titan / karl urban fc/ straight)

Astraeus(hc based / titan / rege-jean page fc/ pansexual)

Arke(hc based / goddess / tashi rodrigues fc / bisexual)

Menoetius(hc based / titan / tom hardy fc/ demi)

Leto(hc based / titaness / loreen talhaoui fc/ demi)

Phoebe (hc based / titaness / caitríona balfe fc/ pansexual)

Theia(hc based / titaness / sarah rafferty fc/ bisexual)

Hephaestus(hc based / olympian / andreas pietschmann fc/ pansexual)

Cronus(hc based / titan / lee pace / pansexual)

A S O N G O F I C E A N D F I R E

Petyr ‘Littelfinger’ Baelish(book canon / human / aiden gillen fc / straight)

Varys (book canon / human / conleth hill fc / ace)

Sarella/Alleras Sand (book canon / human / undefined fc / gay)

Val (book canon / human / jeanne goursaud fc / bisexual)

Laena Velaryon (book & show canon / human / nanna bondell fc / bisexual)

Larys Strong (book & show canon / human / matthew needham fc / straight)

Visenya Targaryen I(book canon / human / katheryn winnick fc / bisexual polyamorous)

Sandor Clegane (book & show canon / human / rory mccann fc / straight)

Jonquil Darke (book canon / human / phoebe tonkin fc/ gay)

Anrea Hightower (OC / human / been saat fc/ straight)

Brynden Rivers (book canon / human / undefined fc / bisexual)

Tyanna of the Tower (book canon / human / eva green / bisexual)

Mysaria (book & show canon / human / Sonya mizuno / bisexual)

Qyburn (book & show canon / human / anton lesser / ace)

K I N N P O R S C H E

Macau Theerapanyakul(show canon / human / ta nannakun fc / bisexual)

Kim Theerapanyakul (show canon / human / jeff satur fc / pansexual)

Porsche Kittisawasd(show canon / human / apo nattwin fc / bisexual)

Smile Busarakham (OC / human / fah yongwaree fc / gay)

Tawan (show canon / human / na naphat fc / gay)

M A V E L / X-M E N

The Vision(mcu canon / synthezoid / paul bettany fc / demi)

Emma Frost(comic canon / mutant / vanessa kirby fc / bisexual)

X-23/Laura Kinney(comic canon / mutant clone / esme creed miles fc / bisexual)

Kwannon/Pyslocke(comic canon / mutant / anna sawai fc / bisexual)

Mastermind(comic canon / mutant / penn badgley / straight)

Valeria Richards(comic canon / human / elle fanning / pansexual)

Sonya Falsworth(mcu canon / human / olivia colman / straight)

B R I D G E R T O N

Edwina Sharma(show canon / human / charithra chandran fc / bisexual)

Benedict Bridgerton (show canon / human / luke thompson fc / bisexual)

Eloise Bridgerton(show canon / human / claudia Jessie / bisexual)

D U N E

Alia Atreides(book canon / human / sofia boutella fc / pansexual)

Gurney Halleck(book canon / human / josh brolin fc / pansexual)

Margot Fenring(book canon / human / lea seydoux fc / pansexual)

J A M E S B O N D

Q(film canon / human / ben whishaw fc / gay)

R(hc based / human / charlotte nicdao fc / bisexual)

Alec Trevelyan(hc based / human / taron egerton fc / bisexual)

T H E W H E E L O F T I M E

Elaida do Avriny a'Roihan(book canon / aes sedai / lara pulver fc / gay)

Siuan Sanche(book canon / aes sedai / sophie okonedo fc / bisexual)

Moiraine Damodred(book canon / aes sedai / rosamund pike fc / bisexual)

C R I M I N A L M I N D S

Penelope Garcia (show canon/ BAU special agent/ kristen vangsness / straight)

Dr. Spencer Reid (show canon / BAU special agent / matthey grey gubler / bisexual)

#&& out of cookies (ooc)

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lilibetts · 4 years

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The Wicked Forest Awaits You...

For Tricks and Treats of Riverdale, Theme 3: Seasonal Celebrations (Haunted House)

Rated E(xplicit) for some wicked fun!

Darkness falls across the land The midnight hour is close at hand Creatures crawl in search of blood To terrorize y'all's neighborhood And whosoever shall be found Without the soul for getting down Must stand and face the hounds of hell And rot inside a corpse's shell

I'm gonna thrill ya tonight I'm gonna thrill ya tonight Ooh, babe I'm gonna thrill ya tonight

The Wicked Forest was reportedly “the most un-hinged haunted attraction in Riverdale”.

Betty had shown up as soon as the sun went down, and she still spent an hour waiting in line. Alone, of course. Every one of her friends would rather spend Halloween getting drunk at an off-campus party than indulging in the spooky atmosphere. Granted, she hadn’t actually told anyone where she would be going tonight, because the Wicked Forest was firmly in the Southside and as much as some people in the Northside liked to brag or bluster, very few had the guts to actually cross the boundary lines.

That she had gave Betty an illicit thrill.

This year, she’d dressed up as a zombie schoolgirl: hair spray painted gray in a side ponytail to match her torn, bloody white blouse and desaturated gray plaid miniskirt. The face makeup was the most fun to apply, all those Youtube tutorials coming in handy. Gray foundation to give herself a deathly pallor on all expanses of exposed skin, black raccoon eyes, fleshy red ‘gouges’ on the side of her face, and dark red lipstick.

She wondered what her friends would think if they knew she was actually dressing sexy for once. They probably wouldn’t believe it.

A haunted house on Halloween was hardly the place to pick up a date, but for Betty, who had been gradually building up her confidence to sign up for Tinder, wearing knee-high white socks and no underwear made her feel like a bold, sexy woman.

“Betty?” a familiar baritone called out from behind her. She turned around and a guy she didn’t immediately recognize waved at her. “Hey.”

Squinting, she took in the mop of black hair and the slim body in a black-and-white skeleton shirt, leather jacket, black jeans and boots, and the skeleton face paint. “Jughead? Is that you? You look amazing!”

“Thanks. So do you.”

Jughead Jones had shared a few classes with her over the past two years. At first, Betty had found him and his voice annoying. She couldn’t be sure at what point over the past two years her feelings had evolved into a massive, uncontrollable crush. Naturally, in true Betty Cooper fashion, she didn’t have the guts to try and make a move and would rather throw herself into the vicissitudes of online hookups.

Jughead ran a hand covered in fingerless gloves through his hair. “Do you want to go through together?”

“Sure!” She could’ve kicked herself for her bobblehead impersonation then. “So have you gone through this one before?”

“Twice as a guest, but I’ve worked it several times as well.”

“Really? What kind of characters did you play?”

“I did mostly forest work—a Jason Vorhees/Leatherface composite type with a hockey mask and chainsaw. One year I got to be a werewolf.” Jughead sounded more bashful than proud when he admitted that.

“I bet it was fun...I prefer to be on the receiving end of scares, though.”

“Unless it’s one of Chipping’s essay prompts,” he quipped.

Betty groaned and smacked his arm. “Don’t remind me. The last one was so stupid, wasn’t it? ‘Write your own ending to prove there’s no single way to tell a story...but’—”

“—’but I’m still going to pick a winner in the end!’” they both chorused, laughing at their shared derision.

After that they were quickly engrossed in a debate about the best Halloween movies to watch during the buildup to the holiday. Jughead’s preferences ran more towards the older classics and Hitchcock, Betty’s more towards relatively recent films like Hocus Pocus, The Addams Family, and Practical Magic.

Oddly enough, she discovered they both loved the cult hit Ginger Snaps.

By the time they were at the head of the line, Betty was sure her blush was showing through the heavy makeup.

The general order of the Wicked Forest went like this: haunted house, a maze that led to the shed, a bridge over the creek, then the forest proper.

The baseboards creaked as they crossed into the dilapidated house; maniacal laughter and screams could be heard faintly in the distance. A ghostly apparition dressed like a long-dead bride lit up in the corner of the living room, moaning as its arm raised, pointing a finger at them. Betty gasped and hugged the wall as she moved into the kitchen, Jughead following close by.

Smoky fog covered the floor, pouring from cauldrons. Made from dry ice, probably, and lit up by green lights. A witch cackled as she stirred her brew. In the corners, cages descended from the ceiling, people in them reaching out and begging for help.

She shared a wide smile with Jughead.

In the bathroom, they found a bloated dead body with red hair, dressed in all white, floating in the tub. “Disturbingly realistic,” Betty muttered to herself. In the dining room, a young woman was suspended up on the wall with long knives sticking out of her body. ‘All those who escaped me before will die’ was scrawled in blood around her body.

“I think she was in our English class last year,” Jughead whispered to Betty, her stomach queasy from the excitement.

They were herded into the basement, where they discovered that in order to get to the other side, they would have to go through a gauntlet of secret society members in dark hooded robes. A red carpet highlighted their path. After they’d taken a few steps past the first hooded figures, they all stepped forward, giving Betty and Jughead less space to escape. As if reading each other’s minds they moved faster, only for the hooded figures to step closer and closer.

One jumped into their path, exposing a Scream mask. Betty was not at all mortified by her little yelp of fright. Not at all.

From there, they were in a cool cellar with a dimly lit tunnel rising up to ground level outside. Cobwebs covered the top and sides and as soon as she spotted the giant spider on top, she had a feeling she knew what was coming. Sure enough, as soon as they passed underneath, the spider dropped onto their heads. Betty shrieked and ran the rest of the way through.

“Oh my god, oh my god!”

Jughead was clearly laughing at her expense as they emerged outside. “What, are you scared of spiders, Cooper?” he teased her.

“Shut it, Jones.” She snapped back without heat. “Why are you even going through the attraction if it bores you?”

“Oh, it’s never boring. Maybe I’m just enjoying it more with you.”

She felt like she was back in sixth grade again. Should she pass him a note asking ‘do you like-like me? Circle y/n’?

Betty was grateful for the absurdly long lead time in between guests. It meant she wasn’t running into the group ahead or the group behind, like in most other haunted attractions she’d attended over the years.

As they entered the shed, the walls and floor tilted, disorienting her. Then Jughead was there, hand slipping into hers as he helped guide her to more even ground. Even after the floorboards started vibrating underneath them, neither let go of the other. Betty laughed with delight as they pushed through the heavy plastic curtains into an open space occupied by a scene out of a medical horror: a conscious, moaning woman was strapped down on a gurney while a man in a bloody doctor’s mask and lab coat performed what looked like a lobotomy on her, bits of brain matter leaking outside her head. Her chest was held open by a spreader, the bloody mass of her internal organs on display.

“Ew, ew, ew!” Betty stomped her feet and pushed Jughead onwards faster. “Too real!”

The trees pressed in on them more as the manmade pathway guided them to the small bridge that would take them across the creek and into the thick of the forest. Part of the way across, a small golden light came on in the distance, drawing her attention to the side. A hulking body unfolded itself before howling at the night sky above.

Betty didn’t realize Jughead was right behind her until her back was pressed into his front and his hands gripped her hips. She turned her head without taking her eyes off the werewolf. “Your old job?”

“Yeah, me and Fangs used to partner during this bit.”

“Partner?”

A dark shape darted in between the bridge railings, grabbing at her ankles. Jughead’s giggles were almost as loud next to her ear as her startled shrieks before she took off to the other side. She had to remind herself to breathe deeply and calm herself down while they moved on.

Maybe it was the near pitch black of the forest that made her brave, but Betty reached out and slid her hand back in Jughead’s. They shared shy smiles that made hope bloom inside her.

There was a decrepit school bus sitting right there in the middle of the trees. Not sinister at all. Jughead made a gallant ‘after you’ motion, sweeping low with his bow. Betty fanned herself and simpered, “such a gentleman!”

“Nonsense! I’m merely ensuing you die first, my dear.” His upper crust British accent was atrocious.

“You sounded like Niles Crane from Frasier.”

She forced herself to stop snickering as she stepped up into the bus. At first glance, all the people in the seats were dead or otherwise inanimate. Carefully, she made her way down the narrow aisle, hugging her arms to herself in anticipation of the movement she knew must be com—

“AH! FUCK!”

Betty twisted around and saw Jughead pressed up against seats opposite a softly hooting ghoul still reaching out for him with gnarled fingers.

At the front, a burly man wearing a black balaclava stood up suddenly, facing them with an enormous, shiny knife. The momentary relief on Jughead’s face morphed to fear and Betty didn’t have to be told twice as they booked it out of the bus, one more monstrous figure trying to impede their progress.

“So much for the unflappable Jughead Jones,” she started after they caught their breath and made sure the man in the black hood wasn’t following them any longer.

“Har har, I am humbled.”

After that point, the path became increasingly bumpy and overgrown and Betty couldn’t see well enough to stop herself from lurching to and fro. Jughead was right there by her side, using his arm around her waist to keep her from face-planting in the dirt. Given that she was wearing low block heels, she had no idea how some of the other guests were doing this in three inch stilettos.

Maybe it was their surroundings, maybe it was Jughead’s touch that was responsible for her heart continuing to pound wildly. Branches closed in on them before they exited into a small clearing. A fire roared in a pit, the sudden brightness making her eyes hurt and eclipsing what was happening along the treeline.

“Whoa,” Jughead murmured, alarmed, causing her to squint harder.

People had stepped into the firelight, wearing dark hooded sweatshirts and gray gargoyle masks. Growling could be heard behind them and when Betty and Jughead turned, an inhumanely tall figure stepped around the bushes, with a long robe, some kind of blooded animal skull mask with horns, branches for wings, and a necklace of bones.

The minions stepped closer, closing ranks menacingly. This time, it was Jughead who grabbed her hand and tugged her past the leader and the wooden placard that proclaimed that the creature was the Gargoyle King, and back into the dark forest.

They stumbled along for another minute before Jughead muttered something to himself that sounded vaguely like “ah, fuck it”.

He led her over to the rope boundary that made up the path and stepped over it.

“What are you doing?”

“Shh! I know this place like the back of my hand. It’s just the lame clown shit ahead. Do you trust me?”

Betty didn’t know about trust, but she was totally down for whatever they might get up to out there. Alone. “Hmm-mm,” she nodded and stepped carefully over the rope too. Together they made their way down a slope and around a cluster of bushes.

She found herself pressed back against a thick tree trunk, warm lips on hers, and the sounds of excited screams nearby reminding her that they weren’t alone. Betty raised up onto her tiptoes and pulled Jughead closer as she kissed him all the more eagerly.

The heat of his hands could be felt through her shirt while he cupped her breasts, making her tilt her head back to moan.

“Shhh,” he whispered softly this time before dotting soft kisses along her neck.

Their face makeup must be horribly messed up by now but Betty didn’t care. She wanted to take him back to her dorm room, or go to his, and do all the wicked things she’d been fantasizing about.

A little exhibitionism was fun, though.

By the time Jughead slipped his hands underneath her skirt and discovered her little secret, she was incredibly wet. Wet enough for him to let out a quiet expletive and a shuddering sigh as his fingers glided along her inner lips. He quickly removed his glove and slid two up into her, stroking slowly before rubbing steady circles over her clit. Back and forth he went, until she was groaning and bucking her hips against his hand as she came embarrassingly fast.

Apparently haunted houses make for excellent foreplay.

Reaching for the button of his jeans,Betty ignored his protests of “you don’t have to”. It was her turn to shush him as she lowered herself onto her knees and took him into her mouth, swirling her tongue around the head of his shaft to get him nice and wet. Jughead did his best to not thrust into her mouth and his panting breaths were harsh in the relative silence of the night. He lost control towards the end, she could feel him shaking as his hips canted forward and salty wetness burst onto her tongue.

Veronica was definitely not going to believe her when she told her what she’d done tonight.

They held hands and grinned broadly as they rejoined the path behind another group. When a tall, demented clown caught sight of them in the intense blue light, he groaned and ripped off his mask. “You’ve got to be kidding me, Jones? Were you two fucking off-path? Fucking seriously?”

Jughead only offered his friend a careless shrug. “Hey Sweets, how’s tricks?”

Betty, however, pressed closer against his side and smiled serenely up at the taller man. “Because I’ve already gotten the treat.”

‘Sweets’ groaned at the pun and waved them on. “Just get out of my forest, you freaks.”

They snickered as they made it to the end where a flatbed full of bales of hay was hooked up to a tractor, waiting to take them back around to the entrance. Jughead glanced over at her then, and Betty had to bite back another laugh. His makeup pretty much announced to everyone what they’d been up to, but she couldn’t bring herself to care.

Orgasms and finally hooking up with your crush would do that.

“So, would it be too weird for me to ask if you wanted to go out to lunch with me this weekend?”

(His answer was an immediate and resounding yes.)

#bughead #bughead fanfiction #riverdaleevents #avarosier writes

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marylandparanormal · 6 years

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Exploring Phantasms of the Living (1886) through Machine Learning: Presentiment, Crisis Apparitions and Thought Transference

NOTE: Click to open graphics for an expanded and clearer view of the findings they contain

Phantasms of the Living, published in 1886 by the Society for Psychical Research (SPR), was a landmark ESP study that presented the case for “telepathy" or thought transference from mind to mind. The study consisted of 702 cases spanning over 1400 pages that considered several varieties of telepathic experiences collectively referred to as “phantasms of the living”

The case collection examined non-sensory and internalized impressions, many of which were presentiment experiences involving dreams, clairvoyance, visions, feelings or an awareness in connection with the deaths of family members or friends. These experiences often coincided with the approximate time of death

Cases also considered sensory and externalized impressions, in particular apparitional representations of living persons, who were perceived to be in moments of crisis or danger. These situations appeared evidential of shock-induced forms of thought transference from a distressed agent to a percipient in the form of telepathic hallucinations

As a follow-on to the earlier wordcloud project, we wondered whether unsupervised machine learning could discover main topics within Phantasms of the Living. For the project, two varieties of generative topic models were used: Latent Dirichlet Allocation (LDA) and probabilistic Latent Semantic Analysis (pLSA)

Both models view documents as having a latent semantic structure of topics that can be inferred from co-occurrences of words in documents. The mathematics underlying both models are beyond the scope of this post, but on an intuitive level there are key differences between the two methods

pLSA views topics as probability distributions over words. Topics are seen as conditionally independent across the documents that produced them. Non-Negative Matrix Factorization (NMF) is a method for finding topic clusters that equates to pLSA

LDA by contrast views documents as probability distributions over topics and topics as probability distributions over words. All documents share the same collection of topics, but each document contains those topics in different proportions. The LDA algorithm samples words across topics until it arrives at topics and word selections that most likely generated the documents

The project used various packages and libraries for natural language processing within the Python programming platform to include: the Natural Language ToolKit (NLTK) for processing the data set; scikit-learn to prepare and fit the LDA and NMF models; pyLDAvis was used to display the results and t-Distributed Stochastic Neighbor Embedding (t-SNE) to map topic distances

The end-to-end project pipeline involved: data set processing; conversion of words and documents into matrix and vector space; fitting the LDA and NMF models; and then displaying the results

Processing. The book was decomposed into several documents from its constituent sections, chapters and volumes for the data set. Stopwords were removed such as common prepositions and conjunctions using the wordcloud application

Since telepathic experiences are spontaneous and can occur at any time or place, words conveying times and locations were removed as well as ordinal and cardinal types of numeric rankings

Nouns or titles representing persons were removed (e.g. man, woman, Mr., Mrs., etc.); however, interpersonal relationships were preserved (i.e. family, friends, acquaintances or strangers)

Conversion. Vector transformations converted the data set into a document-term matrix for mathematical processing

The rows of the matrix correspond to documents with columns corresponding to the frequency of a term. Count vectorizers count word frequencies. Term Frequency-Inverse Document Frequency (TF-IDF) vectorizers normalize (divide) word counts by their frequency in the documents

Both vectorizers converted words to lower case and removed non-word expressions. The vectorizers were also instructed to look for bigrams (or words that were often used together) such as "thought-transference" and "telepathic hallucination"

Model Fit/Display. The LDA and NMF models were fitted using ten topics. Words within topics were sorted and ranked with respect to their frequency in and relevance within a topic

The LDA model was fitted with using Count and TF-IDF vectorization and ran with a maximum of 10 iterations. LDA model results were displayed using pyLDAvis and t-SNE to map topic distances

The NMF model was fitted with TF-IDF vectorization only and ran with a maximum of 200 iterations. NMF model results were displayed via spreadsheet

Results. The topics produced from the models are unlabeled. However words within topics often can be woven into a coherent theme

The first two pyLDAvis graphs provide the top 30 words and bigrams in Topics 1 and 2 using Count vectorization

Words in Topic 1 include: “dreams”; “visions”; “impressions”; and “experiences” in connection with the “death”(s) of family members and friends. This can be considered a presentiment topic and it generated 67% of the content. This mirrors results from the prior wordcloud project

Words and bigrams in Topic 2 include: “thought-transference”, “hallucination(s)”, “phantasms”, “mind(s)”, “percipients”, “agent” and “telepathy.” This can be considered a telepathic hallucinations topic and it produced 27% of the content

The third pyLDAvis graph provides the top 30 words in Topic 1 using TF-IDF vectorization

Topic 1 combines all the aforementioned words into one topic. This can be considered a “presentiment and telepathic hallucinations ” topic and it accounts for 95% of the content, rendering all other topics practically insignificant in influence. The reason for this consolidation is that TF-IDF vectorization lowers the contribution weight of commonly used words

The spreadsheets compare LDA and NMF model runs using TF-IDF vectorizations with results limited to the top 10 words. Although topic weights and distances are not available, some topics appear more meaningful and cohesive, and are likely more impactful than others

There is overlap between topics 5 and 6 in the LDA model and together they form the presentiment and telepathic hallucinations topic. Topics 0 and 1 in the NMF model respectively appear to correspond to presentiment and crisis apparitions topics

The bigram “thought-transference” arises in both the LDA and NMF results and appears associated with the “Society” for “Psychical” Research and the late F.W.H. “Myers” who invented the term “telepathy”

This project had an extended preparation and production pipeline. The results indicate that unsupervised machine learning using LDA and NMF effectively and comprehensively summarized topical content in Phantasms of the Living. Moreover, key topics approximately corresponded to the types of internalized and externalized telepathic experiences described in the book

This project demonstrates the usefulness of topic generation models for finding meaningful patterns in masses of unlabeled or unstructured data. Moreover, visualization and graphing tools are essential for fully comprehending these patterns. Elsewhere in parapsychology LDA or NMF could also be applied to survey data, case collections, web or social media content of interest.

REFERENCES

Anaya, L. A. Comparing Latent Dirichlet Allocation and Latent Semantic Analysis as Classifiers. University of North Texas, 2011.

Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent dirichlet allocation. Journal of machine Learning research, 3(Jan), 993-1022.

Christou, D. (2016). Feature extraction using Latent Dirichlet Allocation and Neural Networks: A case study on movie synopses. arXiv preprint arXiv:1604.01272.

Deerwester, S. (1988). Improving information retrieval with latent semantic indexing.

Gurney, E., Myers, F. W., & Podmore, F. (1886). Phantasms of the Living (2 vols.). London: Trübner. Reprinted at the Esalen Center.

Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., ... & Vanderplas, J. (2011). Scikit-learn: Machine learning in Python. Journal of machine learning research, 12(Oct), 2825-2830.

Sievert, C., & Shirley, K. (2014). LDAvis: A method for visualizing and interpreting topics. In Proceedings of the workshop on interactive language learning, visualization, and interfaces (pp. 63-70).

IMAGES

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