khr

Interesting idea, and it sounds like you like the results, so kudos.

My musical taste tends toward less produced, rougher/lo-fi recordings, e.g. Guided By Voices. So, it follows that I prefer the original recordings.

There is one aspect that I find slightly dehumanizing -- the AI changed the singer's voice so drastically that I don't recognize the original singer anymore. The uniqueness of the voice has been smoothed out to be much more generic. For me, music (and art in general) is in part an expression of one's identity, so I'd consider this a negative outcome. I'm sure similar things could be said of the instrument performances as well.

But again, this is all just my two cents, and it's a matter of taste. Ultimately if you're happy with the results, that's what matters!

I found out that the adhesives I've encountered from time to time that remain tacky and easily moved or removed are called "non-hardening" adhesives. This was after using E8000 glue for a headphone repair today.

You can, depending on your definition of "useful". You can buy a cheap laser pointer, take out its lens, and put it over your camera lens. Tape it onto the lens for a temporary janky version or make a 3d-printed mount for something much better that you can easily take on/off.

I've personally found this little hack useful, but then again I don't have a DSLR and macro lens!

Yes, on my Thinkpad I could remap it with Powertoys. It looks like the sibling comments have had issues though.

For me, the Copilot key outputs the chord "Win (Left) + Shift (Left) + F23". I remapped it to "Ctrl (Right)" and it's functioning as it should.

Thanks for making this! I'm very tempted to get one of these to do some ssVEP stuff.

Do you have plans to make a 16-channel (or 32-channel?) board in the future? In my area of research, 32 channels tends to be the recommended minimum for studies.

Translating a solution from one problem domain to another is called "transfer" in cognitive science. There's some theoretical and empirical work done on the topic of transfer (e.g. https://www.tandfonline.com/doi/full/10.1080/135467808024901...) but as far as I'm aware, there is not a mature "general theory of transfer" that can be computationally implemented. That's still in the fictional "Glass Bead Game" territory. However, you may want to take a look at that literature for broader picture theory on the issue. It's closely related to the fairly vast literature on insight problem solving, which you might be interested in.

This article didn't link to the research article directly. Here it is for those interested:

https://science.sciencemag.org/content/373/6553/eabd0830/

I found a previous HN submission very helpful: https://evamaerey.github.io/ggplot_flipbook/ggplot_flipbook_...

The author builds up plots step by step, showing the changes to the plot along the way. It's really great at showing what each element contributes to the final plot.

Not to take away from some of these comments, but the article does not mention anything about casual observation of the eyes signalling mental health issues. The article is highlighting research on diagnosing disorders of the brain using ophthalmological methods (e.g. optical coherence tomography to measure retinal thickness, electroretinography to measure electrical signaling in rods and cones, and angiography to assess retinal vasculature). Apparently, these non-invasive methods may be used as an additional diagnostic tool in diagnosis of a variety of disorders, and may even be early indicators of brain disorders that have not yet manifested themselves in psychological disturbances.

In that case, perhaps "A Book about Creating Aircraft Scale Drawings with Inkscape and Gimp" would be more appropriate?

Agreed. I was curious enough to run the model myself so I used a tool to extract the data. The slope estimate (b=17.24) is not significantly different from zero, p=.437.

The data are here: https://pastebin.com/HhWTKZRb

I feel the same way. I think this explanation of the transition has been mentioned on HN before:

1) The Internet was created. Early adopters are generally optimistic about its potential to share knowledge and data, and form communities around mutual interests. 2) People begin to realize different ways to create money from this popular new technology, leading to very obvious attempts at creating revenue at some expense of users attention (e.g. advertising), followed by more hidden ways of revenue creation (e.g. selling data).

I also find it hard not to despair. There are still online communities that are still more motivated by communicating and sharing for their own sake (HN included), which I think should be the aspiration of online communities. Most people here have probably just settled into the online communities/blogs that serve these more optimistic goals. The unfortunate thing is that as soon as these communities become relatively popular in any way, other motives start to come to the fore to take advantage of that popularity. As those motives become clear, cynicism is inevitable. It seems to me that you might need something like benevolent community leaders that want to pour their own resources (time and/or money) into online communities without expecting anything in return.

I guess this comment didn't really offer ways to deal with cynicism regarding technology, if anything I justified the cynicism and suggested an option to create communities that would not breed cynicism.

My non-engineer guess is that a nylon brush would be shaved down pretty quickly by rail contact at typical train speeds, so that it would be ineffective at removing debris after a very short time.

I haven't read the entire paper, but it's here: https://psyarxiv.com/a5fgu

The main results are an interaction between Time (pre/post) and Diary condition (3rd person/1st person), t = 2.65, p = .008. They followed this up with a contrast showing that the 3rd person diary condition resulted in more wise reasoning post-intervention (as compared to pre-intervention), B = 0.130, SE = 0.028, t = 4.61, p < 0.0001. And importantly, this same improvement was not seen in the 1st person diary control group: B = 0.022, SE = 0.030, t = 0.74, p = 0.458.

They didn't provide degrees of freedom for their t-tests, but given their sample size (N=298) they're essentially z-tests anyway.

Sure, there is subjectivity in the ways researchers operationalize the concepts that they study. That doesn't mean that their research is not "real science". If the study is of sound design and the result is replicable, it ought to be called science.

Regarding the self-measurements influencing the results: the wisdom in the participants' reasoning (the dependent variable in the focal study) was evaluated by two independent hypothesis-blind raters. This seems like a pretty solid evaluation of the participants which should be immune to anything but the manipulation the researchers employed (the diary conditions). I am not sure what self-measurement you are concerned about.

A 95% confidence interval will contain the true mean 95% of the time (across an infinite number of replications of the experiment/study). For a single confidence interval, you have either captured the mean in your confidence interval, or you've not -- there's no probability about it.

erentz was probably referring to the single transferable vote system (https://en.wikipedia.org/wiki/Single_transferable_vote), which uses a ranked ballot in elections and results in relatively proportional representation. CGP grey explains it pretty well: https://www.youtube.com/watch?v=l8XOZJkozfI

Mirrors in skylights seems like a very obvious improvement to increase the amount of natural sunlight in a space. It seems adaptable to north-facing top-floor suites. Mirrors could be installed such that the sun would reflect into the suite throughout the day. It seems to be such an obvious improvement, but I've not noticed such a system anywhere in my city. Maybe the regular cleaning of the mirrors is enough of a deterrent for building owners to invest in something like this?

Power is also a concern that many researchers do not pay attention to (at least in psychology/neuroscience).

If the original study was under-powered, the estimated effect size in that study will be inflated and any replication attempt that uses this inflated effect size estimate will be severely underpowered.

Plus, two independently conducted studies that are both powered at 80% to detect a true effect will both be positive results only 64% of the time (assuming absolutely nothing fishy going on, e.g. p-hacking).

There are many ways to study attention and mood. What I took from the press release which appears to be novel (though I've not read the original research article) is that our higher-order representations of facial emotions are able to be influenced by stimuli presented to the participant unconsciously. Although the participant was not aware of the happy faces being presented to them, their representation of the emotion of a separate face was affected. This is very different from the obvious "our mood influences what we attend to in the world".

Also highlighted in the press release is the fact that this was robust for unconsciously presented happy faces -- it is unusual for positive stimuli to have a stronger effect on most psychological measures. This is usually due to negative stimuli causing higher levels of arousal (as far as I know, though I'd need to confirm this in the literature), so it's really due to a confounding of valence and arousal.

My main question from this article would be how they controlled for low-level visual properties of the stimuli presented. The hope is that their upside-down face experiment was able to account for any possible confounding of face emotion with something like spatial frequency characteristics influencing the participant's subjective judgement of the neutral face, but there will never be a way to fully claim that it was the emotion of the face alone. If you fully control the underlying visual properties of the stimulus, you remove the emotion!

It's especially strange since there are good free multi-platform statistics programs. There's R (as other commenters have pointed out) and JASP (https://jasp-stats.org/) which has a similar point-and-click interface for those who are used to SPSS.

Do you plan to add PsyArXiv? (https://psyarxiv.com/)

I have found it to be a useful feature that is worth the 1% daily battery life. I prefer it to Shazam/Soundhound because it's passive. I don't have to unlock my phone, open an app, press a button, and wait for the app to recognize the music. That whole process is disruptive to conversation if I'm with someone. How often the question of "what song is this" comes up depends on who you are, and it has occurred to me often enough such that I've recognized that I much prefer using Now Playing.

I agree that the database is a major limitation, although for me it acts as a first pass to see if the song I'm listening to is popular enough to be recognized.