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subnaught

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musician, scientist, human being.

http://subnaught.org http://subnaught.org/supercollider

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www.nypl.org 8y ago

The Myth of Name Changes at Ellis Island

subnaught
3pts0
www.cnbc.com 8y ago

Meg Whitman Is Benchmark Favorite for Uber CEO

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2pts0
www.villagevoice.com 8y ago

The Extropians (2005)

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pubs.acs.org 9y ago

Carbon nanotubes as true random number generators

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www.wsj.com 9y ago

Mark Zuckerberg Hits the Road

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www.telegraph.co.uk 9y ago

Self-driving Volvos struggle to deal with kangaroos

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2pts0
bugs.python.org 9y ago

Tau constant now included in Python

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inference-review.com 9y ago

Higgs on the Moon

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www.guernicamag.com 9y ago

Marc Ribot: Google is hurting musicians

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story.californiasunday.com 9y ago

Letter from a Drowned Canyon

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www.bloomberg.com 9y ago

Apple to Begin Testing Self-Driving Cars in California

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longreads.com 9y ago

A David Grann Reading List

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www.nature.com 9y ago

Science Needs Reason to Be Trusted

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www.theopennotebook.com 9y ago

Visions of Future Physics, Annontated

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blogs.agu.org 9y ago

The scale of damage to the Oroville spillway

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cdec.water.ca.gov 9y ago

Oroville Dam Resource Center

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blogs.agu.org 9y ago

The enormous scale of the erosion problem at the Oroville Dam site

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www.newyorker.com 9y ago

The Atomic Origins of Climate Science

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www.facebook.com 9y ago

Mark Zuckerberg statement on Trump immigration order

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medium.com 9y ago

Trump, Putin and the Pipelines to Nowhere

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www.nytimes.com 9y ago

How Russian Cyberpower Invaded the U.S

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www.theverge.com 9y ago

FCC says AT&T and Verizon ‘harm consumers’ with free data schemes

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blogs.ams.org 9y ago

What Should Mathematicians Do Now?

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exclaim.ca 9y ago

R.I.P. Electronic Music Pioneer Jean-Claude Risset

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www.worldscientific.com 9y ago

Why China Should Build the Great Collider

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newrepublic.com 9y ago

Elena Ferrante, Private Novelist

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gizmodo.com 9y ago

This Smartwatch Powered by Your Body Heat Never Needs Charging

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en.wikipedia.org 9y ago

Moissanite

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aeon.co 9y ago

On epigenetics: we need both Darwin’s and Lamarck’s theories

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www.scientificamerican.com 9y ago

Trump Picks Top Climate Skeptic to Lead EPA Transition

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78pts39

That's an apples-and-oranges comparison. The system you cite differs from the one under discussion in several ways; the most important of which are:

1. The cited system does not include a light-harvesting component. It merely postulates that the required energy could be generated from photovoltaics. This would introduce additional cost and complexity along with an efficiency hit.

2. The cited system comprises a bacterium in conjuction with an electrode-supported catalyst, whereas the system under discussion is solely an engineered bacterium.

Finally, it is not correct to refer to cadmium and cysteine as feedstocks. They are components of the catalyst, and they are not consumed during catalysis. The only feedstocks for both systems are CO2 and water.

That said, relying on a fuel source that requires CO2 as input seems just as potentially destabilizing to the global carbon cycle as relying on a fuel source that produces CO2 as byproduct.

Not really. Using CO2 to generate a fuel which then liberates CO2 when it is consumed ends up being CO2-neutral, which is exactly the way to go.

You've got a lot of it right, but you're missing the key advance described here, which--if true--is pretty wild.

Taking a step back, in 2016, this group did cover a bacterium with tiny semiconductor nanoparticles (specifically CdS) just as you say. That work is described here: http://www.pnas.org/content/113/42/11750.full In short, the semiconductors act as mini-solar cells, converting light into electrical current. The bacteria then use that electricity to convert CO2 into acetic acid. That already is pretty cool.

However, what they claim now is that they don't even need to make the semiconductor nanoparticles. They can simply grow the bacteria in an environment containing cadmium and sulfur sources and the bacterium will synthesize it's own cadmium sulfide coat, and use it for photosensitization.

This is really pretty wild. Bacteria will often incorporate various elements from their host medium, but the generally use them to make biomolecules, not semiconductors. Right now, this is just being presented at a conference, but it will be very interesting to see the details when the full paper comes out.

That may be the origin of this particular phrasing, but the idea is much older:

In 1973, the artist Richard Serra made a film called Television Delivers People which declares "You are the product of TV" [0]

Key to Noam Chomsky's _Manufacturing Consent_ (1988) is the idea that advertising-supported media caters to the desires of the advertiser, not the media consumer [1]

[0] https://en.wikipedia.org/wiki/Television_Delivers_People [1]: https://en.wikipedia.org/wiki/Manufacturing_Consent

Some background and context from someone tangentially related to the field:

1. The overall idea here is to take an intermittent energy source (e.g. solar power) and "store" it as chemical fuel, in this case hydrogen and oxygen. This is what plants do, and we can also view fossil fuels as resulting from the "storage" of millions of years of solar energy. Note also that you get the water back when you burn the hydrogen, so there is no net consumption of water, it's just a carrier.

2. While you can split water without a catalyst, most of the energy gets wasted as heat, so this is not a great way to go if you're trying to do energy storage.

3. Efficient catalysts exist for this reaction, but they are based on rare and expensive metals, typically Pd, Pt, and Ir. As a result, there has been a search for catalysts involving "first-row" metals such as Fe, Co, Ni, etc.

4. There are variety of metrics for an electrocatalyst (efficiency, stability, cost, etc), but it's a fair bet that if this were significantly better than state-of-the-art, it would be in Science or Nature rather than PNAS.

I am interested as to why you chose to focus on reaction prediction. As you acknowledge in the introduction, the acquistion of this skill is a routine part of graduate education in synthetic chemistry.

On the other hand, the key difficulty in synthetic chemistry, and the one that occupies the majority of a chemist's time is the identification of the correct reagent(s), the correct solvent, and the correct time, temperature, and concentration such that the desired reaction proceeds in a convenient amount of time and with the correct chemo- and regio-selectivity, that the reaction conditions are tolerated by the rest of the molecule, and that the product can be easily isolated from the reaction byproducts.

In my opinion, as long as these problems remain, then being able to turn retrosynthetic analysis over to a machine appears to me to provide little benefit.

Tea (1999) 11 years ago

This is absolutely incorrect. The best thing you can do to enhance your tea-drinking experience is to buy good tea, and good tea is invariably brewed off the boil, usually somewhere between 170-200F, depending on the tea.[0] Higher temperatures will extract too much tannin at the expense of aromatics. The British generally drink shit tea and then add milk to it, which is why they can get away with brewing it at 212F.

Remember that the British experience with tea dates back only to the 17th century, whereas the Chinese and Japanese have had much longer to refine the growing, processing, and drinking of tea.

[0] http://www.itoen.com/preparing-tea

The same things go on in America, just under slightly different guises, I would say. This is a not-uncommon pattern:

0) There is a problem that needs to be fixed.

1) Boss recommends A

2) Engineer knows A won't work, but they try it anyway

3) A doesn't work, so they stay up late implementing B. (Of course, they wouldn't have had to stay up late had they just been allowed to implement B first...)

4) B works

5) Boss takes the credit

6) After years of making the boss look good, engineer gets promoted

It's really a shame that they've chosen not to open source their algorithm. They use data from the 4km (hi-res) NAM model, which can be found here[0]. The GRIB files can be read and exported to CSV using Panopoly [1]. They mention using RH at different heights along with low, medium, and high cloud cover (LCDC, MCDC, HCDC). I wanted to make a simple model and train it on Instagram data for #sunset tag frequency for a given location, but Instagram just closed access to their global data. If someone else has access and wants to run with this, it could be fun...

[0] http://nomads.ncep.noaa.gov/cgi-bin/filter_hiresconus.pl

[1] http://www.giss.nasa.gov/tools/panoply/