I mean the passenger train from Lebanon, TN to Nashville, TN is quite busy. I rode it over a decade ago and it was quite used and my partner rides it now and it is much the same. If it still ran at night like it did back then, I'd probably take it into downtown (and go downtown more often) for events. I don't believe the train left the station a long time ago, we just simply shifted it off the tracks.
> I mean the passenger train from Lebanon, TN to Nashville, TN is quite busy.
From the article:
> Outside of Amtrak’s once-daily City of New Orleans, Tennessee has only three rail transit systems (two of which are currently suspended). That leaves just the WeGo Star in Nashville, which is among the lowest-ridership commuter rail lines in the country.
For MD, specifically the type talked about here, we aren't taking in all the quantum effects, and that is known. Crystalizing molecules, especially large either dynamic proteins or ones in lipids is hard. Crystalizing during transitory states is orders of magnitude more difficult. MD allows us to visualize those transitory states and was used, for example, to observe the unfolding of the spike protein in Sars-Cov2 to assist in designing mRNA vaccines, because the important amino acids could be observed.
There is a lot of times where it is good enough, outpaces current experimental techniques, etc that it is the tool for the job. But it is not perfect and very rarely can stand completely on its own, in say drug discovery or other fields.
Amazing article on Molecular dynamics, in the infinite number of things they could add is a small segment on coarse graining. Though I'm biased (and have been thinking about writing one myself).
Granted wished this had been around when I started my journey instead of having to delve into things like the Amber manual... (which I will grant is wonderful for its information but the organization isn't as convenient).
Depends on how deep you want to go. The pioneering work in this field is the "The multiscale coarse-graining method." series of papers kicked off by Noid. Who is still a person to pay attention to in this field.
I also believe the work of Frank Noe is someone to watch for in the ML potential space for proteins.
Went to a show in Nashville with some friends, I think last year. And drones were definitely incorporated in (interestingly showing Star Wars and then US military assets), but it was done in tandem with the fireworks. Which as a distraction during transitional elements does seem like a good use for them.
Honestly I think the biggest threat is also fireworks NIMBYism, people don't like the loud sounds disturbing their lives, their pets, etc combined with the general pressure of bigger and better exacerbating those problems.
This is really cool, I never expected to see reversible computation made in electrical systems. I learned about it undergrad taking a course by Bruce MacLennan* though it was more applied to "billiard ball" or quantum computing. It was such a cool class though.
God I love einsum so much. I discovered it in grad school and it made my life so much nicer, definitely recommend learning it, you can do some wicked powerful stuff. (One of the first things I asked one of the NVIDIA guys when they were showing off cuPy a few years back was whether it had einsum.)
I am a computational biophysicist turned generalist, I enjoy solving the weird problems everyone hates. Undocumented code on a system built from decades old software where it's held up by toothpicks? My jam! Need me to build a jet engine from duct tape, super glue, and balsa wood? Let's go! From being in academia I've worked on large and diverse teams and from being a contractor I've been both part of smaller teams and left to my own devices, I excel no matter what.
This is extraneous to your comment, but as someone who speaks some Japanese, if you ever want someone to practice English with, I am more than happy to lend a hand.
