https://arxiv.org/abs/2005.12505
Very interesting research on voting mechanism. They built a theory to understand how the freemason member selection procedures shape the community. The Freemason only integrates a member if the member is accepted by all of the current members.
Very interesting research on voting mechanism. They built a theory to understand how the freemason member selection procedures shape the community. The Freemason only integrates a member if the member is accepted by all of the current members.
Nature Index’s top five science cities, by the numbers
https://www.nature.com/articles/d41586-020-02576-y
https://www.nature.com/articles/d41586-020-02576-y
Nature
Nature Index’s top five science cities, by the numbers
Sizing up the success of the world’s science hotspots.
Gangster capitalism and the American theft of Chinese innovation – TechCrunch
https://techcrunch.com/2020/09/20/gangster-capitalism-and-the-american-theft-of-chinese-innovation/
https://techcrunch.com/2020/09/20/gangster-capitalism-and-the-american-theft-of-chinese-innovation/
Maternal microbes support fetal brain wiring
https://www.nature.com/articles/d41586-020-02657-y
https://www.nature.com/articles/d41586-020-02657-y
Nature
Maternal microbes support fetal brain wiring
Metabolites made by bacteria signal to the developing mouse brain.
JupyterCon 2020 - Conference Schedule
https://cfp.jupytercon.com/2020/schedule/tutorial-sessions/
https://cfp.jupytercon.com/2020/schedule/tutorial-sessions/
Disney will lay off 28,000 theme park workers as the pandemic continues to ravage its business (DIS)
https://www.businessinsider.com/disney-layoffs-theme-parks-disneyland-disneyworld-2020-9
https://www.businessinsider.com/disney-layoffs-theme-parks-disneyland-disneyworld-2020-9
Business Insider
Disney will lay off 28,000 workers as the pandemic continues to ravage its theme park business
Disney will lay off 28,000 theme park workers as Disneyland in California remains closed, and other parks open with limited capacity during the pandemic.
Synopsis: No Sterile Neutrinos from Eight Years of IceCube
http://link.aps.org/doi/10.1103/Physics.13.s126
http://link.aps.org/doi/10.1103/Physics.13.s126
Physics
No Sterile Neutrinos from Eight Years of IceCube
An analysis of more than 300,000 muon neutrino detections provides no evidence of sterile neutrinos—a finding at odds with other experiments.
TuSimple Hires Former FMCSA Official Jim Mullen
https://www.ttnews.com/articles/tusimple-hires-former-fmcsa-official-jim-mullen
https://www.ttnews.com/articles/tusimple-hires-former-fmcsa-official-jim-mullen
Transport Topics
TuSimple Hires Former FMCSA Official Jim Mullen
Jim Mullen, former acting administrator of the Federal Motor Carrier Safety Administration, has taken a position at TuSimple, a company that specializes in autonomous driving technology for trucks.
https://stackoverflow.com/questions/16047306/how-is-docker-different-from-a-virtual-machine/36368012#36368012
"Docker for Mac uses https://github.com/moby/hyperkit to emulate the hypervisor capabilities and Hyperkit uses hypervisor.framework in its core. Hypervisor.framework is Mac's native hypervisor solution. Hyperkit also uses VPNKit and DataKit to namespace network and filesystem respectively."
hmmm I guess this is why docker on mac uses a lot of resources compared to its linux version
"Docker for Mac uses https://github.com/moby/hyperkit to emulate the hypervisor capabilities and Hyperkit uses hypervisor.framework in its core. Hypervisor.framework is Mac's native hypervisor solution. Hyperkit also uses VPNKit and DataKit to namespace network and filesystem respectively."
hmmm I guess this is why docker on mac uses a lot of resources compared to its linux version
Stack Overflow
How is Docker different from a virtual machine?
I keep rereading the Docker documentation to try to understand the difference between Docker and a full VM. How does it manage to provide a full filesystem, isolated networking environment, etc. wi...
Hypergraph is a decentralized tool to help researchers manage their work. Everything in your research, from notes to data to publications to proposals , is linked together for better discovery and reproducibility.
https://greenelab.github.io/scihub-manuscript/v/8fcd0cd665f6fb5f39bed7e26b940aa27d4770ba/
I am a lit bit scared whenever I think about how it accesses the papers. It is a black box and we have no idea if scihub is doing this in a way that is accepted by every researcher.
On the other hand, it is not easy to live without scihub. There are legal alternatives like unpaywall and kopernio but they are way behind the game.
What shall we do? Require the author of scihub to open source the code? Continue using a black box that may hurt other people? I don't know.
I am a lit bit scared whenever I think about how it accesses the papers. It is a black box and we have no idea if scihub is doing this in a way that is accepted by every researcher.
On the other hand, it is not easy to live without scihub. There are legal alternatives like unpaywall and kopernio but they are way behind the game.
What shall we do? Require the author of scihub to open source the code? Continue using a black box that may hurt other people? I don't know.
greenelab.github.io
Sci-Hub provides access to nearly all scholarly literature
What a boring Friday. I started to experiment on a plastic ring to find out the probabilities of it standing on the edges when dropped from heights. The diameter of this ring is much larger than its width (diameter/width ~ 2). In the beginning, the result was trivial. Then the results started to look weird to me. The probability of it standing on its edges is higher than falling flat down.
Is this an angular momentum problem?
(Why didn't I continue with the experiment? I stepped on it and it shattered.......)
Is this an angular momentum problem?
(Why didn't I continue with the experiment? I stepped on it and it shattered.......)
Forwarded from Parallel Experiments (Linghao)
Staffeng
Work on what matters
Stories of folks reaching Staff Engineer roles.
Signatures of a liquid–liquid transition in an ab initio deep neural network model for water | PNAS
https://www.pnas.org/content/early/2020/10/01/2015440117
https://www.pnas.org/content/early/2020/10/01/2015440117
PNAS
Signatures of a liquid–liquid transition in an ab initio deep neural network model for water
Water is central across much of the physical and biological sciences and exhibits physical properties that are qualitatively distinct from those of most other liquids. Understanding the microscopic basis of water’s peculiar properties remains an active area…