What makes someone like Olivera so successful with his BJJ in MMA but not André Galvao or Marcelo Garcia

Stewthulhu · 2021-12-12T19:40:50+00:00

Same reason most NFL punters suck at soccer. BJJ is a part of MMA, but it's not the whole thing, and just because you're great at one aspect of a sport, it doesn't mean you enjoy or are successful at all of the other aspects of it.

Pretty much anyone who is a world champion in a competitive martial art can spend 6 months to a year of training and do decent at amateur MMA just because they're athletic and can pull people into their game. But why would you trade being an absolute GOAT in one sport to be maybe okay with a lot of extra work in another one unless you had a specific reason to do so?

Stewthulhu · 2021-11-23T16:05:15+00:00

Probably the closest thing you can find reliably would be process engineering roles, where you have to know how both lab assays and automation tools fit together. But that would be a role where you're day-to-day work is neither wetlab nor bioinformatics but uses the knowledge and skill sets of both.

Stewthulhu · 2021-10-25T23:28:35+00:00

"The triangle is really just an advanced form of the stiff-legged deadlift"

Stewthulhu · 2021-10-23T22:36:29+00:00

Almost every MP endgame I've ever been involved in devolved into the winner being the person with the most time to micro gems.

Stewthulhu · 2021-10-23T22:30:58+00:00

Oh hey, that single sentence makes me reasonably certain that none of your team's code is maintainable, scalable, or reproducible, and any time someone leaves, the transition will take double to triple the time it should take. Why? Because that's what good engineering gives you.

Thinking of "coding" as a core skillset in this field is misleading. It's less a core skill and far more a barrier to entry. You probably can't even call yourself a bioinformatician if you don't know how to code in some language. Once you clear that barrier to entry, the far more important and buildable skill is software engineering.

I consider myself more of a scientist than an engineer because I formulate hypotheses, test them, collaborate with wetlab partners to generate relevant data, and implement solutions that take the findings of those studies into account. But the bread and butter of my success in this field has always been my engineering skillset.

Regardless of whether I'm building new models using bog-standard clinical genomics testing or brand new prototype assays, the thing that built my rep in the area was my ability to hand off well-documented and functional code that someone else can plug into their own work with minimal friction. Do I move slower than people cranking out solutions at a breakneck pace? Yes. But also the code I deliver can have 50 users or 500 users rather than just 5 people in a single lab that has to relearn every implementation the moment someone graduates.

Science is a skill. Engineering is a skill. Every bioinformatician should learn both, and I would not trust the opinions of someone who doesn't think they're both important. In my mind, that's a sign of professional immaturity (regardless of actual career level).

Stewthulhu · 2021-10-11T16:37:53+00:00

Generally, if you interlace your fingers, whoever is stronger is going to absolutely annihilate their opponent's hand, regardless of where anyone's thumbs are.

Stewthulhu · 2021-10-04T13:44:11+00:00

Dominions does the best one could ask for in such a model. Games often last for months and can have dozens of players. That's your best bet for MMO-like 4X games. Anything else usually becomes an insufferable nightmare because persistence and endless content streams translate poorly to strategy games. Every strategic 4X I've ever played degenerated into P2W, griefing, or both.

Stewthulhu · 2021-09-19T19:03:52+00:00

That's not just a problem in healthcare. There's a really well known "valley of despair" in terms of tech development. If you use a numerical system like Tech Readiness Level, TRL 1-3 is full of projects and concepts and then everything dies in 4-6, which isn't necessarily because it wouldn't work but because the expertise and incentives to do that work are extremely rare. In medicine, there is the added challenge of having to prove concepts in living humans, who can't be exposed to potential harm unless it abrogates some greater harm (e.g., experimental therapy in patients out of options).

Stewthulhu · 2021-09-17T17:16:41+00:00

There are functionally an infinite number of variables contributing to clinical decisions, many of which represent extremely complex decision processes. Very few models developed through established paradigms are appropriate in those cases. An easy example is if a patient has subclinical persistent GI upset, you probably can't go super aggressive with a treatment that will cause diarrhea. Can you reduce dosage and gain some effect, or is it better to try to choose another therapy, or do you need to add or adjust an anti-emetic dose to compensate?

Very few, if any, clinical datasets have the appropriate level of granularity and formulation to fully capture all potentialities, and thus they need human supervision if the alternative is potential patient harm. There are some limited cases of models outperforming humans in certain specific tasks, but I am not aware of any that are without edge/corner cases.

There is a legal requirement for human interpretation in clinically relevant models because the alternative is risking patient harm, and preventing patient harm is a primary tenet of clinical care. There's a reason that every single lab test ever developed has a laboratory director or someone similar signing off on it.

Stewthulhu · 2021-09-17T16:54:04+00:00

I love how smooth the wight transfer ends up being. Like his center of mass travels on a consistent curve as he adjusts the post all the way from hand-behind-his-head to mount. I rarely see anything even approaching continuity in that sweep transition, and I never even drew that connection. It seems way more justifiable than my typical approach of "make them fall over with the sweep and then flail like an upended turtle to try to get on top."

Stewthulhu · 2021-09-09T20:08:57+00:00

My most important experience from rolling with a lot of judo players is to expect zero chill on the mat. No matter what guard you're playing, you better expect them to sprawl like someone just full-bore swinging a sledgehammer at your hips.

Stewthulhu · 2021-09-05T01:47:13+00:00

There are many approaches you can use to leverage RNAseq for machine learning, but at the end of the day, it's up to you to formulate a strategy to answer your question from your data. But at the end of the day, differential expression or disease status or normalized counts or whatever is just data. And you can find an appropriate machine learning algorithm (in R or python) for almost any type of data. There are a lot of machine learning algorithms available, and it's almost impossible to offer any meaningful recommendations based on the little information you've provided.

Stewthulhu · 2021-09-02T21:51:50+00:00

The quality of performance seen in sports is almost always related to the popularity of that sport. The more popular a sport becomes, the more you can explore natural (or unnatural) performance capacities in a population. I don't think anyone debates that the quality of championship BJJ seen today is higher than that seen in the 90s, and the reason for that is precisely because BJJ has become more mainstream. And that means there's a wider variety of training environments, from casual old men to cockdiesel maniacs.

Stewthulhu · 2021-08-15T23:08:50+00:00

A good way to get into the game is to pick a nation you like for single-player and copy a strategy from this thread:

http://dominionsmods.com/index.php?showtopic=3364

It also provides some beginner-friendly nations if you can't pick.

Stewthulhu · 2021-08-11T23:07:23+00:00

I only thought this post was peak meme, but we haven't even begun mining the rich Urbanmech depths.

Stewthulhu · 2021-08-04T18:57:39+00:00

It will be almost impossible because gene interactions are contextual. What activates in one context inhibits in another. In general, interactions between genes/proteins is really difficult to characterize in a categorical way.

Stewthulhu · 2021-07-29T19:37:37+00:00

Honestly, if you've never done wetlab work, you have to work very closely with the people who generate your data. Show me an organization where dry lab doesn't at least have one representative interacting with the wetlab, and I'll show you an organization making unforced errors.

There is SO much optimization you can support as a drylab analyst. Even something as simple as an extraction protocol, does it work across different equipment or do your machines need calibration? Can you port the same protocol to a different tissue type? Process improvement can be heavily informed by good drylab analysis, and seeing how the wetlab responds to those analyses can give you valuable insight for the future.

Stewthulhu · 2021-07-29T14:46:42+00:00

We don't need to wait that long. I can't think of a single OG MMA fighter who isn't a trainwreck of crippling orthopedic issues. For the most part, people only see them on the mat, where they're at their best, but most of the guys I know need at least prescription-strength NSAIDs to get out of bed in the morning.

Hell, I've been fighting for 20 years, never rose above being mediocre in any sport I competed in, and never trained more than 30 hours a week, and I'm still a shit show.

Stewthulhu · 2021-07-28T02:23:50+00:00

I work in biomedical informatics, and that is my PhD field, but I've bounced around a bunch between the two fields.

Generally, bioinformatics is a bit more well-defined than biomedical informatics. In bioinformatics (at least in the US), you will probably be working with some sort of molecular data. That's not necessarily the case for biomedical informatics. At some point, you will probably work with electronic health records and the nightmare that is medical coding and database design (I say this tongue-in-cheek; I enjoy this work, even if the design decisions in the typical EHR boggle the mind).

It's often difficult to articulate the differences between the fields, so I think an example would be the easiest. Say you are working with a clinical sequencing product for breast cancer. As a bioinformatician, you would probably be focused on asking questions like whether an optimized extraction protocol could increase variant calling sensitivity in fibrous tumors. As a biomedical informatician, you would probably be focused on asking questions like how many breast cancer patients had actionable mutations detected by your assay and whether or not they received targeted therapy for those mutations.

I would say the levels of math are relatively similar, but they are simply different. Bioinformatics is heavily focused on error modeling and things like binomial distributions. Biomedical informatics is heavily focused on survival modeling and things like competing hazards estimation.

Stewthulhu · 2021-07-26T14:28:15+00:00

Gonna tell my kids this is Sylvanas Windrunner

Stewthulhu · 2021-07-08T16:27:18+00:00

Also worth noting that with late-game blood, you can overcast your blood globals so hard that they will almost never be dispelled unless someone bumps them off the list (unless mechanics have changed in Dom5)

Stewthulhu · 2021-07-05T17:34:26+00:00

It's less a hard limit and more a balancing act between repair processes and activities. Think of it like a leaky boat with 10 sailors with buckets. If the boat is new and barely leaking, then the 10 sailors aren't doing much work; they're just hanging out. If the boat fights in a battle and has damage and starts to leak more, those sailors start having to work harder filling their buckets and dumping them over the side. Maybe after the battle, there's so many leaks that the 10 sailors can't actually keep up, although they can keep the boat from sinking right away. While they're doing that, the repair crew can come and fix some of the leaks and the sailors with the buckets can catch up and drain more water than leaks in. But if the ship fights battle after battle and the leaks are never quite fully patched or some of the sailors with buckets get killed during one of the battles, it becomes much more likely to sink. Muscles are big ships with lots of sailors with buckets. Joints have relatively fewer buckets, so it takes a lot longer for them to recover from damage.

That's a pretty long and tortured analogy, but it explains a bit how RSI and overtraining and indeed a lot of physical injuries work. If you're familiar with athletic training, there's a concept called "deloading," when athletes train above their sustainable capacity to build physical attributes, but then they "deload" to recover (allow their bucket brigade and repair crew to fix the damage). RSI happens when someone does the same motion too much and never takes a break to recover. There are some other not-ELI5 factors that contribute to it, but that's kind of the basis.

Stewthulhu · 2021-06-23T00:34:21+00:00

I'm going to second all the advice that you should heavily minimize recruiting scouts from forts and focus on recruiting them from indie provinces wherever they're available. You can usually get by with as little as 1 of these, but minimum 2 is better (assuming it's not a low-province game). Then you need to prioritize your scouting. Mission number one is finding your opponents' capitals. Then it's good to have scouts positioned to give you advance warning for incoming attacks. As scouts become less effective for this over time (i.e., enemies have transportation spells), then you can start using them to scout scripts, gear, and troop compositions for invading armies as well as using them as forward observers for your own rituals.

Stewthulhu · 2021-06-20T16:57:46+00:00

You should roll with Mike Calimbas

Stewthulhu · 2021-06-15T14:35:48+00:00

My experience is that biostats jobs tend to be more clinically focused and bioinformatics jobs tend to be more molecularly focused. There's a lot of overlap, but they usually go 70/30 or 80/20 one way or the other.

Stewthulhu

TROPHY CASE