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Cancer patients' own cells used in 3D printed tumours to test treatments:
TEL AVIV, Aug 18 (Reuters) - Researchers have used brain cancer patients' own cells in a form of 3D printing material to make a model of their tumour to test the efficacy of potential treatments before using them for real inside the body.
The scientists extract "a chunk" of the tumour from the brain of a patient with glioblastoma [...] and use it to print a model matching their MRI scans, said Professor Ronit Satchi-Fainaro, who led the research at Tel Aviv University.
The patient's blood is then pumped through the printed tumour, made with a compound that mimics the brain, followed by a drug or therapeutic treatment.
While previous research has used such "bioprinting" to simulate cancer environments, the Tel Aviv University researchers say they are the first to print a "viable" tumour.
[...] A treatment is deemed promising if the printed tumour shrinks or if it lowers metabolic activity against control groups.
The article has photos and a short video of the process.
Also at: Nerdist.
Journal Reference:
Lena Neufeld, Eilam Yeini, Noa Reisman, et al. Microengineered perfusable 3D-bioprinted glioblastoma model for in vivo mimicry of tumor microenvironment [open], Science Advances (DOI: 10.1126/sciadv.abi9119)
[Update #2; 2021-08-23 02:35:27 UTC]
So, mechanicjay responded to the bat signal, and "did a kill on every process that referenced slashd and started the service."
We think that should do the trick; please reply here or in the #soylent channel on IRC.
Again, many MANY thanks for your patience and understanding!
[Update #1; 2021-08-23 01:41:16 UTC]
"Constants aren't; variables won't." So goes an old adage. Seems to be the case for us, as well. My efforts to get comment counts to update and to get get mod points to be distributed have been fruitless. I've reached out to mechanicjay to see if he is available to take a look and lend a hand. So far, it appears that mod points were not distributed at 00:10 UTC this [Monday] morning.
I apologize for the disruption. --martyb
Original story follows below the fold.
As if nothing else of importance was going on with the site pertaining to moderation...
We discovered this morning that slashd (think slashdot's creation of cron way back in slashdot's early days) did not run to completion overnight. And, obviously, it chose to die right when it was handing out mod points for the day.
(NB: Rehash (the code that runs the site) is a fork of a version of slashcode. That code was open-sourced a couple years before we grabbed it. It also needed a great deal of work to get into an actually-functioning state.)
It actually handed out some mod points. It wasn't until we received reports that some people failed to get mod points that we realized there was a problem. I restarted slashd. Problem solved, right?
That would be easy. Who wants easy on a Sunday? Apparently easy was not in the cards for today.
We later learned that things were left in an interim state — some users got some mod points and others did not get any. Of course, I did not realize *that* until a bunch of people had used mod points.
So there was no obvious way to give "make up" mod points to those who missed out. (My mysql skills are limited.) Nor, apparently, was it obvious to any other staff who was around.
Rather than mung (Mung Until No Good) things even further, in discussion with other staff, it was decided to leave well enough alone. Things should clear themselves up on their own the next time mod points are scheduled to be re-issued (starting each morning at 00:10 UTC).
--martyb
Tesla unveils chip to train A.I. models inside its data centers:
Tesla on Thursday unveiled a custom chip for training artificial-intelligence networks in data centers.
The work, shown at the automaker's live-streamed AI Day, demonstrates the company's continuing pursuit of vertical integration.
The D1 chip, part of Tesla's Dojo supercomputer system, uses a 7-nanometer manufacturing process, with 362 teraflops of processing power, said Ganesh Venkataramanan, senior director of Autopilot hardware. Tesla places 25 of these chips onto a single "training tile," and 120 of these tiles come together across several server cabinets, amounting to over an exaflop of power, Venkataramanan said.
"We are assembling our first cabinets pretty soon," said Venkataramanan, who previously worked at chipmaker AMD.
He said the Tesla technology will be the fastest AI-training computer.
[...] "We should have Dojo operational next year," CEO Elon Musk said.
I'd like some feedback from those on Soylent News about a personal project of mine -- a "unique" Git glossary. (After looking at a few terms, it should be clear what makes it unique from other Git glossaries.)
For those who use Git, it's pretty well known that Git documentation is... how shall I put this nicely? Git documentation is "difficult to understand" at times.
I never learned Git from more experienced people at the places I worked, because the groups in which I worked never used Git. That means I started learning Git on my own at home. This turned into a confusing and frustrating experience because as I tried to learn Git from different online sources and even a couple of books, I noticed a lot of conflicting information. No one seemed to be able to agree what terms to use or what certain terms meant. Turning to more official sources, it didn't get any better. Actually, sometimes it was worse.
I decided to figure out what exact Git terminology is and where things went wrong -- my glossary was born. My glossary is not meant to replace the Git documentation in any way, but to supplement it.
Pulling information from the official Git glossary, man pages, and Pro Git (the book distributed by the Git website for beginners), I realized some things that I'd never seen written down anywhere else. For instance, the term remote reference has two differing definitions, branch has five definitions, and in my detailed version of the definition of tag, I explain that I could never find any clear definition of tag.
The terms remote and tracking were the most challenging. They were so poorly defined and so poorly documented by Git that not only do they have glossary entries, but I wrote complete and highly detailed articles about them. (Links to the articles can be found in the glossary entries.)
Here are my two main links:
I'd like your feedback: if you know Git well, I'd like to know if I've gone completely off the rails. If you're a casual user of Git, I'd like to know if the glossary is helpful or confusing.
Expect a few rough spots, though. The glossary is still a work in progress. There are typos, terminology that I should probably add (suggestions are welcome), and a few things that are "half baked" (although I think you'll recognize them when you see them). Nevertheless, there should be plenty enough to get a feel for what I'm trying to do.
One other thing that might interest you: The entire thing is written in html and css. There is no javascript. That means no tracking, and the files are small for the large amount of info given.
Baidu Announces Upgraded Baidu Brain 7.0 and Mass Production of 2nd Generation Kunlun AI Chip:
Baidu today showcased its strengths in artificial intelligence technology with the launch of Baidu Brain 7.0, the start of mass production of its 2nd generation Kunlun AI chip, Kunlun II, and the demonstration of industrial applications using Baidu AI Cloud. Shared at Baidu World 2021, Baidu's annual flagship technology conference, the announcements represent the depth of Baidu's expertise in AI technology and industrial practice, and its efforts to make AI technology more accessible.
"AI technology is growing increasingly complex, and integrated innovation has made AI more powerful," said Haifeng Wang, Baidu's Chief Technology Officer at Baidu World 2021. As AI technology plays an expanding role in a wider range of industries and drives a new era of technological revolution and industrial transformation, it is increasingly important to lower the threshold for different real-world applications and to increase accessibility to AI development platforms.
A key infrastructure supporting industrial applications of AI and Baidu Cloud, Baidu Brain is one of the world's largest AI open platforms. The newly upgraded Baidu Brain 7.0 offers greater integration of a wide array of knowledge sources and deep learning, including language comprehension and reasoning, using numerous combined technologies to enable output across language, voice and visual formats.
Working together with Baidu Brain 7.0's software capabilities is the new Kunlun II AI Chip, providing an improved hardware foundation for a new generation of AI applications. Independently developed by Baidu, Kunlun II offers 2-3 times more processing power than the previous generation, using the world's leading 7nm process and equipped with Baidu's own second-generation XPU architecture.
Japan successfully tests rocket engine propelled by new technology
Japan on Tuesday successfully tested a rocket engine that was propelled by new technology using shock waves produced by burning a mixture of methane and oxygen gases, with the aim of applying the propulsion method to deep space exploration in the future, the country’s space agency said.
The No. 31 vehicle of the S-520 sounding rocket series, measuring 8 meters in length and 52 centimeters in diameter and carrying the engine, lifted off from the Uchinoura Space Center in Kagoshima Prefecture at around 5:30 a.m., according to the Japan Aerospace Exploration Agency.
It reached an altitude of 235 kilometers four minutes and four seconds after the launch and landed in the sea southeast of Uchinoura about eight minutes later, with JAXA retrieving a capsule containing test data in nearby waters.
[...] Jiro Kasahara, a Nagoya University professor, jointly developing the technology with JAXA, said the test demonstrated that the engine maintained a propelling force in space as expected.
“We will aim to put the technology into practical use in about five years,” he said.
InterestingEngineering offers some numbers
The rocket began the tests after the first stage separated, firing the rotating detonation engine for six seconds. When the rocket was recovered from the ocean after the demonstration, it was discovered that the rotating detonation engine produced around 500 Newtons of thrust.
More info:
A rotating detonation engine (RDE) is a proposed engine using a form of pressure gain combustion, where one or more detonations continuously travel around an annular channel. Computational simulations and experimental results have shown that the RDE has potential in transport and other applications.
In detonative combustion, the results expand at supersonic speed. It is theoretically more efficient than conventional deflagrative combustion by as much as 25%. Such an efficiency gain would provide major fuel savings.
Disadvantages include instability and noise.
May 2020, UCF Researchers Develop Groundbreaking New Rocket-Propulsion System
A University of Central Florida researcher and his team have developed an advanced new rocket-propulsion system once thought to be impossible.
The system, known as a rotating detonation rocket engine, will allow upper stage rockets for space missions to become lighter, travel farther, and burn more cleanly.
The results were published this month in the journal Combustion and Flame.
“The study presents, for the first time, experimental evidence of a safe and functioning hydrogen and oxygen propellant detonation in a rotating detonation rocket engine,”...
Feb 2021, Successful engine test brings Australian space launch capability a step closer (also covered by S/N). Not too much information of fuel/oxidant, thrust or frequency of operations for this one.
Alzheimer's discovery reveals "Achilles' heel" of synapse degeneration:
Scientists believe one of the key culprits behind the cognitive decline seen in Alzheimer's are amyloid beta proteins that clump together and disrupt the brain's synaptic connections, but how they carry out such degeneration has remained unclear. A new study has shone compelling new light on this phenomenon, with the authors demonstrating how these toxic agents take aim at the "Achilles' heel" of synapses, and better yet, how they might just be stopped.
[...] Neurobiologists at the University of California (UC) San Diego focused on a major type of synapse called glutamatergic synapses. During brain development, these synapses are pieced together by a powerful signaling pathway called the planar cell polarity (PCP) pathway, which includes signaling components called Celsr3 and Vangl2. These work in harmony to stabilize and disassemble synapses, respectively, to keep their numbers at a healthy level.
[...] The researchers then turned their attention to another key component of the PCP pathway called Ryk, which functions much like Vangl2 in mediating synapse disassembly. Using special antibodies, the scientists blocked the function of Ryk and found that this too prevented the degeneration of synapses by the amyloid beta proteins. In mouse models of Alzheimer's, both knocking out the gene for Ryk and administering the Ryk-blocking antibody protected the synapses and preserved cognitive function.
"As amyloid beta pathology and synapse loss usually occurs in early stages of Alzheimer's disease, even before cognitive decline can be detected, early intervention, such as restoring the rebalance of the PCP pathway, will likely be beneficial for Alzheimer's patients," says Zou.
The Ryk antibody also proved effective at quelling some of the signs of neuroinflammation seen in Alzheimer's, though the exact mechanisms behind this are unclear. In any case, the scientists believe these results indicate the PCP could prove a valuable target in efforts to protect synapse loss in Alzheimer's disease, and potentially other conditions.
Also at: UC San Diego
Journal Reference:
Bo Feng, Andiara E. Freitas, Lilach Gorodetski, et al. Planar cell polarity signaling components are a direct target of β-amyloid–associated degeneration of glutamatergic synapses [open], Science Advances (DOI: 10.1126/sciadv.abh2307)
NASA's Perseverance to attempt second Mars soil scoop, hoping rocks don't 'crumble':
NASA's Perseverance rover will drive to a new location in the coming weeks to drill for its first Mars soil sample, scientists say, weeks after the robot's first attempt resulted in an empty sample tube.
[...] Now the rover, a science lab on wheels that landed on Mars in February, will drive to a new location called Citadelle for a second shot at picking up its first rock sample. This time, to make sure a sample is actually collected, engineers will wait for images of the sample tube to come back before it gets processed and stowed inside the rover’s belly.
“We were just super excited that the hardware worked from beginning to end without any faults. And then there was that surprise — ‘No sample? What do you mean no sample?’,” Louise Jandura, the Chief Engineer for Sampling & Caching on NASA’s Perseverance team, says of the first attempt on August 5th. “So quickly, after that sunk in, we started to do the investigation.”
The rock that Perseverance’s sampling drill bit dug into wasn’t as sturdy as scientists thought it’d be. What was supposed to be a fairly solid rock core turned out to be a crumbly powder that slipped out of the rover’s sampling tube. After finding the sample tube was empty, mission staff used the rover’s cameras to analyze remnants of the hole that Perseverance drilled. They figured the mound of dust around the hole and some material at the bottom of the hole were what slipped out.
“The rock simply wasn’t our kind of rock,” Jennifer Trosper, Project Manager at NASA’s Jet Propulsion Laboratory, wrote in a blog post on Thursday. “Although we had successfully acquired over 100 cores in a range of different test rocks on Earth, we had not encountered a rock in our test suite that behaved in quite this manner.”
Rain fell at the normally snowy summit of Greenland for the first time on record:
Temperatures at the Greenland summit over the weekend rose above freezing for the third time in less than a decade. The warm air fueled an extreme rain event that dumped 7 billion tons of water on the ice sheet, enough to fill the Reflecting Pool at the National Mall in Washington, DC, nearly 250,000 times.
It was the heaviest rainfall on the ice sheet since record keeping began in 1950, according to the National Snow and Ice Data Center, and the amount of ice mass lost on Sunday was seven times higher than normal for this time of year.
The New York Times adds It Rained at the Summit of Greenland. That's Never Happened Before:
Something extraordinary happened last Saturday at the frigid high point of the Greenland ice sheet, two miles in the sky and more than 500 miles above the Arctic Circle: It rained for the first time.
The rain at a research station — not just a few drops or a drizzle but a stream for several hours, as temperatures rose slightly above freezing — is yet another troubling sign of a changing Arctic, which is warming faster than any other region on the planet.
"It's incredible, because it does write a new chapter in the book of Greenland," said Marco Tedesco, a researcher at Lamont-Doherty Earth Observatory of Columbia University. "This is really new."
At the station, which is called Summit and is occupied year-round under the auspices of the National Science Foundation, there is no record of rain since observations began in the 1980s. And computer simulations show no evidence going back even further, said Thomas Mote, a climate scientist at the University of Georgia.
Above-freezing conditions at Summit are nearly as rare. Before this century, ice cores showed they had occurred only six times in the past 2,000 years, Martin Stendel, a senior researcher at the Danish Meteorological Institute, wrote in an email message.
But above-freezing temperatures have now occurred at Summit in 2012, 2019 and this year — three times in fewer than 10 years.
The Greenland ice sheet, which is up to two miles thick and covers about 650,000 square miles, has been losing more ice and contributing more to sea-level rise in recent decades as the Earth has warmed from human-caused emissions of carbon dioxide and other heat-trapping gases.
The surface of the ice sheet gains mass every year, because accumulation of snowfall is greater than surface melting. But overall, the sheet loses more ice through melting where it meets the ocean, and through the breaking-off of icebergs. On average over the past two decades, Greenland has lost more than 300 billion tons of ice each year.
Chip shortage: Toyota to cut global production by 40%:
The world's biggest carmaker had planned to make almost 900,000 cars next month, but has now reduced that to 540,000 vehicles.
Volkswagen, the world's second-biggest car producer, has warned it may also be forced to cut output further.
The Covid pandemic boosted demand for appliances that use chips, such as phones, TVs and games consoles.
On Thursday, German firm Volkswagen, which cut output earlier in the year, told Reuters: "We currently expect supply of chips in the third quarter to be very volatile and tight.
"We can't rule out further changes to production."
Toyota's other rivals, including General Motors, Ford, Nissan, Daimler, BMW and Renault, have already scaled back production in the face of the global chip shortage.
[...] New cars often include dozens of microchips but Toyota benefited from having built a larger stockpile of chips - also called semiconductors - as part of a revamp to its business continuity plan, developed in the wake of the Fukushima earthquake and tsunami a decade ago.
The decision to cut production now has been precipitated by the resurgence of coronavirus cases across Asia hitting supplies.
[...] The aim for Toyota as a whole was to make up for any lost volume by the end of 2021, he added.
[...] Shares in Toyota fell by 4.4% on Thursday, their biggest daily drop since December 2018.
AMD Launches The Infinity Hub As Its Newest Open-Source Portal:
AMD Infinity Hub is [...] focused on high performance computing (HPC) with AMD Instinct accelerators. Infinity Hub is also more about porting existing software to the Radeon Open eCosystem (ROCm) for enjoying Instinct support rather than developing new and original HPC software.
The AMD Infinity Hub in its initial form lays out instructions on how to obtain/use ROCm-enabled versions of AMBER, Chroma, CP2K, GROMACS, NAMD, OpenMM, PyTorch, SPECFEM3D, and TensorFlow.
Some of these upstream open-source projects already have ROCm support available and in those cases the Infinity Hub is just outlining ROCm support caveats and other details to help users. While ROCm can work on select consumer Radeon GPUs too, the Infinity Hub is just focused on the support around their Instinct accelerators.
AMD is striving for the Infinity Hub to be a resource to make it easier to deploy HPC workloads on their GPUs/accelerators, simplify deployments, and stay up to date with new resources.
[...] The Infinity Hub can be viewed on AMD.com.;
Babylonian Tablet Trigonometry:
Contrary to what generations of pupils have learned in high school geometry, the Greek philosopher Pythagoras did not come up with this foundational theorem [(a² + b² = c²)] first. The proof lies in an ancient artifact that dates back to the Old Babylonian (OB) period: 1900 to 1600 B.C.
In 1894, Father Jean-Vincent Scheil excavated a clay tablet at an archaeological expedition at Sippar, southwest of Baghdad. "But its significance was not understood at the time," Daniel Mansfield—lead author of the new research and a mathematician at the University of New South Wales in Sydney, Australia—writes in The Conversation.
The tablet, known as Si.427, is "the only known example of a cadastral document from the OB period, which is a plan used by surveyors to define land boundaries," according to Mansfield. On the front of the artifact is an inscription showing a diagram of a field. The surveyors drew a series of perpendicular lines, using Pythagorean triples to create precise right angles so that the fields' boundaries were as square as possible.
There's evidence of triangles drawn around the periphery of the field documented on the tablet, but if that's not enough proof, consider the back of the clay tablet. On it, cuneiform text describes the opposite side, including details about the sizes of the fields.
[...] Surveyors used Pythagorean triples to measure fields and draw accurate maps, but some numbers that make up Pythagorean triples aren't regular, and don't make sense to try to scale up to fit any field. Plimpton 322 lists a bunch of Pythagorean triples and notes which of their three values is regular, helping ancient Babylonian surveyors to quickly "do the math," so to speak.
Journal Reference:
Mansfield, Daniel F.. Plimpton 322: A Study of Rectangles [open], Foundations of Science (DOI: 10.1007/s10699-021-09806-0)
Elon Musk reveals plans to unleash a humanoid Tesla Bot:
Tesla CEO Elon Musk ended a deeply technical AI Day event [(3h3m21s)] with a head-turning announcement: a humanoid robot.
After a dancing human dressed as a robot moved off stage at Thursday's invitation-only event in Palo Alto, California, Musk introduced Tesla Bot. It will be based on Tesla's Autopilot system and is essentially a humanoid form of the car. Musk considers the electric vehicles "fully sentient robots on wheels." So might as well make it a human-like bot!
The bot looks like a human with two arms (and two hands with five fingers) and two legs. It'll stand at 5 feet 8 inches and weigh 125 pounds. It can only run 5 mph, which Musk assured was slow enough for most people to escape if something goes wrong: "If you can run faster than that it’ll be fine."
Most importantly, Musk said it would be friendly ("of course") and operate dangerous, repetitive, and boring tasks as it "navigates a world built for humans."
Musk repeated that the humanoid would have a screen on its head and eight cameras, like on Tesla cars that can drive with assistance from Autopilot. "It's all the same tools we see in the car," he said.
The story continues at c|net:
Elon Musk reveals Tesla Bot, a humanoid robot utilizing Tesla's vehicle AI:
Three slides detailed the robot's proposed specifications and Musk made sure he pointed out you could both outrun the Tesla Bot and "overpower" it. He has, in the past, rallied against the use of robots as weapons and warned of the risks AI might pose -- once calling it the "biggest risk we face as a civilization." I guess if they're your incredibly slow, easy-to-overpower robots, the dangers are reduced.
One particular slide said they would eliminate "dangerous, repititive, boring tasks" and Musk provided an example suggesting the robot could be told to "go to the store and get ... the following groceries."
A prototype would likely be ready next year, he said.
Google Has Been Paying Wireless Carriers Billions To Not Develop Competing App Stores:
To be clear, wireless carrier app stores have always kind of sucked. Verizon's efforts to create its own app store were shut down in 2012, after underwhelming consumers for years. At the time, the narrative was that Verizon just didn't find it worth the trouble in the face of Google domination and innovation. And while that's still largely true (wireless carriers are utterly unfamiliar with competition and therefore historically suck at innovation and adaptation), it turns out there was another reason.
Namely, that Google was paying Verizon and other major wireless companies a big chunk of money to not compete with the Android marketplace. And they were paying smartphone manufacturers to ship devices without competing app stores installed. Both nuggets were buried in a freshly unredacted copy of Epic's antitrust complaint (pdf) against Google, first spotted by Jeremy Owens:
Man, I love when the redactions come off and there are fascinating numbers underneath.
This unredacted graf shows that telcos get up to 25% of Google's app sales to keep them from developing rival app stores on the smartphones they sell and service. pic.twitter.com/Vx6p1YBU6S
This agreement to start paying wireless carriers 20-25% of app sales was occurring right around the time that Google brass was visibly starting to wimp out on consumer-centric issues like net neutrality. That involved working closely with Verizon to push the FCC toward flimsy, loophole-filled, "compromise" 2010 net neutrality rules that excluded wireless entirely. Verizon proceeded to then successfully sue the FCC to have those repealed anyway, leading to better rules in 2015 that were also dismantled a few years, later, albeit thanks to lobbying, not the courtroom.
UCLA-led study could clarify how microbes can exacerbate cognitive decline:
In the experiment, which was conducted with mice, researchers found that gut microbes can exacerbate the effects of cognitive impairment because of how they affect the hippocampus, the region of the brain that is critical for memory and learning. They found that the concentration of one group of bacteria called Bilophila increased dramatically in the gut microbiota of mice that were fed a ketogenic diet — high in fat, and low in carbohydrates — and were intermittently deprived of oxygen, creating a condition called hypoxia.
The scientists also found that a ketogenic diet, hypoxia and treatment with a species of Bilophila called Bilophila wadsworthia impaired the hippocampus, leading to reduced cognitive ability in mice.
The researchers gave several mice a ketogenic diet and others a standard diet. Then, all of the mice received reduced levels of oxygen for five consecutive days and then were given four days to recover. Depriving the animals of some oxygen was a way for the scientists to cause cognitive impairment, in order to mimic the cognitive impairment in humans that can be caused by neurological diseases or aging.
Next, the scientists observed their ability to navigate a maze. When trying to find their way out of a maze, mice on the ketogenic diet made an average of 30% more errors than mice given the standard diet. (The range of difference between the two groups was 25% to 75%.)
The researchers also evaluated whether the different diets alone could cause any change in cognitive behavior in mice who had not been deprived of oxygen. In that experiment, there was no appreciable difference in the mice’s ability to find their way out of the maze based on whether they had a ketogenic diet or a standard diet — indicating that the negative impact on cognitive ability only occurred in combination with oxygen deprivation.
[...] Next, the researchers investigated what would happen if they depleted the mice’s microbiota before administering a ketogenic diet and exposing them to hypoxia. Interestingly, mice that had their microbiota depleted first made significantly fewer errors in the maze than mice that were exposed to hypoxia and given a ketogenic diet but had not had changes to their microbiota first.
Journal Reference:
Christine A. Olson. Alterations in the gut microbiota contribute to cognitive impairment induced by the ketogenic diet and hypoxia, Cell Host & Microbe (DOI: 10.1016/j.chom.2021.07.004)