The disinformation landscape of this conflict is insane. This article paints a decidedly optimistic picture, however I fear the reality is far more bleak.
Unreliable casualty numbers aside, Russia simply has way more men, and can eventually attrite Ukraine into a demographic death spiral. Indeed, with the exodus of ~20% of its population since the start of the war, this demographic trajectory may now be inexorable. Eastern Ukraine, where much of the most fertile land is, and where most of the fighting has occurred, is now likely littered with bomb parts and unexploded ordinances, and the prospect of the jackals of the American arms industry turning it into a live weapons laboratory is particularly grim.
Russia simply has way more men, and can eventually attrite Ukraine into a demographic death spiral.
Not so, because to fully subjugate another country (that is strongly determined to defend itself) a mere 3x population differential, as Russia has over Ukraine, is not sufficient. Really you need more like 10x. This is one of the main reasons why nearly all the European colonial efforts, and American efforts in Vietnam and Afghanistan ultimately failed.
And why Israel knows it will never be able to subjugate the population of Gaza for any length of time.
The jackals of the American arms industry turning it into a live weapons laboratory is particularly grim.
Basically another version of the "Dontcha know, it's really the West's fault that we have this conflict in the first place; poor misunderstood Russia was simply forced to defend itself, you see" line.
It's supremely naive to think that Russia wants to fully subjugate Ukraine and instead of allowing one to observe clearly how this war is unfolding, such thinking creates a false reality that is ripe for exploitation and susceptible to propaganda.
The Russians will simply grab and keep the oblasts with large ethnic Russian populations and ensure that the rest of Ukraine remains a broken state. They've already captured 20% of Ukraine and if this war continues, this will certainly increase, but will not reach even 50%. One would be stupid to think that Putin is interested in another Afghanistan.
It's supremely naive to think that Russia wants to fully subjugate Ukraine
You're splitting hairs, and basically putting up a strawman defense here.
Whether Russia intended to subjugate about 70 percent of Ukraine's territory (which by all indications was its initial goal at the outset, and probably still is), or 100 percent, is irrelevant to the main point under discussion.
Your words were that Russia "can eventually attrite Ukraine into a demographic death spiral", implying some sort of eventual decisive victory over Ukraine (as opposed to holding on to a few Oblasts).
The latter it might be able to do, but the former - no.
One would be stupid to think that Putin is interested in another Afghanistan.
He has already racked up 4x the total casualties of the Afghan occupation in just 2 years. We all know it isn't what he "wanted" but it's the situation he has created for himself, and his people, nonetheless.
The variants in ClinVar will have genomic coordinates associated with them, each given with respect to a particular reference genome, e.g.
GRCh38 - chr2:41785474-41785474
or something like that.
You will need to align your FASTQ to one of these reference genomes using a short-read aligner such as BWA-MEM (assuming your genome was sequenced using something like Illumina NGS) to produce a BAM (binary alignment map) file, and then from there use a variant calling tool such as GATK's HaplotypeCaller or Google's DeepVariant to produce a VCF (variant call format) file, which will contain the mutations in your genome. Then you can see if any of the mutations found in your genome match those in ClinVar.
As humans are diploid, you will also need to be cognizant of the zygosity of each mutation, i.e., whether you have a particular mutation on just one of your two chromosomal homologs (heterozygote) or both (homozygous mutant), as this may affect whether or not the mutation is of concern, the variant caller will attempt to determine this for you and report it in the VCF file.
Unfortunately, the preponderance of very low value research in the literature puts a significant burden on the scientists who have to sift through a lot of garbage to find what they're looking for. Even if the work is ostensibly correct (much of it is not), it really doesn't do anyone much good, except for the authors of course. But now every undergraduate and every parent's vanity project at Andover wants a first author contrib., so here we are.
I think language models will help us sift through the garbage. I have a hard time finding answers using Google (too much SEO garbage), but ChatGPT does a pretty good job of filtering the noise. It's not perfect, but it saves lots of time vs. Google.
It looks like from the preprint that they sequenced the Y chromosome of HG002, which was one of the original 1000 genomes samples from way back in the day, still held in deep freeze at a number of biobanks.
Short-read sequencing data is a notoriously bad datatype for reconstructing the low-complexity / repetitive regions of genomes, so up until recently the most commonly used reference genomes have left many of these regions "dark". According to the preprint, the Y chromosome has the highest density of these low-complexity regions. It's also something of a bioinformatic nuisance when constructing a generic human reference genome, as it's only present in 50% of the population.
Well if you ran that on a normal processor it would take you less than 10s and that's including the 9s it takes for python to load and numpy to import.
There's a lot of optimism in this thread, but does DFT (or any theoretical model really) actually have much predictive value in quantum chemistry? I've always gotten the impression that in this field the proof is in the pudding.
There are so many bad DFT papers out there because it's cheap to do DFT compared to growing and measuring samples carefully. DFT is notoriously unreliable as a predictive tool in strongly correlated systems, though when electron correlations are small it works well. I mean, I want this to be true, but I put little stock in DFT that doesn't calculate observables. So yes, you're right.
The prof who taught us computational chemistry during masters basically said 90% of published results cannot be trusted and most people in this field don't really know what they're doing. Results can look seemingly good and stil be way off from reality, even for very simple molecules. This is a crystal lattice. I take dft and other computational results with a big grain of salt.
GGA-DFT (+ some corrections) used here seems quite ok to me for this system. For more trust into this, I would like similar calculations with other methods to see how similar or different they are. LDA-DFT will most likely not be great (as in most cases), but I would be very interested in some DFT+GW calculations, even though LK99 might not be it's strength.
But it isn't used for its predictive value here, it is used to verify that which is already known (or at least, strongly suggested to be known). That's different than coming up with a compound based on some hunch, this is modeling a compound with a known structure to check that for properties consistent with the expectations.
That's radically different from searching for a compound with particular properties, that is a much more error prone process.
Explaining why is valuable. The band gap described in this paper is common to other high temperature superconductors. While I remain skeptical, this gives a glimmer of hope, and if the material is indeed superconducting, analysis like this is useful in further understanding high temperature superconductors. If it's not superconducting, then this research may yet be interesting -- if the analysis is correct, it would be interesting to know what's different.
In any case it's a pretty silly contrivance, how about the oil age? or the silicon age? Both of those are likely to remain more impactful than the LK-99 age, in the event that it does turn out to be an ambient temp/pressure superconductor.
Good lord, AI engineers get paid a median salary of $243,500, while non-AI engineers only get paid a median of $166,750, how can it be so much more? Is it because AI jobs are more concentrated in big tech?
The knowledge is harder to come by, and the field is (relatively) new. You need a fusion of data engineering, math, software engineering, and data analysis. Plus the ability to read and implement esoteric papers hot off the press, or in some cases innovate a new technique/module/architecture that hasn't been done before.
Oh, and you need to be able to do all the above _quickly_.
What's nice about it versus SWE is that you can totally ship hot garbage, doesn't have to be optimal at all, just "fast enough" and cheap enough.
Unreliable casualty numbers aside, Russia simply has way more men, and can eventually attrite Ukraine into a demographic death spiral. Indeed, with the exodus of ~20% of its population since the start of the war, this demographic trajectory may now be inexorable. Eastern Ukraine, where much of the most fertile land is, and where most of the fighting has occurred, is now likely littered with bomb parts and unexploded ordinances, and the prospect of the jackals of the American arms industry turning it into a live weapons laboratory is particularly grim.