> Body mass index (BMI) was calculated from measured weight and height and categorized into 4 groups (<18.5, 18.5–24.9, 25–29.9, and ≥30 kg/m2). Hypertension was defined as systolic blood pressure ≥140 mm Hg and/or diastolic blood pressure ≥90 mm Hg, or the use of antihypertensive medication. Diabetes was identified through self-reported diagnosis, medication usage, and registry records. The intake of lipid-lowering drugs was self-reported. Baseline blood lipoproteins were only available in 4,549 participants and, therefore, not included as covariates. The APOE genotype was determined based on 2 single-nucleotide variants, rs429358 and rs7412, which define the ε2, ε3, and ε4 alleles. Participants carrying at least 1 ε4 allele were classified as APOE ε4 carriers.
The most magical part of this transform is the search! First learned about this in a bioalgorithms course, and the really cool property is that for a string length l, you can search for the string in O(l) time. It has the same search time complexity of a suffix tree with O(n) space complexity (with a very low constant multiple). To this day it may be the coolest algorithm I've encountered.
I encountered the search version of this, which is turned suffix arrays, in grad school and was so taken by them I incorporated them as the primary search mechanism for the pi searcher. 25 years later it's still the best way to do it. Incredible insight behind bwt and suffix arrays.
Mostly because In the 1980's the mergers guidelines at the FTC were dramatically narrowed explicitly to reduce antitrust enforcement and allow consolidation. It basically kicked off the wave of Corporate Raiders like Carl Icahn that dominated the 80s financial world (Gordon Gecko was based of this model of individual). Since then we've seen consistent, steady consolidation of almost every industry.
Matt Stoller writes about this frequently, and does an incredible job highlighting everywhere it's happening and what the downstream consequences are. I'm surprised he's not more popular on HN.
One of the most unambiguously good things Biden did during his term is appoint the actual most aggressive antitrust individual in the modern political environment to be head of the FTC, and a similar profile in Jonathan Kanter to the DOJ.
PBS Spacetime has a fantastic video on the Higgs Field that explains it about one level deeper that typical pop science, and answers some of the questions I'm seeing in this thread, include "why did the field switch on suddenly?" and "Why is the Higgs Field different from other fields"
I can also add this set of articles from Matt Strassler which explains it all with surprisingly simple math. It really is quite understandable and I wish more pop-sci discussions of the subject threw in a few equations now and then to explain such stuff.
Sean Carroll produces a great deal of content for people that want a bit more rigorous explanation rather than the leaky metaphors of most popsci. He often delves into equations and technical details, but keeps it at a level mostly understandable for someone who has basic scientific understanding, but isn't a professional/academic. I spend many hours every month listening to him and recommend his content every chance I get.
Carroll's latest book "Quanta and Fields: The Biggest Ideas in the Universe" is about all this quantum field theory, and I think it perfectly covers the gap between pop-sci and academic material for people with some math exposure.
While other authors just keep shy of equations and thus need to resort to simplified analogies, Carroll is not afraid of throwing a good share of math stuff and explaining the rationale from one equation to the other, while avoiding the really hard parts ("solving this equation tortures undergrad physics students for a year, but we won't be doing that")
Just to go off these great works, there's a wonderful academic piece on the interaction between cosmology, quantum particles, and the higgs field here:
https://www.youtube.com/watch?v=FYJ1dbyDcrI
I did 2 rounds (6 weeks) of BEP a few years back. I'd planned to do some technical reading while I was being treated. About 3 weeks in I was unable to really understand or learn any of it.
It took about 4 months before I was full speed again, but I definitely did make it back to 100%.
Around the same time, my grandfather was diagnosed with AML and had something like 6 months of chemo-- he's also 100% back to full mental capacity.
> Body mass index (BMI) was calculated from measured weight and height and categorized into 4 groups (<18.5, 18.5–24.9, 25–29.9, and ≥30 kg/m2). Hypertension was defined as systolic blood pressure ≥140 mm Hg and/or diastolic blood pressure ≥90 mm Hg, or the use of antihypertensive medication. Diabetes was identified through self-reported diagnosis, medication usage, and registry records. The intake of lipid-lowering drugs was self-reported. Baseline blood lipoproteins were only available in 4,549 participants and, therefore, not included as covariates. The APOE genotype was determined based on 2 single-nucleotide variants, rs429358 and rs7412, which define the ε2, ε3, and ε4 alleles. Participants carrying at least 1 ε4 allele were classified as APOE ε4 carriers.