I am interested to retain more what I read. This is my attempt at doing. For every online news article that I read, I am going to write a short TL;DR here on Caspershire Meta. I am planning to make a regular series out of this: Aizan reads stuff.
The Cloud Is Just Someone Else’s Computer by Jeff Atwood. The premise is about using co-location (co-loc) instead of VPS or dedicated server to host website. By using his scooter computer, he claimed that he would only spend around $2,000 for 3 years of hosting, as opposed to using about-the-same VPS plan on Digital Ocean, costing around $5,000. Bonus: the co-loc PC runs faster and beefier.
Scientists' ‘Craziest Experiment Possible’ Actually Works On Mosquitoes. The group used A. aegypti mosquitoes as their model, and they fed diets contain ATP (that ATP?). The paper is open-access, btw, and they did some really interesting assays. The premise is that how to use some drugs to suppress their desire to eat.
We have a new global tally of the insect apocalypse. It’s alarming. Ratio insect to human is around 17:1. As for the extinction, butterflies are being hit the hardest, followed by grasshoppers & crickets. Note that this study didn’t include regions other than Europe and North America. What killed these insects? Multifactorial. In short, human activity is to blame. Here is something similar from the Post.
802.11ax and 802.11ay explained. My friend, Bawang, tweeted this to me. Soon I am going to write this on AmanzMY. The 802.11ay is going to sport wireless gigabit. I can’t quite find something really interesting with 802.11ax variant. I guess I will have to read more into this.
The Wild Experiment That Showed Evolution in Real Time. An interesting experiment focusing on the fur color of the mice. The mice, over time, developed lighter color against the light-sand or darker in darker soils. Why the fur? Well, they won’t get caught up by predators by blending in.
Machine learning spots natural selection at work in human genome. Another natural selection article. Algorithms were developed by people from MIT/Broad, and they flagged > 20,000 single nucleotide mutations (SNPs). The data that they worked on was from the 1,000 Genomes Project. They developed algorithms good for mining data in silico, but still need to go through validation in vitro or in vivo.
One particular interesting paragraph: Several other researchers are training deep-learning algorithms to search for signs of adaptation in genomes. A deep-learning model developed by Kern suggests that at first, most mutations in humans are neither beneficial nor harmful. Rather, they seem to drift along in populations, increasing natural genetic variability, and only become more frequent when a change in the environment gives people who possess the mutation an evolutionary edge.