jinto36

Japanese culture also has a number of "ritual purity" elements, such as taking shoes from outside off in the genkan (vestibule) before stepping into the main part of a house, and ritual cleansing with water when visiting a shrine. I understand that Japan is far more economically advantaged than India, but even so, the difference in how clean things are between New York City (for example) and any major city in Japan is quite stark. [I'm from the US but lived in Japan for a year. Haven't been to India but I know a lot of people from there.]

One thing that works for me is to just start writing figure legends. That seems easy, it doesn't feel like "writing the paper". I end up basically writing the results section for that figure or table, so I just cut and paste most of it to the actual results later, and keep a summarized version for the actual figure legend. By coincidence, I'm trying to submit a PhD thesis today (Genetics/Computational Biology).

Alphafold is a big improvement, but a structure of a single protein in isolation isn't representative of how these things exist in vivo. Binding substrates can modify protein shapes, and proteins often function in complexes, which can form some pretty complex arrangements, where positioning is critical to function. I think training set bias is an issue to some extent, even with single-protein prediction. For example, I've been looking at a family of transcription factors, and most of the resolved crystal structures are of just the DNA-binding domain, crystallized with the substrate (DNA) bound. Alphafold predictions for homologous proteins that haven't been experimentally resolved but share a decent amount of sequence similarity thus have high confidence for the DNA-binding domain, but lower confidence in other parts of the protein, even if they're "ordered" regions (e.g. helices and sheets rather than floppy loops), and all the predictions for the DNA-binding domain look like the bound-to-DNA conformation. So we don't have a good way yet to predict different "modes" of a protein that has interaction-dependent conformations. Technically with Alphafold if you were interested in modelling a protein that had similar experimentally resolved both with and without substrates bound, but were interested in sampling just one of those states, you could customize your sequence database to include one or the other, which would be mostly manual curation.

I've been testing out the multimer (protein complex) mode of Alphafold recently, to see if could predict interactions for a family of proteins where some members in the family are known to form complexes, but others previously were found to not form complexes at least when expressed in vitro rather than in vivo. So far I've found that if you try to throw two completely unrelated proteins together, they won't be modeled with any contacts, but for the ones in the family I'm interested in, there's always at least one (of the five models per run) that has them interacting such that there's something that looks like a real DNA-binding domain. For the latter case, it's presently hard to know based just on Alphafold output if it's a structure that could actually form, or if it's just due to bias in the training data, with perhaps the rest of the structured regions of the protein being conformed in unrealistic ways due to less training information for those parts.

TL;DR Alphafold results are biased by existing experimentally resolved structures, and not based on simulating physics, so proteins- or parts of proteins- that don't have good coverage in existing experimental data are not going to be predicted with high confidence.

Same for me, I try to make it meditative in a way. I don't use earbuds or anything, just try to continue existing and moving. Sometimes identify birds. Practice talking to myself in languages I'm studying. In races it turns into body state monitoring and trying to determine when/if to adjust pace. Check in on form. On heart rate. Pick someone up ahead to try to catch. Count down to the next gel or electrolyte tab or water station.

I've done quite a few 2hr+ runs (half marathon to marathon) and 100 mile bike rides, and after a while for me it turns into a psychological game.

Trail running, if you haven't tried it, is much more "stimulating" I might say, depending on where you are there's a lot more focus and attention required to stay on the trail, to stay upright (slipping on mud, ending up in a river), to dodge trees and rocks as required, etc. I personally find there's much more of an aspect of being "in the zone" for trail running, and especially in races, when I miss a turn and have to stop and backtrack, it becomes really obvious that I was in some kind of "flow" state and then got pulled out of it.

We haven't done lightning/thunderbolt, but the Youtube reviews include the different USB-C power modes. We also look at some aspects of safety, such as when overcurrent protection in kicks in relative to the device rating, and if it automatically resets after tripping or requires power cycling.

I haven't tried Affinity Photo but Affinity Designer has been a pleasant surprise. Worth the non-recurring $50 investment. I want to like Inkscape, but there are just too many quirks still. PDF output from Designer so far always looks great. My primary use case is putting together figures for scientific papers.

Akebi for Android is pretty good. For a while I used the Nintendo DS Japanese dictionary (Rakubiki Jiten) for the ability to do stylus-based character recognition, which was less frustrating to use than the Windows IME pad feature. Akebi works reasonably well for that function.

I only just started learning Chinese, so I haven't looked at Pleco yet and can't really compare them.

I'll agree with some other comments that once you get into the area bordering intermediate and advanced proficiency there are many fewer resources, but by then you have a better idea of what you don't know, and and can use your existing base to sort of plot a path to fill those gaps.

I pulled a 128D out of a dumpster (literally) around 2002, in the US. I was always a bit confused if it was actually a 128D or a 128DCR since the articles I checked at the time said the 128D wasn't sold in the US, but the nameplate does say "128D" on it. Newer articles mention that the DCR had a metal case, whereas the original 128D was plastic so now I know mine is the DCR. I've never seen another 128D in person so it was really difficult to tell.