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For those interested in drone technology.


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You are on the PRO RobotsThe best drone with a camera. What quadcopter to buy? In this issue we will tell you about the top of the coolest quadcopters.
Today’s video is about drones, as drones are rapidly becoming the most popular hobby. Today you can buy a drone on aliexpress, make your own hands or find one at almost any hardware store, and new drones appear there every day. Although drones can be treated as toys, a really cool quadcopter is a serious investment and you want to choose the best one for yourself.

0:00 announcement.
0:23 DJI Air 2S
01:54 DJI Mini 2
03:03 DJI Mavic 2 Pro.
04:14 Skydio 2
05:00 Parrot Anafi.
06:02 Potensic Dreamer Pro 4K
06:32 Syma X20
07:03 Propel X-Wing.
07:45 DJI Ryze Tello.
08:33 Emax Tinyhawk 2
09:03 DJI FPV
09:40 PowerVision PowerEgg X

#prorobots #robots #robot #future technologies #robotics.

More interesting and useful content:
✅ Elon Musk Innovation https://www.youtube.com/playlist?list=PLcyYMmVvkTuQ-8LO6CwGWbSCpWI2jJqCQ
✅Future Technologies Reviews https://www.youtube.com/playlist?list=PLcyYMmVvkTuTgL98RdT8-z-9a2CGeoBQF
✅ Technology news.

#prorobots #technology #roboticsnews.

PRO Robots is not just a channel about robots and future technologies, we are interested in science, technology, new technologies and robotics in all its manifestations, science news, technology news today, science and technology news 2021, so that in the future it will be possible to expand future release topics. Today, our vlog just talks about complex things, follows the tech news, makes reviews of exhibitions, conferences and events, where the main characters are best robots in the world! Subscribe to the channel, like the video and join us!

## JOURNAL OF THE AMERICAN CHEMICAL SOCIETY • JUN 4, 2021.

# *A lovely single step bio-inspired process with some interesting complex benefits particularly for humans on Mars.*

*by holly ober, university of california — riverside*

A team led by UC Riverside engineers has developed a catalyst to remove a dangerous chemical from water on Earth that could also make Martian soil safer for agriculture and help produce oxygen for human Mars explorers.

Perchlorate, a negative ion consisting of one chlorine atom bonded to four oxygen atoms, occurs naturally in some soils on Earth, and is especially abundant in Martian soil. As a powerful oxidizer, perchlorate is also manufactured and used in solid rocket fuel, fireworks, munitions, airbag initiators for vehicles, matches and signal flares. It is a byproduct in some disinfectants and herbicides.

Because of its ubiquity in both soil and industrial goods, perchlorate is a common water contaminant that causes certain thyroid disorders. Perchlorate bioaccumulates in plant tissues and a large amount of perchlorate found in Martian soil could make food grown there unsafe to eat, limiting the potential for human settlements on Mars. Perchlorate in Martian dust could also be hazardous to explorers. Current methods of removing perchlorate from water require either harsh conditions or a multistep enzymatic process to lower the oxidation state of the chlorine element into the harmless chloride ion.

Doctoral student Changxu Ren and Jinyong Liu, an assistant professor of chemical and environmental engineering at UC Riverside’s Marlan and Rosemary Bourns College of Engineering, took inspiration from nature to reduce perchlorate in water at ambient pressure and temperature in one simple step.

Ren and Liu noted anaerobic microbes use molybdenum in their enzymes to reduce perchlorate and harvest energy in oxygen-starved environments.

“Previous efforts in constructing a chemical molybdenum catalyst for perchlorate reduction have not been successful,” Liu said. “Many other metal catalysts either require harsh conditions or are not compatible with water.”

The researchers tried to emulate the complicated microbial perchlorate reduction process with a simplified approach. They found by simply mixing a common fertilizer called sodium molybdate, a common organic ligand called bipyridine to bind the molybdenum, and a common hydrogen-activating catalyst called palladium on carbon, they produced a powerful catalyst that quickly and efficiently broke down the perchlorate in water using hydrogen gas at room temperature with no combustion involved.

“This catalyst is much more active than any other chemical catalyst reported to date and reduces more than 99.99% of the perchlorate into chloride regardless of the initial perchlorate concentration,” Ren said.

The new catalyst reduces perchlorate in a wide concentration range, from less than 1 milligram per liter to 10 grams per liter. This makes it suitable for use in various scenarios, including remediating contaminated groundwater, treating heavily contaminated wastewater from explosives manufacturing, and making Mars habitable.

“A convenient catalytic reduction system may help harvest oxygen gas from perchlorate washed from the Martian soil when the catalyst is coupled with other processes,” Liu said.

## ORIGINAL PAPER

Changxu Ren et al, **A Bioinspired Molybdenum Catalyst for Aqueous Perchlorate Reduction**, Journal of the American Chemical Society (2021). DOI: 10.1021/jacs.1c00595

https://pubs.acs.org/doi/10.1021/jacs.1c00595

Thanks to Zoomers of the Sunshine Coast BC, Bio — A.I., Sunshine Coast Climate Action Network & Folkstone Design Inc.

#Perchlorate #Mars #Oxygen #CatalyticReduction #WasteWater #Fuel #Food #SpaceX #ElonMusk #Mars #EnvironmentalMediation #Environment.

New EPFL research has found that almost half of local Twitter trending topics in Turkey are fake, a scale of manipulation previously unheard of. It also proves for the first time that many trends are created solely by bots due to a vulnerability in Twitter’s Trends algorithm.

Social media has become ubiquitous in our modern, daily lives. It has changed the way that people interact, connecting us in previously unimaginable ways. Yet, where once our social media networks probably consisted of a small circle of friends most of us are now part of much larger communities that can influence what we read, do, and even think.

One influencing mechanism, for example, is “Twitter Trends.” The platform uses an algorithm to determine hashtag-driven topics that become popular at a given point in time, alerting to the top words, phrases, subjects and popular hashtags globally and locally.

The researchers started with a sample taken from the temporal lobe of a human cerebral cortex, measuring just 1 mm3. This was stained for visual clarity, coated in resin to preserve it, and then cut into about 5300 slices each about 30 nanometers (nm) thick. These were then imaged using a scanning electron microscope, with a resolution down to 4 nm. That created 225 million two-dimensional images, which were then stitched back together into one 3D volume.

Machine learning algorithms scanned the sample to identify the different cells and structures within. After a few passes by different automated systems, human eyes “proofread” some of the cells to ensure the algorithms were correctly identifying them.

The end result, which Google calls the H01 dataset, is one of the most comprehensive maps of the human brain ever compiled. It contains 50000 cells and 130 million synapses, as well as smaller segments of the cells such axons, dendrites, myelin and cilia. But perhaps the most stunning statistic is that the whole thing takes up 1.4 petabytes of data – that’s more than a million gigabytes.

It’s either some obscure fluid effect or black magic.


Just when I think I’ve seen every possible iteration of climbing robot, someone comes up with a new way of getting robots to stick to things. The latest technique comes from the Bioinspired Robotics and Design Lab at UCSD, where they’ve managed to get a robot to stick to smooth surfaces using a vibrating motor attached to a flexible disk. How the heck does it work?

The Beijing Academy of Artificial Intelligence (BAAI) researchers announced this week a natural language processing model called WuDao 2.0 that, per the South China Morning Post, is more advanced than similar models developed by OpenAI and Google.

The report said WuDao 2.0 uses 1.75 trillion parameters to “simulate conversational speech, write poems, understand pictures and even generate recipes.” The models developed by OpenAI and Google are supposed to do similar things, but they use fewer parameters to do so, which means WuDao 2.0 is likely better at those tasks.

Biobots could help us with new organs! 😃


Computer scientists and biologists have teamed up to create a creature heretofore unseen on Earth: a living robot. Made from the cells of frogs and designed by artificial intelligence, they’re called xenobots, and they may soon revolutionize everything from how we fight pollution to organ transplants.

#Xenobots #Moonshot #BloombergQuicktake.
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When Open AI’s GPT-3 model made its debut in May of 2020, its performance was widely considered to be the literal state of the art. Capable of generating text indiscernible from human-crafted prose, GPT-3 set a new standard in deep learning. But oh what a difference a year makes. Researchers from the Beijing Academy of Artificial Intelligence announced on Tuesday the release of their own generative deep learning model, Wu Dao, a mammoth AI seemingly capable of doing everything GPT-3 can do, and more.

First off, Wu Dao is flat out enormous. It’s been trained on 1.75 trillion parameters (essentially, the model’s self-selected coefficients) which is a full ten times larger than the 175 billion GPT-3 was trained on and 150 billion parameters larger than Google’s Switch Transformers.

In order to train a model on this many parameters and do so quickly — Wu Dao 2.0 arrived just three months after version 1.0’s release in March — the BAAI researchers first developed an open-source learning system akin to Google’s Mixture of Experts, dubbed FastMoE. This system, which is operable on PyTorch, enabled the model to be trained both on clusters of supercomputers and conventional GPUs. This gave FastMoE more flexibility than Google’s system since FastMoE doesn’t require proprietary hardware like Google’s TPUs and can therefore run on off-the-shelf hardware — supercomputing clusters notwithstanding.