

Waking life - I have no way of explaining why, it just leaves me with something unique. Blissful maybe?


Waking life - I have no way of explaining why, it just leaves me with something unique. Blissful maybe?
Not sure. In Begium I’ve seen butcher shops that specialise in horse meat and in Korea there are restaurants where horse meat is served.


That’s not uncommon in many other languages aside from German. Think of it as saving space(s).


There’s a lot of overlap with villains but whereas true villains are irredeemable, anti-heroes show some humanity or empathy or ethics in some context and have vulnerability.
Cat didn’t seem to mind camouflaging into the kids chalk artwork. She did mind though me having to clean her afterwards.


“If the human brain (mind) was simple enough for us to understand it, we would be too dumb to understand it”. I don’t know who said it but my point is that I cannot imagine any health care pathology to be so simply one dimensional that it’ll fit on a continuum.


Perhaps it helps to understand that a spectrum can be comprised of a cluster of continua: a possibility space of which any subset can be observed. Like each colour in the light spectrum. The continuum notion in that case can refer to its brightness. Same in the case of emotions. We don’t just experience one emotion at any given time although there’s a prominent one and others might be subdued. How we cluster certain aspects, such as traits in mental health as well as the threshold to diagnose anyone is of course arbitrary. Severities in presentations are perhaps seen as a continuum, but the underlying structure that aids in defining it, is a spectrum.


I feel like people confuse the term spectrum with the term continuum. Fading from black to white through gray is a continuum. Rainbow colours are a spectrum. In mental health, most conditions have no aetiology - or it is not considered, and the condition is described or defined by signs and symptoms, and not something like a bloodtest. The weight of each of these signs and symptoms is what makes up the spectrum. When someone is on the spectrum of whatever condition, it means the sum of those weights exceed a value that causes some detriment to the individuals quality of life. Maybe I’m spliting hairs but I thought to share my understanding.


There’s a lot of overlap in experiences of folks with different mental conditions. Whilst the root cause is different with a neurodiverse brain or mood disorders or personality disorders they might lead to similar experiences. The question becomes how much is it impacing someone’s life or how well can those behaviours stemming from these experiences be integrated. There’s also the fact that self-awareness might be picking up on those experiences better in one group compared to others.
Specific yes, but not oddly: this is paraphrasing from an actual testimony of victims.


Of all the things wrong with this, what sticks out to me how he seemed to be offended when you put down your boundaries. I feel sorry for your sister and i would share this with her. If he behaves like this with his own family, it doesn’t bode well outside of it. Yeah, perhaps replying wasn’t the best idea but i cannot put myself in your position vis-a-vis your state of mind at the time but it doesn’t take away the lack of appropriateness of his comments.

It relates to stuk, which means broken in this context. It can also mean a piece. You could read it as (broken) into pieces.


I find this monologue amazing as it reveals so much about someone with narcissistic personality only that the character has more self awareness than the typical narcissist.
What other posters said, respond with the blinking. My son calls them eye kisses. It shows trust. In case you’re unfamiliar: you look at her and slowly close your eyes for a second. She might mirror it. Facing a fierce predator such as the one you pictured and confronting it willingly blinded, even for a second, takes courage. She’ll honour it most likely. Also food and clean water, preferably placed in separate locations.


I like learning languages so with that in mind: German, Dutch, French, Swedish, Estonian, Russian, Afrikaans, Japanese, Mandarin, Korean, Irish and Latin. I don’t speak all of them thought.


Don’t remember the movie or show but on aired in Korea I saw they would blur out parts such as cigarettes as well as arm pits (male actor) and a chef’s knife (prop was being held with the actors intention to defend herself).


One day he was going on about Kiki, how she does things in a certain way and I kept him going by say how interesting it was. He then turned to me and asked “You know that Kiki isn’t real, right, I made her up?”. He doesn’t like lying or being lied to, so within that frame I guess he wanted me to confirm that it was just play.


Our child has one. Her name is Kiki and she lives on a farm where she drives her tractors in a village called Plamplams. She speaks also an imaginary language. It seems like she represents experience he lives through vicariously expressing some image he has on how he fits in this world. We as his parents have always encouraged him; it is wonderful how he develops such creative images.
I see a flag. I like flags. Especially the Japanese flags. I don’t specifically care for Japan, but the flag is one of my favourites. I prefer flags with low entropy: so I wrote a script once that ranks the nations flags by entropy so I could quantify my preference. Thanks for letting me infodump a bit.
Edit: Due to people aski g for it: here is the top ten of my ranking:
Nations' flag entropy ranking (n=208). Image source: Wikimedia. 0 white_field -1.439759075204976e-10 1 Indonesia 3.3274441922278752 2 Germany 3.391689777286108 3 South_Ossetia 3.8174437373506778 4 Monaco 3.9718936201427066 5 Poland 3.9719290780440133 6 Austria 4.372592975412404 7 Ukraine 4.405280849871184 8 Hungary 4.4465472496385985 9 Albania 4.6134257669087395 10 Mauritius 4.707109405551959 11 Luxembourg 4.721346585737304Here’s how I defined the entropy value for each flag:
def color_weighted_spectral_entropy(image): b_channel, g_channel, r_channel = cv2.split(image) # Calculate spectral entropy for each channel def channel_spectral_entropy(channel): f_transform = np.fft.fft2(channel) f_shifted = np.fft.fftshift(f_transform) magnitude_spectrum = np.abs(f_shifted) if np.sum(magnitude_spectrum) > 0: normalized = magnitude_spectrum / np.sum(magnitude_spectrum) else: normalized = magnitude_spectrum # Entropy calculation with color channel weighting epsilon = 1e-10 entropy = -np.sum(normalized * np.log2(normalized + epsilon)) return entropy weighted_entropy = ( 0.333 * channel_spectral_entropy(b_channel) + 0.333 * channel_spectral_entropy(g_channel) + 0.333 * channel_spectral_entropy(r_channel) ) return float(weighted_entropy)“White_field” is just an array that holds zeroes. I use this as a sanity check. Code is on github. I can send DM to whomever is interested. I guess it can also be searched for.