How many Mac Pro's have ever sold? Or the Pro Display XDR that costs more than the Vision Pro... Apple are in the business of generating hype and a ladder of hype and glam around what would otherwise be boxes of electronics. They then sell millions at the bottom end whilst everyone aspires for debt to buy the high end.
That's a different meaning of endosymbiosis at a more macro scale. This is cellular endosymbiosis. Having bacteria in your gut is not the same as having them be integrated at a molecular level into your cells as an organelle. You're scepticism of the media hype claim is correct though, there are other well known examples of endosymbiosis like this occurring, primary and secondary. Perhaps not primary with cyanobacteria but thats hardly some huge "scientific leap" in understanding or astonishment compared to some of the other stuff we know about.
Ironically you do see this kind of cellular endosymbiosis amongst the endosymbionts within insect guts with the most extreme example probably being Mixotricha paradoxa https://en.wikipedia.org/wiki/Mixotricha_paradoxa
Hatena arenicola https://en.wikipedia.org/wiki/Hatena_arenicola is very similar to this new finding, but with an algae instead of a cyanobacteria so its a secondary endosymbiosis which if anything is actually more interesting and bizarre.
We also know from the genome of Smybiodinium that its undergone quite a few endosymbiotic capture events some secondary with algae but quite likely some primary with bacteria too https://en.wikipedia.org/wiki/Symbiodinium
The main issue is the majority of managers arent especially qualified to make a judgement of the code itself which makes the metric spurious at best. Lines changed is at least a better version than lines added. But it is fairly devoid of meaning removing ten lines can be extremely hard and impactful compared to adding 1000 lines of deeply nested ifs written poorly. Lines changed multiplied by number of files touched is possibly better too.
Any generic measurement of productivity is a sign that the manager is incompetent.
If you're a manager and can't tell what your employees are doing, you're a terrible manager. Same reason they hate people working from home, they can't actually tell if someone's a good employee, they have no clue whether anyone is good at their job because they don't understand their job
1) A good manager needs to look at code to see what employees are actually doing. They can't just rely on the employees' verbal description.
2) One (correlated though not guaranteed) indicator that an engineer is struggling is when they are producing much less code than their peers or compared to any natural expectation of the role. Yes of course it's 100% that some bugs are super tricky and take a long time to find the magical one-liner fix. But statistically those are not common.
This is premised also on my belief that every engineer manager should be a very strong engineer themselves. This is common at most of the big tech companies.
Valid comment, unless $is_bad_example. I genuinely really like the use of unless in Perl. There are lots of times it's nicer to express inverse logic. You could change the name of a variable to have inverse truthyness and not have if not everywhere. Or you could accept you often need to deal with inverse logic on something and use the right language.
I'd say this is more like pytorch is horribly packaged and a nightmare as an eng user to integrate into codebases. All of their assumptions are you use conda and are a datascientist one time doing something in an ipython notebook. Very little consideration is made to how you deploy at scale reliably. It's not really on poetry.
While this is on the one hand at least partially true, it is also the case that as long a poetry can't deal with these (and similar) cases then it cannot really be said to be a candidate for the 'default' dependency management tool. Having people say 'just use poetry' as the go to answer is very bad default advice as long as poetry will fail in a number of important cases.
There are proteins known as "Intrinsically Unstructured Proteins" or "disordered" proteins. That function with no fixed configuration. Typically a good way of thinking about them is an ensemble of transient more common states, where things like post translational modification alters how long and which conformations the protein visits. The other replies you've gotten are inaccurate and about 15+ years out of date in thinking about protein structure.
Think of a roiling noodle where sections or the whole thing linger in certain shapes and configurations longer than in other positions.
> The other replies you've gotten are inaccurate and about 15+ years out of date in thinking about protein structure.
I do not believe the case, speaking as one of the others replies, and having reviewed the others. But since you do, could I request the extra work of some pointers to the inaccuracies?
NMR-driven descriptions of protein structure flexibility are far more than 15 years old, and common in all graduate bio courses since the 90s, so if I'm perpetuating some sort of inaccuracy I'd really like to know so I can stop.
Right... but the title before the first line reads "DataFrames for the new era". If you don't know what a data frame is then, yes, it's for people who already know that.
I'd say you're pushing from flippant to disrespectful on the who and how of this being done. Starting with you've got Addenbrooks and Guangzhou hospitals collecting the foetal material that will have been lovingly donated from some of the most distressed members of the British and Chinese population. The pipeline although commodity came from a new startup Enhanc3D Genomics Ltd (inc. 2020). Over 15 labs worked collaboratively to build the atlas of results, because the expense in human time alone far exceeds what could be done in a single lab.
I am being flippant I suppose, but it is also so incredibly easy to publish such works when you have the money of an entire consortium behind you.
Also, how are these datasets to be shared? In some of the sets I've worked with, I've had to reintegrate subsets myself because though the authors published the embeddings of their data (e.g. cell1 is at position X and Y on PC1 and PC2), they flat out refused to publish the loadings (e.g. PC1 is made up of GeneX, GeneY, ...) making it obscenely hard to project your own data on to these reference Atlas's.
Yes, I'm disillusioned in general when I see these papers.
I suspect a lot of the back to brick is actually more phase one of dealing with damp. Once its dried out a lot of houses in my area then go and get coloured insulating render. So it's not even paint anymore but the actual material is coloured.
