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miyukihoshizora · 9 months

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So! FFVIII! Finished it yesterday, loved most of the last stretch! And it totally comes appart the second you think about it too hard!

First what I liked:

Squall and Rinoa, obviously. Their dynamic and respective growths mirroring each other. One who shuts off the world and one who forces herself to seem like this dizzy social butterfly, both because they are terrified of being hated. Their friendship very organically evolve into a romance and the best scenes in the game like the space rescue are always between these two.

Quistis was also the teammate I felt got to do the most. Started off as a mentor, before realizing the mantle of leader was not for her and learning to put her full trust into something other than her instincts. She also had the emotional intelligence to dodge a love triangle when she felt that shit arrive lmao.

The game is also full of really cool setpieces in general. The space rescue, the Gardens themselves, the Lunatic Pandora... And of course, Ultimecia's castle! I absolutely loved the whole dream sequence at the end, how it communicated without words on all of Squall's fears and how Rinoa became the reason he learned to enjoy his life. How he clung to her image like a lifeline even if the time distortion + GF poisoning tried to take it away from him (as it did with Ultimecia if you subscribe to the U=R theory). Like god damn, this was strong stuff.

Speaking of! I'm actually shocked Ultimecia being Rinoa is just a fan theory Square went out of their way to debunk because it seemed so obvious to me from the get go and I wasn't even aware of the theory until I looked into it. I find it weird they decided to just say no to the whole thing instead of keeping it ambiguous, as the game does, because thematically, this makes it a really powerful story, and Ultimecia a much more sympathetic baddie. Like damn, you can do so much with Griever being all she has left of her knight, while her refusal to let go of it twisting her memories to the point she can no longer recognize him when he comes to her from the past, as she wanted. Respectfully gonna kill the author on this one.

Now for the less good stuff... The orphanage plot twist, obviously. Doctor Odine's whole deal. The Norg stuff. I imagine the fact this plot is held together by duct tape is like, the popular opinion at this point. The best parts of this game kind of mostly work in a vacuum.

Also, well... Zell, Irvine and Selphie don't really have any arc to speak of as far as I can tell. Which is a bit disappointing, compared to VII, I wish they all got to do a lot more. They are still my babies but I really didn't care for them as much as I did the other three, and that Is a problem in a seried that lives or die by how much you engage with its characters.

Oh and bro, Seifer. I jokingly compared him to Draco Malfoy and just like Draco they totally half assed his part in the plot. He had strong momentum as a rival character in Disc 1, but the fact Rinoa stops having feeling for him the second he does his heel turn, and that he just wanted to be Ultimecia's knight, regardless of whether it was Edea or Rinoa, TWO WOMEN HE LOVED, is completely ridiculous. He also got a total anticlimax with the most heavy-handed Gilgamesh cameo, and then Fujin and Raijin (the best part of this stupid plot thread) just redeem him off screen where he goes back to Balamb and never gets any comeuppance for actively trying to destroy the world, like, what the hell even was that.

Oh yeah also the gameplay system is jank and I only started having fun with it when I broke it.

That about sums up my thoughts. I'm really happy of my experience with this game, and to finally be done with the Playstation era!~

My X replay is next, and then I'll probably hop straight onto XV.

#puri gaming;#arz plays viii;

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heyitsyn · 4 years

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Keeping Up With Seijoh Ep. 4

a/n: uwuwuwuwu @animesportboys and i were just talking about this and my heart was just bursting at this thought 😭

for more seijoh content, check this masterlist out!

also requests are currently closed right now since i have like nearly 30 to finish so please be patient with me and wait for me to finish it all and until then i can open them up again. however, dont stop sending me cute stuff okay? 🥺

summary: its the time of the month for seijoh’s manager 🥺

@ yn when shes extra moody and mean during that time and does this every time she hears anything even come out of the boys’ mouth

oh dear

so basically

it’s,,,,,, a natural thing that most girls go through every month for more than half of their lives and its absolutely D R E A D F U L

the boys ofc knew what the hell a period was bc hello health class so they knew you would become this,,, other version of yourself

youd be moodier, childish, and easy to annoy and snap to everyone

but you would quickly realize how you’re acting then be all regretful and teary and cry easily and then youd forget about it then start the cycle again

you’d stick your tongue out at them and tease them mercilessly, making them run even more laps and pushing them harder

‘I SEE THOSE ARMS SHAKING, IWAIZUMI HAJIME. ADD 15 MORE TO THAT ROUTINE’

‘WHAT?!’

‘IF I SEE YOU EVEN A STEP BEHIND KINDAICHI, YOU WILL BE RUNNING 8 MORE LAPS KUNIMI’

‘NOO!!!!’

‘CHECK YOURSELF OUT ONE MORE TIME, YAHABA, I WILL GOUGE OUT YOUR EYES’

‘HAVE MERCY!!!!’

dear god they hated it

when it was time, they would protect themselves and work even harder and be more perfect to make sure you couldnt see their faults and point them out and try and kill them

it was like war for everyone

but they didnt know the exact date it started so they didnt really know when to start preparing for war until it came

this time, you didnt either

you didnt even know you were starting as you were extra busy booking the buses for away comps and collecting and emailing teachers for any missed homeworks for the team

so when it did start,,,

oh dear part 2

it wasnt really something you found out when you woke up that morning but you noticed you must be getting close since you were feeling extra cranky and you havent even been awake for more than an hour

nothing really happened throughout the day so you were just thinking that you didnt get enough sleep last night so you were just tired and wanted to sleep

but then it happened

you were standing next to iwa, reviewing his spike percentages when you shifted your weight to the other leg and then your eyes widened

your water broke

i saw this tiktok of this one girl and she was about to start filming with her friend when her eyes widened and her friend knew immediately and her caption was ‘my water broke’

iwa was worried as heck on to what was going on with you and even followed your gaze to see it on the wall and nothing out of the ordinary

‘y/n?’

‘oh god’

you mumbled and you wanted to run but you were too scared that you leaked and probably have an obvious redness on your white track pants

yep it def was your time bc you felt tears welling up in your eyes and you sniffled, embarrassed and upset for this to happen now, of all times

then oikawa tooru bursted through the doors

iwa, taking his eyes off of you and to the captain, started to yell at him until he noticed the brunette’s flushed face and panting form, hunched over as he gripped on the door handle with the plastic bag

you, too busy trying to think of a way to get out of there like deciding to waddle or to just crawl, didnt see oikawa as he approached you

the team paused and watched as he took a black hoodie from the plastic bag and wrapped it around your waist

‘hmm, y/n-chan, better get dressed so we can go now’

he hummed and you snapped out of your panic and looked up at him with watery eyes

‘oikawa-san’

you whispered and he nodded, eyes knowing what was going on

‘coach, theres a planetarium special tonight’

oikawa shouted without tearing his gaze away from you and coach irihata instantly knew, knowing the code that oikawa came up with when you became a part of the family team

the elder coach made a noise of agreement and oikawa didnt wait to up and carry you in his arms and waved to the team while pushing your head in his chest so you can hide

‘work hard everyone!’

‘oi, shittykawa! what the hell-!’

but an intense side-eye from his best friend shut him up and he knew something happened so he didnt say anything since he trusts oikawa to fix it

‘i trust you will take care of them, iwa-chan’

iwaizumi nodded firmly before shouting to resume back to practice and he himself went back to the line for spikes

you were carried to the bathroom so you could change into your emergency undies and pad and after you did your business, oikawa noticed you uncomfortably waddling towards him so he took you back into his arms

oikawa continued to carry you like his bride down the street towards an unknown destination, humming a children’s show tune that takeru loved to watch, while you maintained curled around yourself, partly due to the shame but also from the pain in your abdomen

you wiped the few stray tears that spilled past your eyes and oikawa chuckled when he noticed you aggressively wipe them off

‘hmm, y/n-chan, you shouldnt do that to yourself. it irritates your eyes and the skin around it so gently dab it next time, kay?’

you nodded, burrowing back to his chest and breathing in his scent

french toast

he smelled like french toast as the smell of caramel and vanilla wafted into your nose

‘howd you know’

you mumbled against the fabric of his jacket

oikawa stopped his humming and replaced it with a chuckle

‘oh, y/n-chan. oikawa-san is a reliable senpai, dont you know? i got a tracker! just for you!’

he answered and your eyes moved from his arm to his smile and you gripped his jacket tighter, fingers curled around it as if it was your lifeline

‘thank you, oikawa-san’

your words of appreciation made oikawa’s heart thump and he faltered a little, blush creeping up his neck, but he fought it down, covering it up with a smirk

‘you should be, y/n-chan! girls would kill to be you right now!’

you rolled your eyes at the return of his cocky attitude but you knew better

the real oikawa tooru was under that mask

turns out, he carried you to his home as his house was the closest while yours had to be taken by a bus

thankfully his parents were out and his sister and nephew were in a trip in tokyo that you had the house to yourselves without anyone asking questions that might make you uncomfortable and them misunderstand

he shut the door with his foot and made his way up the stairs with ease, his strength truly impressing you at that moment, before settling you down on his bed

it wasnt even on purpose but you curled yourself on his blanket, head buried in his pillow

his heart combusted and tooru had to look away or else he wouldve jumped on you and coddled you forever

instead, he quickly ran over and knelt down under his desk to reach for the box that he has prepared for you

‘y/n-chan, i never knew your pattern until last month so i was able to prepare for you now’

you looked up from your position on the bed and sat up enough to see him standing there, grinning with a mint green box

‘wh-what is that?’

you asked and he shuffled over, sitting next to you

‘this, is the y/n care love box! this special box was created by yours truly with everything you want and need during this dreadful week. theres your favorite food, warm socks, coupons you can spend like watching movies and eating ten tubs of ice cream while we talk shit about the boys’

he listed, gripping the box nervously

‘so? do you like it?’

he looked away from the box and to you but his smile slipped into a panicked one when he saw you silently crying and biting your lip to keep the sobs in

‘y-y/n-chan! i-its okay if y-you dont like it! o-oikawa-san can-’

‘no!’

you cut him off and lunged to hug him with all your might

hehe all might

E A T T H I S

‘i love you so much, oikawa-san! so much! thank you!’

you sobbed into his neck and he tightly hugged you back, lifting you so you could comfortably sit on his lap straddle him if you want me to be straight forward

oikawa gently moved so he was leaning against the wall that his bed was pressed against while you were pressed against his warmth

his fingers were drawing small circles on your back and whispering corny jokes or puns that made you giggle and laugh and occassionally, he would kiss your nose and you would whine at the ticklish feeling

eyes fleeting around the room, your eyes settled back on the box and you reached out, wanting to grab it until oikawa beat you to it and snatched it for you then placed it on your hold

‘whats inside, oikawa-san?’

you cutely mumbled, sitting comfortably back on his thighs so you could open the box in front of you

oikawa laughed

‘just open it and figure it out yourself, y/n-chan’

you pouted at his tease but smiled widely when you revealed the contents inside

‘oikawa-san!’

his eyes followed your surprised expression and his hands gripped your waist

‘you like it?’

he whispered and you nodded, looking back up at him and kissing his cheek, his

‘youre so sweet, oikawa-san! like-like this candy bar! howd you know i like this?’

you held up the treat and he shrugged

‘i keep seeing you get it whenever we go to the store’

you continued to sift through the things, seeing a dvd of your favorite movie, a f/c heating pad, a note that said your favorite ice cream was in the fridge, a bag of your favorite chips, fluffy socks, the goodies

you didnt even notice yourself crying again, only realizing it when there were wet spots beneath you

oikawa saw this and he quickly but gently put the box to the side and cradled your face with both of his hands, softly wiping the tears away with his thumbs

‘aw, dont cry, my little baby. princesses should never cry’

you sniffled and choked a laugh

‘hah, n-not a baby. j-just hor-monal’

you complained and oikawa snickered but shook his head then kissed your nose again

‘youre my baby’

you didnt have it in you to complain so you went back to snuggling into him

oikawa squeezed you and went back to drawing the circles on your back and he felt you relax into his touch and slump against his form, slowly starting to snore

your head rested on his shoulder and he turned slightly to watch your eyes flutter and nose scrunch when a strand of your hair fell on it

his heart continued to beat faster and faster and it showed by the way his fingers shook as he carefully lifted the hair away from you

he slowly bent down to give you a kiss on the forehead before laying you down to sleep more comfortably

‘good night, princess’

he sweetly placed a last kiss on your cheek before getting up to go prepare your heating pad for when you wake up

the next few days were possibly the best period days youve ever had

maybe because it was oikawa telling the team that you were in,,,,, satan’s domain currently and they should be careful with you so they tried their best to lift the weight and burden off of your shoulders

however,,

the next day after the incident,,,

they still didnt know what was wrong with you and oikawa forgot to text the gc about your condition so they were still unknowing

like today

during your classes, you were feeling off, almost nauseous but eating little bits of your chocolate treats were helping you get through until lunch

ofc kunimi noticed bc hellow he sits next to you and he doesnt pay attention during class so hes been watching you sneak little bites so the teacher doesnt see and ducking under your book

he was just amused with the way your eyes would widen if you thought the teacher caught you

kindaichi and kunimi and you usually ate lunch together at your classroom since you three only got to hang out as first years during lunch

so they know you usually have a bento with you and have a general idea of how much you eat

and kunimi thought since you ate all those chocolates earlier, you wouldnt eat as much food but then he saw you scarf down your bento, eat 2 more bags of chips and was finishing last chocolate bar

kindaichi,,,, wasnt even finished with his own bento and was watching you, amazed, at how easily you ate all of it

they didnt say anything since they thought you just didnt eat dinner last night but even during the walk towards the gym for after school practice, you were complaining that you were hungry and was eating another chocolate bar

they thought something was truly wrong bc you were eating so much more than usual

kunimi watched you chew on it as you opened the gym door and still ate even when you were talking to mattsun about his jump height

‘man, you sure are hungry, aren’t you, y/n? thats like your fifth chocolate bar today’

kunimi teased, grabbing a ball to spike but he froze, seeing you with the coldest and angriest look hes ever seen

you blinked at him, grip tightening on the treat, and mattsun slowly backing away from you

you advanced towards the blep boy, treat already forgotten and shoved to be held by mattsun

despite your shorter height than kunimi, he trembled slightly as you looked up at him

‘are you calling me fat, kunimi? are you? am i fat? do you think im ugly? im a piggie?’

you ranted and slowly started crying, making kunimi frantically scramble to stop you before the other upperclassmen see or worse, oikawa-san

‘y/n-wait-no!-um’

‘y/n-chan?’

kunimi shut his eyes tightly in fear at the deadly sweet voice of his captain and kindaichi and mattsun sent a quick prayer to their fellow teammate before he was going to get killed

‘uh oh, i think we’d have to start looking for a replacement for kunimi’

makki, who just arrived, teased making kindaichi fearfully look at him

‘eh?!’

‘oh, you first years have never seen oikawa mad, have ya? well, you’ll get front seat of it!’

mattsun clapped him in the back making him gulp

you werent sobbing but you were definitely crying, tear tracks quickly being wetted by the numerous amount of tears that fell

kunimi scrambled to his knees and folded himself, forehead resting on the floor by his hands

‘I APOLOGIZE! PLEASE DONT KILL ME! I APOLOGIZE! PLEASE FIND MERCY IN YOURSELF AND FORGIVE ME, Y/N-SAMA!’

it was certainly a sight to see

normally calm and collected and chill and relaxed hippie kunimi begging to be forgiven

oikawa stepped forward but you quickly felt the change of your mood, feeling bad for your boy and scrambling to pull him back up

‘oh kunimi-kun! dont kneel like that! the floor is too hard and might give you knee pain!’

it was like whiplash

iwa stepped in the gym and saw the team’s confused and bewildered expressions and saw you, kunimi, and oikawa and he shook his head

this aint even half of bad as he has seen

oikawa gently took you away from kunimi and held you to him instead, giving you a smile, to which you returned, and looked at kunimi, a deadly glint in his eye

‘what happened, y/n-chan?’

the tone of his voice sent a chill to run down everyone’s spines and even iwa, the boy who’s seen this a handful of times, shivered and nervously watched oikawa, ready to jump in

but you just blinked, completely unaware of the change of atmosphere

‘oh, um, i overreacted. i was eating too much food today and mustve annoyed him or something’

you sheepishly mumbled but oikawa was having none of it

‘no, its fine. youre literally bleeding out as we speak! dont feel the need to validate yourself!’

he lightly scolded while you hung your head low and continued to apologize but he gently bonked your head before scolding you again

the team definitely knew now that you were in that,,,, time and they definitely knew now, especially kunimi, that even if youve seen oikawa mad, youd think that the devil was more merciful than him when it relates to the topic of you

a/n: i swear to GGGOOOOODDDDDD im an oikawa whore who cant seem to stop writing for him!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

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clawsandaffect · 4 years

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Angry stomach is angry - or how we can translate tweet-speak for the medical world

“Ow my stomach is killing me”

“That burrito is really not sitting well with me”

“Uhhhg angry stomach is angry”

“My tum is :( :(”

Not only does everyday language incorporate a lot of figurative sayings, but sometimes what we write online seems like it could be another language altogether.

Now consider the problem of mapping this internet-speak to medical concepts. Chances are your doctor didn’t dissect a stomach emoji in medical school. There needs to be some system to translate the kind of language we find online to formal medical terminology. This task is called concept normalization.

Limsopatham and Collier (2016) [1] explain what has been suboptimal about previous approaches to associating informal language with medical language and propose a method of their own. In brief, they argue that there needs to be some understanding of text at the semantic level, that is lower-level meaning, before it can be understood as health-related information. The successful approach uses a convolutional neural network (CNN), which outperforms their other model of a recurrent neural network (RNN).

Both CNNs and RNNs, when used in natural language processing (NLP), typically take word embeddings as their input. The most intuitive way we can understand word embeddings is that "a word is characterized by the company it keeps." [2] Each word in an embedding is represented by a vector, typically reduced to 300 dimensions, that is the result of some statistical analysis that quantifies the relationship among all words. In this paper, the preexisting, widely used GNews (based on 100B words pulled from Google News) and BMC (based on 854MN words from medical articles) word embeddings are used as model input.

Click here for an explanation of word embeddings

A CNN applies convolution over a sliding window across words in a sentence, which here is a tweet or a phrase from a blog post. Convolution refers to a filtering function being applied to a subset of the word embeddings, resulting in a new value that gets stored to summarize that subset. The result is a feature matrix where each window of words has a value corresponding to each feature. The maximum value at each feature goes on to represent the fully connected layer, the output of the neural net. The CNN used in the paper uses a single convolutional and pooling layer, meaning that this procedure is done only once.

Click here for a primer on CNN

Instead of using a sliding window, an RNN sequentially goes through words in the sentence and at each state produces an intermediate output called the hidden state. Each subsequent word’s embedding is processed with the previous hidden state as the input, which is what makes the network recurrent. A gated recurrent unit (GRU) is used as one type of gating function that chooses what information is relevant to maintain or forget throughout the sequence of words.

Click here for a primer on RNN and click here for details on gating functions such as GRU

When a sentence is given to the trained neural net, the output is passed to the softmax activation function, which gives a probability for the sentence being assigned to each of the selected medical terms. The probability of a phrase belonging to a given term is calculated as the exponential of the network output for that term divided by the sum of all exponentiated outputs.

Click here for a quick video explaining softmax

There are six baseline models that the two neural networks are compared against and three evaluation datasets, two based on tweets and one based on blog posts that have health-related phrases. One of the Twitter-derived sets is a novel dataset created by the authors centered around adverse drug reactions (ADRs). The models are evaluated on the basis of accuracy, where each tweet or blog post phrase is labeled with some ground truth medical topic label that the neural network then has to predict. The blog dataset resulted in higher accuracy than the other two in every case, and the researchers reason that this is because written posts tend to have more linguistic structure than brief quips like tweets. In terms of models, CNN and RNN both greatly outperform the chosen baselines, especially when using GNews embeddings. The CNN achieves a stunning 44% improvement in accuracy over the highest baseline, from 0.3099 to 0.4478.

The authors discuss where their neural network models have advantages over other previously used methods for this task. One historically used class of methods is based on string matching and finding similarities in words. The pitfall here is that the models cannot derive semantic meaning and would be mislead to believe that “i don’t hunger or thirst” is indicating hunger rather than loss of appetite as a health phenomenon. A phrase such as “appetite on 10” is complex and doesn’t make sense to a model that is unaware of semantics, or the meaning being conveyed by a word. By contrast, these neural networks can make use of co-occurence of words to understand something about their underlying meanings and understand “appetite on 10” as signaling “increased appetite.”

Hungry for more? I will be starting a new blog called Code Blue that interfaces topics in healthcare with data science. More posts in this vein (ha ha) are to come soon!

Related Work

1 - Adapting Phrase-based Machine Translation to Normalise Medical Terms in Social Media Messages (Limsopatham & Collier 2015) [3]

The authors of the reviewed paper also developed a model using not neural networks but phrase-based machine translation to address this same problem of mapping informal language to medical terminology. This model is also built on the foundation of word embeddings. Like in the reviewed paper, they strive to derive a semantic sense to words and go beyond past work simply considering lexical features.

2 - Pharmacovigilance from social media: mining adverse drug reaction mentions using sequence labeling with word embedding cluster features (Nikfarjam et al 2015) [4]

This paper also models semantic similarities in words to try and derive medical meaning from the type of language used on social media. Specifically, they focus on the task of mining adverse drug reactions (ADR) based on what people have shared online. Their model, ADRMine, is based on conditional random fields (CRFs).

3 - Utilizing social media data for pharmacovigilance: A review (Sarker et al 2015) [5]

This is a survey of studies that detect ADRs from social media. They found that while there were 22 studies done on the topic, only six of them had their annotations publicly available, which is what would allow the methods to be compared on the basis of performance. They use these insights to propose a systematic way to collect ADR information from social media.

4 - Automagically Encoding Adverse Drug Reactions in MedDRA (Zorzi et al 2015) [6]

This paper continues on the theme of identifying and classifying ADRs. It uses the MedDRA database, the standard terminology set for reporting adverse events related to medications. The authors describe an algorithm to automatically derive MedDRA codes from freeform text, making it so that experts don’t have to manually annotate descriptions but only need to validate them.

5 - Twitter as a Lifeline: Human-annotated Twitter Corpora for NLP of Crisis-related Messages (Imran et al 2016) [7]

Although this paper does not deal with medical data, it still uses the Twitter universe as its subject of study for learning information from informal, noisy, and short messages. It trains an impressive word2vec model based on 52 million tweets from 19 different disaster situations that happened between 2013 and 2015. What is interesting here is that the language found in the tweets is hand-, or human-, annotated. This is something the reviewed paper did not do in coming up with a model for online to medical terminology. However, in both this paper and the one reviewed, the “ground truth” labels used to evaluate accuracy were based on hand annotation.

References

[1] Limsopatham, N., & Collier, N. (2016). Normalising Medical Concepts in Social Media Texts by Learning Semantic Representation. Apollo - University of Cambridge Repository. https://doi.org/10.17863/CAM.378

[2] "A synopsis of linguistic theory 1930-1955". Studies in Linguistic Analysis: 1–32. Reprinted in F.R. Palmer, ed. (1968). Selected Papers of J.R. Firth 1952-1959. London: Longman.

[3] Limsopatham, N., & Collier, N. (2015). Adapting Phrase-based Machine Translation to Normalise Medical Terms in Social Media Messages. In arXiv [cs.CL]. arXiv. http://arxiv.org/abs/1508.02285

[4] Nikfarjam, A., Sarker, A., O’Connor, K., Ginn, R., & Gonzalez, G. (2015). Pharmacovigilance from social media: mining adverse drug reaction mentions using sequence labeling with word embedding cluster features. Journal of the American Medical Informatics Association: JAMIA, 22(3), 671–681.

[5] Sarker, A., Ginn, R., Nikfarjam, A., O’Connor, K., Smith, K., Jayaraman, S., Upadhaya, T., & Gonzalez, G. (2015). Utilizing social media data for pharmacovigilance: A review. Journal of Biomedical Informatics, 54, 202–212.

[6] Zorzi, M., Combi, C., Lora, R., Pagliarini, M., & Moretti, U. (2015). Automagically Encoding Adverse Drug Reactions in MedDRA. 2015 International Conference on Healthcare Informatics, 90–99.

[7] Imran, M., Mitra, P., & Castillo, C. (2016). Twitter as a Lifeline: Human-annotated Twitter Corpora for NLP of Crisis-related Messages. In arXiv [cs.CL]. arXiv. http://arxiv.org/abs/1605.05894

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