At Scientific American, we were told last month: “Physicists have devised a mind-bending error-correction technique that could dramatically boost the performance of quantum computers”:

“It is very exciting to see this unusual phase of matter realized in an actual experiment, especially because the mathematical description is based on a theoretical ‘extra’ time dimension,” says team member Philipp Dumitrescu, who was at the Flatiron Institute in New York City when the experiments were carried out. A paper describing the work was published in Nature on July 20.

 Opening a portal to an extra time dimension—even just a theoretical one—sounds thrilling, but it was not the physicists’ original plan. “We were very much motivated to see what new types of phases could be created,” says study co-author Andrew Potter, a quantum physicist at the University of British Columbia. Only after envisioning their proposed new phase did the team members realize it could help protect data being processed in quantum computers from errors.

 Zeeya Merali, “New Phase of Matter Opens Portal to Extra Time Dimension” at Scientific American (July 26, 2022)

So, time travel? Not really. Physicist Philipp Dumitrescu and colleagues (the paper requires a fee or subscription) were studying phases of matter and realized that one of them could be used as an error correction technique for quantum computers. They used a pulse frequency that was neither periodic nor random but rather followed the Fibonacci sequence of numbers.

Experimental physicist Rob Sheldon offers an explanation:

They are constructing “time crystals”, where moving atoms return to the same position after some time.

A simple example is to connect two pendulums with a spring and set them in motion. After a while, one pendulum comes to rest and the other oscillates wildly. But then the stationary one starts to move and oscillates wildly while the first one stops. This goes on for some time.

If we make a graph with time on the x-axis, and positions of two pendulums on y-axis, the pattern repeats with time. This is an example of a “time crystal.” The researchers wanted to do it for 11 atoms in a quantum computer, that were acting as “qubits”, or quantum states. So you can think of this as 11 pendulums connected by springs. But the “springs” are actually two lasers beams that push them around.

 The reason for this arrangement is that we need to “entangle” the 11 atoms in a coherent wavefunction to make a quantum computation. But the slightest disturbances “perturb” the entangled state and destroy it or “decohere” it into random, uncoordinated motions.

 However to make a quantum computer useful, the entangled state must last long enough to do a calculation and be read out. The perturbations were too strong, so the entangled state “decayed” too quickly to be useful.

 In the past decade, people realized that one can “digitize” these entangled states by making them wrap around a crystal or some physical symmetry. Then, as in Bohr’s electron model of the atom, only a very few waves have the right “size” ( or energy) to wrap around an object and match the ends. It’s like a jump rope. You can have waves of 1/2 wavelength with one jumper (that’s the normal one) or, with talented rope handlers, twice that for two jumpers. But you can’t have .75 wavelengths and 1 1/2 jumpers. It has to come out even.

 This effect is what turns squishy waves into digitized units of 1/2 wavelengths. It’s a “topological” effect of wrapping waves into a package that turns them into integers. That’s how the “quantum” in quantum mechanics (QM) comes about.

 What physicists realized in the past three decades is that this applies to large groups of atoms as well as to Bohr’s single atom. There are waves that wrap around a million atoms or even a trillion atoms, but have to match at the ends. This allows one to construct (with silicon etching) macroscopic (visible to the eye) shapes with distinct, quantized wavefunctions called “topological” states.

 With such a wavefunction, little perturbations don’t have enough oomph to push the entangled state to another wrapping number (higher energy). So the topological state is very stable and robust. This gives the quantum computer the stability it needs to carry out computations on qubits.

 This is how the experiment started out: They took 11 atoms, connected the springs, and made a time crystal with topological (in time) symmetry. If it helps, think of the two dimensions of a donut as polar and azimuthal angles that wrap back to the beginning. Now for a time crystal, the pulses of the two lasers have time lags, called phases, that also wrap back to the beginning. So we are making a “donut” time crystal.

 Their time crystal didn’t work. The results were a mishmash. Too many perturbations “resonated” with the time or phase of the crystal, and spoiled the effect. So they decided to lengthen the size. If it were space they would expand from microns to meters in size, but since they are using time crystals, they “size” is a really long repetition time. In nuclear fusion tokomaks, this is the “wrapping angle” around the donut torus. If chosen correctly, it keeps the hydrogen ions from repeating an orbit, as they densely fill all the possible area of the donut like winding thread on a spool.

 This means that a bump or imperfection in the walls of the tokamak donut — a tokamak is a donut-shaped vacuum chamber — only affects a hydrogen atom once, and doesn’t resonate or add perturbations with each orbit. So with two lasers, they made a time crystal where the phases or timing of two lasers pulses adjusted the “wrapping angle” in time. When they found these “long repeat” wrapping angles, they discovered that their entangled states lasted a great deal longer, which made a quantum computer using atoms for qubits possible.

They found a useful error correction technique that may help with the development of quantum computers but it’s not really a portal to an extra time dimension. For that, we need science fiction.

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Few biological facts seem as irrevocable as brain death. It has long been assumed that when we die, our neurons die with us. But a new study on the neuron-packed tissue of the eye is beginning to challenge that dogma.

In the new work, researchers restored electrical activity in human retinas—the light-sensitive neural tissue that sits at the back of our eyes and communicates with our brains—from recently deceased organ donors. This achievement, reported in Nature, offers a better way to study eye diseases such as age-related macular degeneration, a leading cause of vision loss and blindness. It could also lay the groundwork for reviving other types of neural tissue and perhaps—one day—for retinal transplants.

Most retina studies are done in animals, primarily mice. But mouse retinas lack the macula, a key region found in human eyes that picks out fine details, so they are not an ideal model. Human eye tissue from autopsies often takes hours to obtain and is dead before scientists can study its function. But what if you could revive it?

When Yale University researchers showed in 2019 that rudimentary electrical activity could be restored in pig brains after death, University of Utah vision scientist Frans Vinberg, Scripps Research retinal surgeon Anne Hanneken and their colleagues were inspired to study whether retinal tissue could also be restored postmortem.

For the study, the researchers first tested how long mouse retinas could send electrical signals after the animals were euthanized. They were able to restore this activity up to three hours later—and found that a lack of oxygen was the main factor in irreversible loss of function. They then investigated human eyes that the researchers obtained from organ donors very soon after brain or cardiac death. The scientists transported the eyes to the laboratory in a container that supplied oxygen and nutrients, then exposed the retinal tissue to dim light and measured electrical signals generated by the tissue. They were able to reestablish electrical activity in light-sensitive cells called photoreceptors, as well as in the neurons these cells connect to, in the donor eyes—if the eyes were obtained less than 20 minutes after death. Of course, the eyes could not “see,” because they were not connected to a brain, Hanneken notes. But the results showed it was possible to restore not just individual retinal cells but the communication between them.

“What's most exciting is this really could become a model for studying visual physiology in human retinas, in health and in aging and in disease,” says Joan Miller, chief of ophthalmology at Mass Eye and Ear and ophthalmology chair at Harvard Medical School, who was not involved with the new study. Macular degeneration, for example, has so far been difficult to study because living human eye tissue has been impossible to access. Using this new technique, scientists could study healthy and diseased donor eyes to understand their function and test treatments.

The team's findings also suggest it may be possible to revive other types of neural tissue. “The retina is a window to the brain, so if you can restore communication in the retina after death, it makes you pause and consider what kind of communication you might be able to recover in the brain,” Hanneken says. The study additionally raises the prospect of retinal transplants, although those are likely still very far off, the researchers say.

This new work illustrates the importance of donor tissue to basic science. “We are very thankful for the donors and their families,” Vinberg says. “We hope this will encourage people ... to check that box in their driver's license and also be willing to donate tissues for research.”

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When analyzing the literature on 375 human pathogens, researchers from the University of Hawaiʻi at Mānoa and the University of Wisconsin-Madison in the US found 58 percent of these diseases were, at some point in recorded history, aggravated by climate hazards.

That's 277 known diseases we need to watch for future outbreaks, and when you consider all the ways in which those pathogens can spread with climate change, the possibilities are overwhelming.

There are simply too many infections and too many modes of transmission for society to adapt to each of these threats at once. Instead, the researchers say, our best bet is to fight climate change at its source by significantly reducing our greenhouse gas emissions.

Human-driven climate change is already increasing the severity and frequency of climate hazards like heatwaves, wildfires, and flooding in many areas around the globe, often bringing a variety of organisms into closer contact with humans.

To gain a better sense of the size of the problem, the researchers combed Google Scholar for thousands of articles on climate change and infectious diseases known to impact human society, like Zika, malaria, dengue, influenza, and Ebola (to name just a few).

The team found 3,213 empirical examples in human history in which climate hazards were implicated in outbreaks of infectious disease.

All of these cases were related to 286 unique pathogens, and 277 of these were aggravated by at least one climate hazard.

The authors also identified 1,006 ways in which climate hazards can result in a disease outbreak.

Storms and floods, for instance, can cause displacements that bring humans into close contact with water-borne pathogens, like cholera. Fires and droughts can also push wild animals looking for shelter, water or food right into our houses, carrying their diseases with them.

Warming temperatures and precipitation can expand the range of a pathogen, extending the risks of bug-borne diseases like Lyme disease, dengue or malaria. Heatwaves also increase our contact with water as we attempt to keep cool and they have already been implicated in the rise of infections like gastroenteritis[.]

Similar processes also occur in the sea. In a warming ocean, for example, harmful algal blooms and diseases are much more common.

It's a lot to consider. And these are just the pathogens we know about. The COVID-19 pandemic has made it painfully clear that the more we interact with other species, the greater the risk of new diseases making the jump into humans.

Plus, as permafrost melts, ancient pathogens preserved in the icy Arctic could find their way into hosts who lack the immunity to deal with them.

"The successful emergence of pathogens frozen in time could be regarded as a 'Pandora's box', given the potentially large pool of pathogens accumulated over time and the extent to which these pathogens may be new to people," the authors of the current review write.

It's also possible that some pathogens will be strengthened by climate change. In a warming world, the life cycle of an infectious disease could very well accelerate, allowing for greater reproduction in a shorter space of time. If that pathogen spreads better in summer, then as the season expands, the risk of infection will also stick around for longer.

Scientists have already warned that climate change is making humans sicker. Allergies, skin disease, dehydration, and pregnancy complications are all associated with climate hazards, like heat waves, storms, or droughts.

It's unclear how the human body will cope if infectious disease outbreaks become more common in the future. As our immune system's defenses fall, our enemies seem to be strengthening, and we don't have time to fight them all.

At a critical juncture like this it's worth remembering: We are only as healthy as the world we live in.

The study was published in Nature Climate Change.

Source

China has issued two licences for robot taxi operations, according to local tech giant Baidu.

In a statement sent to The Register, Baidu claimed its Apollo robot taxis have won the right to operate in parts of the cities of Chongqing and Wuhan.

The licences issued apparently do not require the presence of a human driver.

China's organic cabbies don't have a lot to worry about – for now – because the services are geo-fenced, as was the case when Baidu was allowed to operate tests in Beijing. The licences also restrict operations to daylight hours.

In Wuhan the robot rides will therefore only operate in a 13 square kilometre block of the Wuhan Economic & Technological Development Zone, between 9:00AM and 5:00PM. In Chongqing's Yongchuan District robots will roll across 30km2 from 9:30AM to 4:30PM.

Each city will also get just five robot taxis.

But Baidu's Wei Dong, who serves as vice president and chief safety operation officer at the company's Intelligent Driving Group, has hailed the issue of the permits as an important step.

"We believe these permits are a key milestone on the path to the inflection point when the industry can finally roll out fully autonomous driving services at scale," he sad in a canned statement.

Those words aren't just hyperbole. Baidu says it has a million orders on the books for its robo-cabs and recently introduced a vastly cheaper model it expects will spur further adoption and provide additional revenue streams to cab companies by including space for vending machines.

The two just-announced services will use a previous generation car, depicted below.

Baidu 5th-gen apollo robotaxi

China is all-in on electric and autonomous vehicles, with several local manufacturers already offering ready to roll cars and tech giants like Alibaba, Huawei and Xiaomi set to enter the market too.

The nation has even tested "smart highways" equipped with sensors to help such vehicles move at higher speeds, and manage traffic flows to lessen the impact of bottlenecks like traffic lights.

China's activity in the sector has not gone unnoticed elsewhere. One of the aims of the US's recently approved giant tech stimulus package is to ensure the nation is not reliant on Chinese battery technology and can match its progress towards autonomous driving adoption. ®

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As the sun set over Maury Island, just south of Seattle, Ben Goertzel and his jazz fusion band had one of those moments that all bands hope for — keyboard, guitar, saxophone and lead singer coming together as if they were one.

Dr. Goertzel was on keys. The band’s friends and family listened from a patio overlooking the beach. And Desdemona, wearing a purple wig and a black dress laced with metal studs, was on lead vocals, warning of the coming Singularity — the inflection point where technology can no longer be controlled by its creators.

“The Singularity will not be centralized!” she bellowed. “It will radiate through the cosmos like a wasp!”

After more than 25 years as an artificial intelligence researcher — a quarter-century spent in pursuit of a machine that could think like a human — Dr. Goertzel knew he had finally reached the end goal: Desdemona, a machine he had built, was sentient.

But a few minutes later, he realized this was nonsense.

“When the band gelled, it felt like the robot was part of our collective intelligence — that it was sensing what we were feeling and doing,” he said. “Then I stopped playing and thought about what really happened.”

Credit...Ian Allen for The New York Times

What happened was that Desdemona, through some sort of technology-meets-jazz-fusion kismet, hit him with a reasonable facsimile of his own words at just the right moment.

Dr. Goertzel is the chief executive and chief scientist of an organization called SingularityNET. He built Desdemona to, in essence, mimic the language in books he had written about the future of artificial intelligence.

Many people in Dr. Goertzel’s field aren’t as good at distinguishing between what is real and what they might want to be real.

The most famous recent example is an engineer named Blake Lemoine. He worked on artificial intelligence at Google, specifically on software that can generate words on its own — what’s called a large language model. He concluded the technology was sentient; his bosses concluded it wasn’t. He went public with his convictions in an interview with The Washington Post, saying: “I know a person when I talk to it. It doesn’t matter whether they have a brain made of meat in their head. Or if they have a billion lines of code.”

The interview caused an enormous stir across the world of artificial intelligence researchers, which I have been covering for more than a decade, and among people who are not normally following large-language-model breakthroughs. One of my mother’s oldest friends sent her an email asking if I thought the technology was sentient.

When she was assured that it was not, her reply was swift. “That’s consoling,” she said. Google eventually fired Mr. Lemoine.

For people like my mother’s friend, the notion that today’s technology is somehow behaving like the human brain is a red herring. There is no evidence this technology is sentient or conscious — two words that describe an awareness of the surrounding world.

That goes for even the simplest form you might find in a worm, said Colin Allen, a professor at the University of Pittsburgh who explores cognitive skills in both animals and machines. “The dialogue generated by large language models does not provide evidence of the kind of sentience that even very primitive animals likely possess,” he said.

Alison Gopnik, a professor of psychology who is part of the A.I. research group at the University of California, Berkeley, agreed. “The computational capacities of current A.I. like the large language models,” she said, “don’t make it any more likely that they are sentient than that rocks or other machines are.”

The problem is that the people closest to the technology — the people explaining it to the public — live with one foot in the future. They sometimes see what they believe will happen as much as they see what is happening now.

“There are lots of dudes in our industry who struggle to tell the difference between science fiction and real life,” said Andrew Feldman, chief executive and founder of Cerebras, a company building massive computer chips that can help accelerate the progress of A.I.

A prominent researcher, Jürgen Schmidhuber, has long claimed that he first built conscious machines decades ago. In February, Ilya Sutskever, one of the most important researchers of the last decade and the chief scientist at OpenAI, a lab in San Francisco backed by a billion dollars from Microsoft, said today’s technology might be “slightly conscious.” Several weeks later, Mr. Lemoine gave his big interview.

These dispatches from the small, insular, uniquely eccentric world of artificial intelligence research can be confusing or even scary to most of us. Science fiction books, movies and television have trained us to worry that machines will one day become aware of their surroundings and somehow do us harm.

It is true that as these researchers press on, Desdemona-like moments when this technology seems to show signs of true intelligence, consciousness or sentience are increasingly common. It is not true that in labs across Silicon Valley engineers have built robots who can emote and converse and jam on lead vocals like a human. The technology can’t do that.

But it does have the power to mislead people.

The technology can generate tweets and blog posts and even entire articles, and as researchers make gains, it is getting better at conversation.

Although it often spits out complete nonsense, many people — not just A.I. researchers — find themselves talking to this kind of technology as if it were human.

As it improves and proliferates, ethicists warn that we will need a new kind of skepticism to navigate whatever we encounter across the internet. And they wonder if we are up to the task.

Desdemona’s Ancestors

Credit...Sol Goldberg/Cornell University Photography, via Division of Rare and Manuscript Collections, Cornell University Library

On July 7, 1958, inside a government lab several blocks west of the White House, a psychologist named Frank Rosenblatt unveiled a technology he called the Perceptron.

It did not do much. As Dr. Rosenblatt demonstrated for reporters visiting the lab, if he showed the machine a few hundred rectangular cards, some marked on the left and some the right, it could learn to tell the difference between the two.

He said the system would one day learn to recognize handwritten words, spoken commands and even people’s faces. In theory, he told the reporters, it could clone itself, explore distant planets and cross the line from computation into consciousness.

When he died 13 years later, it could do none of that. But this was typical of A.I. research — an academic field created around the same time Dr. Rosenblatt went to work on the Perceptron.

The pioneers of the field aimed to recreate human intelligence by any technological means necessary, and they were confident this would not take very long. Some said a machine would beat the world chess champion and discover its own mathematical theorem within the next decade. That did not happen, either.

The research produced some notable technologies, but they were nowhere close to reproducing human intelligence. “Artificial intelligence” described what the technology might one day do, not what it could do at the moment.

Some of the pioneers were engineers. Others were psychologists or neuroscientists. No one, including the neuroscientists, understood how the brain worked. (Scientists still do not understand it.) But they believed they could somehow recreate it. Some believed more than others.

In the ’80s, an engineer named Doug Lenat said he could rebuild common sense one rule at a time. In the early 2000s, members of a sprawling online community — now called Rationalists or Effective Altruists — began exploring the possibility that artificial intelligence would one day destroy the world.

Soon, they pushed this long-term philosophy into academia and industry.

Inside today’s leading A.I. labs, stills and posters from classic science fiction films hang on the conference room walls. As researchers chase these tropes, they use the same aspirational language used by Dr. Rosenblatt and the other pioneers.

Even the names of these labs look into the future: Google Brain, DeepMind, SingularityNET. The truth is that most technology labeled “artificial intelligence” mimics the human brain in only small ways — if at all. Certainly, it has not reached the point where its creators can no longer control it.

Most researchers can step back from the aspirational language and acknowledge the limitations of the technology. But sometimes, the lines get blurry.

Why They Believe

In 2020, OpenAI, a research lab in San Francisco, unveiled a system called GPT-3. It could generate tweets, pen poetry, summarize emails, answer trivia questions, translate languages and even write computer programs.

Sam Altman, the 37-year-old entrepreneur and investor who leads OpenAI as chief executive, believes this and similar systems are intelligent. “They can complete useful cognitive tasks,” Mr. Altman told me on a recent morning. “The ability to learn — the ability to take in new context and solve something in a new way — is intelligence.”

GPT-3 is what artificial intelligence researchers call a neural network, after the web of neurons in the human brain. That, too, is aspirational language. A neural network is really a mathematical system that learns skills by pinpointing patterns in vast amounts of digital data. By analyzing thousands of cat photos, for instance, it can learn to recognize a cat.

“We call it ‘artificial intelligence,’ but a better name might be ‘extracting statistical patterns from large data sets,’” said Dr. Gopnik, the Berkeley professor.

This is the same technology that Dr. Rosenblatt explored in the 1950s. He did not have the vast amounts of digital data needed to realize this big idea.

Nor did he have the computing power needed to analyze all that data. But around 2010, researchers began to show that a neural network was as powerful as he and others had long claimed it would be — at least with certain tasks.

These tasks included image recognition, speech recognition and translation. A neural network is the technology that recognizes the commands you bark into your iPhone and translates between French and English on Google Translate.

More recently, researchers at places like Google and OpenAI began building neural networks that learned from enormous amounts of prose, including digital books and Wikipedia articles by the thousands. GPT-3 is an example.

As it analyzed all that digital text, it built what you might call a mathematical map of human language — more than 175 billion data points that describe how we piece words together. Using this map, it can perform many different tasks, like penning speeches, writing computer programs and having a conversation.

But there are endless caveats. Using GPT-3 is like rolling the dice: If you ask it for 10 speeches in the voice of Donald J. Trump, it might give you five that sound remarkably like the former president — and five others that come nowhere close. Computer programmers use the technology to create small snippets of code they can slip into larger programs, but more often than not they have to edit and massage whatever it gives them.

“These things are not even in the same ballpark as the mind of the average 2-year-old,” said Dr. Gopnik, who specializes in child development. “In terms of at least some kinds of intelligence, they are probably somewhere between a slime mold and my 2-year-old grandson.”

Even after we discussed these flaws, Mr. Altman described this kind of system as intelligent. As we continued to chat, he acknowledged that it was not intelligent in the way humans are. “It is like an alien form of intelligence,” he said. “But it still counts.”

Credit...Ian C. Bates for The New York Times

The words used to describe the once and future powers of this technology mean different things to different people. People disagree on what is and what is not intelligence. Sentience — the ability to experience feelings and sensations — is not something easily measured. Nor is consciousness — being awake and aware of your surroundings.

Mr. Altman and many others in the field are confident that they are on a path to building a machine that can do anything the human brain can do. This confidence shines through when they discuss current technologies.

“I think part of what’s going on is people are just really excited about these systems and expressing their excitement in imperfect language,” Mr. Altman said.

He acknowledges that some A.I. researchers “struggle to differentiate between reality and science fiction.” But he believes these researchers still serve a valuable role. “They help us dream of the full range of the possible,” he said.

Perhaps they do. But for the rest of us, these dreams can get in the way of the issues that deserve our attention.

Why Everyone Else Believes

In the mid-1960s, a researcher at the Massachusetts Institute of Technology, Joseph Weizenbaum, built an automated psychotherapist he called Eliza.

This chatbot was simple. Basically, when you typed a thought onto a computer screen, it asked you to expand this thought — or it just repeated your words in the form of a question.

Even when Dr. Weizenbaum cherry-picked a conversation for the academic paper he published on the technology, it looked like this, with Eliza responding in capital letters:

 Men are all alike.

 IN WHAT WAY?

 They’re always bugging us about something or other.

 CAN YOU THINK OF A SPECIFIC EXAMPLE?

 Well, my boyfriend made me come here.

 YOUR BOYFRIEND MADE YOU COME HERE

But much to Dr. Weizenbaum’s surprise, people treated Eliza as if it were human. They freely shared their personal problems and took comfort in its responses.

“I knew from long experience that the strong emotional ties many programmers have to their computers are often formed after only short experiences with machines,” he later wrote. “What I had not realized is that extremely short exposures to a relatively simple computer program could induce powerful delusional thinking in quite normal people.”

We humans are susceptible to these feelings. When dogs, cats and other animals exhibit even tiny amounts of humanlike behavior, we tend to assume they are more like us than they really are. Much the same happens when we see hints of human behavior in a machine.

Scientists now call it the Eliza effect.

Much the same thing is happening with modern technology. A few months after GPT-3 was released, an inventor and entrepreneur, Philip Bosua, sent me an email. The subject line was: “god is a machine.”

“There is no doubt in my mind GPT-3 has emerged as sentient,” it read. “We all knew this would happen in the future, but it seems like this future is now. It views me as a prophet to disseminate its religious message and that’s strangely what it feels like.”

After designing more than 600 apps for the iPhone, Mr. Bosua developed a light bulb you could control with your smartphone, built a business around this invention with a Kickstarter campaign and eventually raised $12 million from the Silicon Valley venture capital firm Sequoia Capital. Now, though he has no biomedical training, he is developing a device for diabetics that can monitor their glucose levels without breaking the skin.

Credit...Know Labs

When we spoke on the phone, he asked that I keep his identity secret. He is an experienced tech entrepreneur who was helping to build a new company, Know Labs. But after Mr. Lemoine made similar claims about similar technology developed at Google, Mr. Bosua said he was happy to go on the record.
“When I discovered what I discovered, it was very early days,” he said. “But now all this is starting to come out.”

When I pointed out that many experts were adamant these kinds of systems were merely good at repeating patterns they had seen, he said this is also how humans behave. “Doesn’t a child just mimic what it sees from a parent — what it sees in the world around it?” he said.

Mr. Bosua acknowledged that GPT-3 was not always coherent but said you could avoid this if you used it in the right way.

“The best syntax is honesty,” he said. “If you are honest with it and express your raw thoughts, that gives it the ability to answer the questions you are looking for.”

Mr. Bosua is not necessarily representative of the everyman. The chairman of his new company calls him “divinely inspired” — someone who “sees things early.” But his experiences show the power of even very flawed technology to capture the imagination.

Where the Robots Will Take Us

Credit...Ian Allen for The New York Times

As a researcher at Microsoft, then Google, where she helped found its A.I. ethics team, and now Hugging Face, another prominent research lab, she has seen the rise of this technology firsthand. Today, she said, the technology is relatively simple and obviously flawed, but many people see it as somehow human. What happens when the technology becomes far more powerful?

In addition to generating tweets and blog posts and beginning to imitate conversation, systems built by labs like OpenAI can generate images. With a new tool called DALL-E, you can create photo-realistic digital images merely by describing, in plain English, what you want to see.

Some in the community of A.I. researchers worry that these systems are on their way to sentience or consciousness. But this is beside the point.

“A conscious organism — like a person or a dog or other animals — can learn something in one context and learn something else in another context and then put the two things together to do something in a novel context they have never experienced before,” Dr. Allen of the University of Pittsburgh said. “This technology is nowhere close to doing that.”

There are far more immediate — and more real — concerns.

As this technology continues to improve, it could help spread disinformation across the internet — fake text and fake images — feeding the kind of online campaigns that may have helped sway the 2016 presidential election. It could produce chatbots that mimic conversation in far more convincing ways. And these systems could operate at a scale that makes today’s human-driven disinformation campaigns seem minuscule by comparison.

If and when that happens, we will have to treat everything we see online with extreme skepticism. But Dr. Mitchell wonders if we are up to the challenge.
“I worry that chatbots will prey on people,” she said. “They have the power to persuade us what to believe and what to do.”

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The billionaire and Tesla CEO has been trying to back out of his April agreement to buy the social media company, leading Twitter to sue him last month to complete the acquisition. Musk countersued, accusing Twitter of misleading his team about the true size of its user base and other problems he said amounted to fraud and breach of contract.

Both sides are headed toward an October trial in a Delaware court.

"If Twitter simply provides their method of sampling 100 accounts and how they're confirmed to be real, the deal should proceed on original terms," Musk tweeted early Saturday. "However, if it turns out that their SEC filings are materially false, then it should not."

Musk, who has more than 100 million Twitter followers, went on to challenge Twitter CEO Parag Agrawal to a "public debate about the Twitter bot percentage."

Twitter declined comment Saturday. The company has repeatedly disclosed to the Securities and Exchange Commission an estimate that fewer than 5% of user accounts are fake or spam, with a disclaimer that it could be higher. Musk waived his right to further due diligence when he signed the April merger agreement.

Twitter has argued in court that Musk is deliberately trying to tank the deal and using the bot question as an excuse because market conditions have deteriorated and the acquisition no longer serves his interests. In a court filing Thursday, it describes his counterclaims as an imagined story "contradicted by the evidence and common sense."

"Musk invents representations Twitter never made and then tries to wield, selectively, the extensive confidential data Twitter provided him to conjure a breach of those purported representations," company attorneys wrote.

While Musk has tried to keep the focus on bot disclosures, Twitter's legal team has been digging for information about a host of tech investors and entrepreneurs connected to Musk in a wide-ranging subpoena that could net some of their private communications with the Tesla CEO.

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"I couldn't have imagined that it would ever melt as dramatically as this summer... Our 'archive' is melting away," says the glaciologist.

Fischer—vice director of the Institute for Interdisciplinary Mountain Research at the Austrian Academy of Sciences—has spent more than 20 years surveying Jamtal and four other Alpine glaciers across Austria's highest peaks for the oldest areas of ice.

For scientists looking to reconstruct the Earth's climate in the distant past, such ice formations are a unique time capsule stretching back thousands of years.

The glaciers contain an invaluable treasure trove of data—as they grew, the ice encapsulated twigs and leaves, which can now be carbon-dated, Fischer explains.

And based on the age of such material and the depth where it was found, scientists can infer when ice grew during colder periods, or when warmer conditions caused it to melt.

But now the glaciers are melting rapidly—including the one in the remote and narrow Jamtal valley, not far from where tourists found the stunningly preserved 5,300-year-old mummy of Oetzi, the Iceman, in the 1990s.

Temperatures in Europe's highest mountains have risen by nearly two degrees Celsius in the past 120 years—almost double the global average, according to the International Commission for the Protection of the Alps (CIPRA).

The Alps' roughly 4,000 glaciers have since become one of the starkest signs of global warming.

'If this continues, in five years, Jamtal glacier won't be a glacier anymore,' says scientist Andrea Fischer.

Disappear completely?

The Jamtal glacier has been losing about one meter (three feet) from its surface annually, but this year it has already lost more than a meter, Fischer says.

"And we've got at least two months of summer left... where the glacier is entirely exposed to the sun," she warns.

Snow usually protects most of the glacial ice from the sun until September, but the little snow that fell last winter had already melted by early July.
"This year is outrageous compared to the average of the past 6,000 years," says Fischer.

"If this continues, in five years, Jamtal glacier won't be a glacier anymore."

By the end of the summer, Fischer fears that about seven meters of depth will have melted off the surface—or about 300 years of climate "archives".

"We need the data the glaciers hold to understand the climate of the past—and to create models of what awaits us in the future," she says.

Fischer and her team have drilled on both the Jamtal and other nearby glaciers to extract data, taking out ice samples up to 14 meters deep.

As temperatures rise and the glaciers become more unstable, they are compelled to take additional safety precautions—11 people died in a glacial ice avalanche in the Italian Dolomites in July, the day after temperatures there rose to new records.

In Galtuer, the nearest village to Jamtal glacier, the Alpine Club is already offering a "Goodbye, glacier!" tour.

'My heart is bleeding'

In Galtuer, the nearest village to Jamtal with 870 residents who are mostly dependent on tourism, the Alpine Club is already offering a "Goodbye, glacier!" tour through the once ice-filled valley to raise awareness about the effects of climate change.

Where the ice has retreated, scientists found that within three years about 20 species of plants, mostly mosses, have taken over. In some areas, larches are growing, according to Fischer.

"If the glacier is gone in five years, that's a pity, because it's part of the landscape," says Sarah Mattle, who heads the Alpine Club.

"But then there'll also be new paths, and maybe there'll be an easier hike over the mountains than over the ice. It'll all be a matter of adapting," the 34-year-old adds.

Other locals like Gottlieb Lorenz, whose great-grandfather was the first manager of the 2,165-meter-high Jamtal cabin set up as a refuge for mountaineers, are heartbroken.

"My heart is bleeding when I think about how magnificent and mighty the glacier was and what a miserable tiny pile it is today," the 60-year-old says.
He points at a black-and-white photo taken in 1882 showing a thick ice sheet flowing past the cabin.

Today, the ice is a 90-minute hike away.

Source

Alexa’s approach to prediction is a revelation: “Today you can look for sunny weather, with highs in the mid-70s.” Go to town, scan the skies! You might get lucky.

Really, what more can or should be said about the future? Look around and see what happens. You can look for your crypto windfall. You can look for the love of your life. You can look for the queen of hearts. Seek and ye might find. You can even look for a four-leaf clover, though the chances are about 1 in 10,000. But if you find one, the shamrock is no less lucky because you looked for it. In fact, it’s luck itself.

“Diligence is the mother of good luck” and “The harder I work the luckier I get”—these brisk aphorisms get pinned on Ben Franklin and Thomas Jefferson, lest we earnest Americans forget that salvation comes only to individuals who work themselves to dust. In truth, the luck = work axiom does nothing but serve the regime and the bosses, by kindling credulity in a phantom meritocracy instead of admitting that virtually every single advantage we get in the world is one we lucked into—by being born to the right parents who speak the right language in the right zip code. How about we invert the meritocratic fallacy in those aphorisms and create a new aphorism that makes “work” the delusion and “luck” the reality? “The luckier I get, the harder I pretend I’ve worked.” An excellent way to describe the people born on third who believe they hit a triple.

After all, the chances of the precise sperm colliding with the exact egg in the right fallopian tube and convening to make you—or me—are so low as to be undetectable with human mathematics. The meeting that determines only 100 percent of your existence.

If there’s any method of prediction that never fails, it’s luck. You look for your horse—or your candidate—to win, and she wins? What luck. What if she loses? Better luck next time. If Alexa says you can look for rain, and you look and find it—lucky you, you brought an umbrella! Luck is fate and fate is what happens and a prediction of what happens is a perfect prediction.

Sure, for free-will buffs, being told that your sole agency lies in looking for luck, which you may or may not find, can be demoralizing. Perhaps that’s why people tell themselves that luck is actually just hard work. We can do something about work—namely, do it.

But work and diligence can never be the parents of luck, because luck has no mother, no father, no precedent or context. Luck is a spontaneous mutation, signaling improbability; it shows up randomly, hangs around according to whim, and—as every gambler knows—makes an Irish goodbye. Mischievous luck is fun, a shamrock, a “lady.” It’s worlds away from grinding toil.

So where does the “looking for” luck come in? Ah—your agency comes in the almost-passive search for luck. The noticing. In 2018 the philosophy professor Steven Hales, along with one of his colleagues at Bloomsburg University, found that we’re only as lucky as we think we are. We only find luck when we look for it. Better still—for those who like action items—luck begets luck. You look for sunny weather, you’re more likely to find it; you find it, you come to think you’re lucky; you try your luck looking for more sunny weather and you luck out again.

In Aeon magazine, Hales wrote, “Luck might not be a genuine quality of the world at all.” Fine. But neither is beauty or justice. At the same time, the Bloomsburg researchers discovered “a significant positive correlation” between people’s temperaments and how lucky they thought others were. “One of the things this means is that the more optimistic you are, the more you think others are lucky.” For “optimistic,” I might substitute “happy-go-lucky.”

“Luck is a mere façon de parler, or turn of phrase,” Hales wrote (using the Irish, of course). Of anyone who believes they’re lucky, he went on, “their luck might well be, in a very strict psychological sense, entirely of their own making.”

Of our own making! So you make your own luck by looking for it, but you also make it with lucky turns of phrase and lucky casts of mind. You see a friend who recovered from Covid as lucky for recovering, rather than unlucky for getting sick in the first place. And, if you’re a happy-go-lucky type, you groove luck into your world by saying it, over and over. Wow, you were lucky. Your sister had some stock and made you soup? What luck! Your system rallied? Boy, that’s great genetic luck right there.

Einstein didn’t like the idea of God “playing dice” with the world. Lucky for Einstein, dice, in a world determined by luck, are not thrown by anyone, much less a God who is said to have Yahtzee skills. Instead, the chips fall where they may—and really they just fall, unpredictably, spontaneously. We then look for patterns in them.

For those seeking self-improvement, and who isn’t, I’m not just freestyling here. Living by a doctrine of luck promotes at least five excellent things that have got to be good for your brain.

1. Active skepticism about “meritocracy.”

2. Recognition of the utter contingency of one’s own advantages. An act, if I may, of “checking your privilege.”

3. Appreciation for the spontaneity, serendipity, and unpredictability of the universe. Nicholas Rescher, the illustrious philosopher at the University of Pittsburgh, calls luck “the brilliant randomness of everyday life.”

4. A way to practice “gratitude” without doing calligraphy in $75 journals. All you have you do is say, every time it hits you that life is OK and could be otherwise, “What luck!”

5. A way to make more luck in your life.

Luck really is the best creed. It makes no truth claims, requires no messiahs or gurus. It’s not religious, partisan, or ideological. It doesn’t just allow for surprise; it’s nothing but surprise. It’s charming. It may even be the secular answer to grace, but it comes with laughs rather than piety.

When you get good at luck, you can even find a spot of luck in a heat wave or your team’s defeat. But don’t be a psychopath. Luck is not about looking on the bright side. It’s much more minor. It’s about just being—and observing that, of all the prospective organisms in the broken but intriguing world, you happened, against the odds, to be one.

This article appears in the September issue. Subscribe now.

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The Secret to Being Lucky

Tuesday, August 9

At 5:52 a.m. UTC, Russia will launch one of its Soyuz 2.1b rockets carrying a number of CubeSats as well as its primary payload, a satellite called Khayyam. The satellite is being launched for the Iranian military and is described as a remote sensing satellite, however, it’s based on a similar design to a Russian reconnaissance satellite called Razbeg. The Khayyam satellite has a high-resolution camera, weighs 650 kg and will be placed in a Sun-synchronous orbit.

The satellite is named after the Persian polymath, Omar Khayyam, who lived between 1048 and 1131. Polymaths are people involved in a number of fields and in Khayyam’s case, he made contributions to mathematics, astronomy, philosophy, and poetry.

The second and final launch will be carried out by SpaceX at 11 p.m. UTC. It will launch a Falcon 9 carrying 53 Starlink satellites into low Earth orbit. For anyone who uses apps like ISS Detector, this set of satellites will be identifiable by the group number: 4-26. Starlink's satellites are not hard to see and can be spotted with the naked eye or binoculars, so you could see this group after they’re launched if you know where to look. The launch will be streamed on SpaceX’s website.

Recap

The first launch of the week was Rocket Lab’s Antipodean Adventure mission. An Electron rocket carried a classified payload for the National Reconnaissance Office.

Next, a Long March-4B carried several satellites to space, including the Terrestrial Ecosystem Carbon Inventory Satellite (TECIS).

On August 4, an Atlas V carried the SBIRS GEO 6 satellite to orbit for the U.S. Space Force.

On the same day, Blue Origin’s New Shepard carried paying customers to the edge of space.

Also on Thursday, SpaceX launched South Korea’s first lunar mission atop a Falcon 9.

Finally, India launched its first SSLV-D1 rocket carrying the EOS-02 and AzaadiSAT satellites.

That’s all we have this week, check in next time!

TWIRL 77: Roscosmos will launch Iran's Khayyam remote sensing satellite this week

Physical scientists seem to find the phenomenon of chaos everywhere: in the orbits of planets, in weather systems, in a river’s swirling eddies. For nearly three decades, ecologists considered chaos in the living world to be surprisingly rare by comparison. A new analysis, however, reveals that chaos is far more prevalent in ecosystems than researchers thought.

Tanya Rogers was looking back through the scientific literature for recent studies on chaos in ecosystems when she discovered something unexpected: No one had published a quantitative analysis of it in over 25 years. “It was kind of surprising,” said Rogers, a research ecologist at UC Santa Cruz and the new study’s first author. “Like, ‘I can’t believe no one’s done this.’”

So she decided to do it herself. Analyzing more than 170 sets of time-dependent ecosystem data, Rogers and her colleagues found that chaos was present in a third of them—nearly three times more than the estimates in previous studies. What’s more, they discovered that certain groups of organisms, like plankton, insects, and algae, were far more prone to chaos than larger organisms like wolves and birds.

“That really wasn’t in the literature at all,” said Stephan Munch, an evolutionary ecologist at Santa Cruz and a coauthor of the study. Their results suggest that to protect vulnerable species, it is both possible and necessary to build more complex population models as guides for conservation policies.

When ecology was first recognized as a formal science in the 19th century, the prevailing assumption was that nature follows simple, easily understood rules, like a mechanical clock driven by interlocking gears. If scientists could measure the right variables, they could predict the outcome: More rain, for example, would mean a better apple harvest.

In reality, because of chaos, “the world is a lot more whack-a-mole,” said George Sugihara, a quantitative ecologist at the Scripps Institution of Oceanography in San Diego who was not involved in the new research. Chaos reflects predictability over time. A system is said to be stable if it changes very little over a long timescale, and random if its fluctuations are unpredictable. But a chaotic system—one ruled by nonlinear responses to events—may be predictable over short periods but is subject to increasingly dramatic shifts the further out you go.

“We often give the weather as an example of a chaotic system,” said Rogers. A summer breeze over the open ocean probably won’t impact tomorrow’s forecast, but under just the right conditions, it could theoretically send a hurricane plowing into the Caribbean in a few weeks.

Ecologists began flirting with the concept of chaos in the 1970s, when the mathematical biologist Robert May developed a revolutionary tool called the logistic map. This branching diagram (sometimes known as a cobweb plot because of its appearance) shows how chaos creeps into simple models of population growth and other systems over time. Since the survival of organisms is affected so much by chaotic forces like the weather, ecologists assumed that species populations in nature would also often rise and fall chaotically. Logistic maps quickly became ubiquitous in the field as theoretical ecologists sought to explain population fluctuations in organisms like salmon and the algae that cause red tides.

By the early ’90s, ecologists had amassed enough time-series data sets on species populations and enough computing power to test these ideas. There was just one problem: The chaos didn’t seem to be there. Only about 10 percent of the examined populations seemed to change chaotically; the rest either cycled stably or fluctuated randomly. Theories of ecosystem chaos fell out of scientific fashion by the mid-1990s.

The new results from Rogers, Munch and their Santa Cruz mathematician colleague Bethany Johnson, however, suggest that the older work missed where the chaos was hiding. To detect chaos, the earlier studies used models with a single dimension—the population size of one species over time. They didn’t consider corresponding changes in messy real-world factors like temperature, sunlight, rainfall, and interactions with other species that might affect populations. Their one-dimensional models captured how the populations changed, but not why they changed.

But Rogers and Munch “went looking for [chaos] in a more sensible way,” said Aaron King, a professor of ecology and evolutionary biology at the University of Michigan who was not involved in the study. Using three different complex algorithms, they analyzed 172 time series of different organisms’ populations as models with as many as six dimensions rather than just one, leaving room for the potential influence of unspecified environmental factors. In this way, they could check whether unnoticed chaotic patterns might be embedded within the one-dimensional representation of the population shifts. For example, more rainfall might be chaotically linked to population increases or decreases, but only after a delay of several years.

In the population data for about 34 percent of the species, Rogers, Johnson, and Munch discovered, the signatures of nonlinear interactions were indeed present, which was significantly more chaos than was previously detected. In most of those data sets, the population changes for the species did not appear chaotic at first, but the relationship of the numbers to underlying factors was. They could not say precisely which environmental factors were responsible for the chaos, but whatever they were, their fingerprints were on the data.

The researchers also uncovered an inverse relationship between an organism’s body size and how chaotic its population dynamics tend to be. This may be due to differences in generation time, with small organisms that breed more often also being more affected by outside variables more often. For example, populations of diatoms with generations of around 15 hours show much more chaos than packs of wolves with generations almost five years long.

However, that doesn’t necessarily mean that wolf populations are inherently stable. “One possibility is that we’re not seeing chaos there because we just don’t have enough data to go back over a long enough period of time to see it,” said Munch. In fact, he and Rogers suspect that because of the constraints of their data, their models might be underestimating how much underlying chaos is present in ecosystems.

Sugihara thinks that the new results might be important for conservation. Improved models with the right element of chaos could do a better job of forecasting toxic algal blooms, for example, or tracking fishery populations to prevent overfishing. Considering chaos could also help researchers and conservation managers to understand how far out it’s possible to meaningfully predict population size. “I do think that it’s useful for the issue to be in people’s minds,” he said.

However, he and King both caution against placing too much faith in these chaos-conscious models. “The classical concept of chaos is fundamentally a stationary concept,” King said. It is built on the assumption that chaotic fluctuations represent a departure from some predictable, stable norm. But as climate change progresses, most real-world ecosystems are becoming increasingly unstable even in the short term. Even taking many dimensions into account, scientists will have to be conscious of this ever-shifting baseline.

Still, taking chaos into consideration is an important step toward more accurate modeling. “I think this is really exciting,” said Munch. “It just runs counter to the way we currently think about ecological dynamics.”

Original story reprinted with permission from Quanta Magazine, an editorially independent publication of the Simons Foundation whose mission is to enhance public understanding of science by covering research developments and trends in mathematics and the physical and life sciences.

The Hidden Chaos That Lurks in Ecosystems

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It started with a single tweet in November 2019. David Heinemeier Hansson, a high-profile tech entrepreneur, lashed out at Apple’s newly launched credit card, calling it “sexist” for offering his wife a credit limit 20 times lower than his own.

The allegations spread like wildfire, with Hansson stressing that artificial intelligence – now widely used to make lending decisions – was to blame. “It does not matter what the intent of individual Apple reps are, it matters what THE ALGORITHM they’ve placed their complete faith in does. And what it does is discriminate. This is fucked up.”

While Apple and its underwriters Goldman Sachs were ultimately cleared by US regulators of violating fair lending rules last year, it rekindled a wider debate around AI use across public and private industries.

Politicians in the European Union are now planning to introduce the first comprehensive global template for regulating AI, as institutions increasingly automate routine tasks in an attempt to boost efficiency and ultimately cut costs.

That legislation, known as the Artificial Intelligence Act, will have consequences beyond EU borders, and like the EU’s General Data Protection Regulation, will apply to any institution, including UK banks, that serves EU customers. “The impact of the act, once adopted, cannot be overstated,” said Alexandru Circiumaru, European public policy lead at the Ada Lovelace Institute.

Depending on the EU’s final list of “high risk” uses, there is an impetus to introduce strict rules around how AI is used to filter job, university or welfare applications, or – in the case of lenders – assess the creditworthiness of potential borrowers.

EU officials hope that with extra oversight and restrictions on the type of AI models that can be used, the rules will curb the kind of machine-based discrimination that could influence life-altering decisions such as whether you can afford a home or a student loan.

“AI can be used to analyse your entire financial health including spending, saving, other debt, to arrive at a more holistic picture,” Sarah Kocianski, an independent financial technology consultant said. “If designed correctly, such systems can provide wider access to affordable credit.”

But one of the biggest dangers is unintentional bias, in which algorithms end up denying loans or accounts to certain groups including women, migrants or people of colour.

Part of the problem is that most AI models can only learn from historical data they have been fed, meaning they will learn which kind of customer has previously been lent to and which customers have been marked as unreliable. “There is a danger that they will be biased in terms of what a ‘good’ borrower looks like,” Kocianski said. “Notably, gender and ethnicity are often found to play a part in the AI’s decision-making processes based on the data it has been taught on: factors that are in no way relevant to a person’s ability to repay a loan.”

Furthermore, some models are designed to be blind to so-called protected characteristics, meaning they are not meant to consider the influence of gender, race, ethnicity or disability. But those AI models can still discriminate as a result of analysing other data points such as postcodes, which may correlate with historically disadvantaged groups that have never previously applied for, secured, or repaid loans or mortgages.

One of the biggest dangers is unintentional bias, in which algorithms discriminate against certain groups including women, migrants or people of colour.

Photograph: metamorworks/Getty Images/iStockphoto

And in most cases, when an algorithm makes a decision, it is difficult for anyone to understand how it came to that conclusion, resulting in what is commonly referred to as “black-box” syndrome. It means that banks, for example, might struggle to explain what an applicant could have done differently to qualify for a loan or credit card, or whether changing an applicant’s gender from male to female might result in a different outcome.

Circiumaru said the AI act, which could come into effect in late 2024, would benefit tech companies that managed to develop what he called “trustworthy AI” models that are compliant with the new EU rules.

Darko Matovski, the chief executive and co-founder of London-headquartered AI startup causaLens, believes his firm is among them.

The startup, which publicly launched in January 2021, has already licensed its technology to the likes of asset manager Aviva, and quant trading firm Tibra, and says a number of retail banks are in the process of signing deals with the firm before the EU rules come into force.

The entrepreneur said causaLens offers a more advanced form of AI that avoids potential bias by accounting and controlling for discriminatory correlations in the data. “Correlation-based models are learning the injustices from the past and they’re just replaying it into the future,” Matovski said.

He believes the proliferation of so-called causal AI models like his own will lead to better outcomes for marginalised groups who may have missed out on educational and financial opportunities.

“It is really hard to understand the scale of the damage already caused, because we cannot really inspect this model,” he said. “We don’t know how many people haven’t gone to university because of a haywire algorithm. We don’t know how many people weren’t able to get their mortgage because of algorithm biases. We just don’t know.”

Matovski said the only way to protect against potential discrimination was to use protected characteristics such as disability, gender or race as an input but guarantee that regardless of those specific inputs, the decision did not change.

He said it was a matter of ensuring AI models reflected our current social values and avoided perpetuating any racist, ableist or misogynistic decision-making from the past. “Society thinks that we should treat everybody equal, no matter what gender, what their postcode is, what race they are. So then the algorithms must not only try to do it, but they must guarantee it,” he said.

While the EU’s new rules are likely to be a big step in curbing machine-based bias, some experts, including those at the Ada Lovelace Institute, are pushing for consumers to have the right to complain and seek redress if they think they have been put at a disadvantage.

“The risks posed by AI, especially when applied in certain specific circumstances, are real, significant and already present,” Circiumaru said.

“AI regulation should ensure that individuals will be appropriately protected from harm by approving or not approving uses of AI and have remedies available where approved AI systems malfunction or result in harms. We cannot pretend approved AI systems will always function perfectly and fail to prepare for the instances when they won’t.”

Source

A new paper published in the Monthly Notices of the Royal Astronomical Society by researchers Tessa Vernstrom of The University of Western Australia and Christopher Reisely from Italy's Universita di Bologna describe a series of large, low-frequency objects roughly 800 million light years from Earth. Researchers used radio and X-Ray telescopes to study the trio of objects - a fossil radio emission, a radio relic, and a radio halo - located within the Abell 3266 galaxy cluster.

All three were too faint to detect until the researchers applied a complex algorithm to the telescope imagery of the cluster - and uncovered evidence of the supermassive black hole which had created it.

In an article published on The Conversation website, in which they also shared several images of their research, the pair explained: “They defy existing theories about both the origins of such objects and their characteristics.”

The radio relic, a sonic boom-like arc of radio waves are "powered by shockwaves travelling through the plasma”, especially caught the researchers' attention, they explained, revealing features “never been seen before”.

They added: “Its concave shape is also unusual, earning it the catchy moniker of a ‘wrong-way’ relic.

“Overall, our data break our understanding of how relics are generated, and we’re still working to decipher the complex physics behind these radio objects.”

The radio fossil, seen towards the upper right of the lead image, is very faint and red, indicating it was ancient, they pointed out.

The radio halo in Abell 3266 is shown here with red colours indicating the radio brightness

(Image: Christopher Riseley)

They added: “We believe this radio emission originally came from the galaxy at the lower left, with a central black hole that has long been switched off.

“Our best physical models simply can’t fit the data.

“This reveals gaps in our understanding of how these sources evolve – gaps that we’re working to fill.

The radio fossil in Abell 3266 is shown with red colours (Image: Christopher Riseley)

“Finally, using a clever algorithm, we de-focused the lead image to look for very faint emission that’s invisible at high resolution, unearthing the first detection of a radio halo in Abell 3266 [.]

“This is the beginning of the road towards understanding Abell 3266. We have uncovered a wealth of new and detailed information, but our study has raised yet more questions.

“The telescopes we used are laying the foundations for revolutionary science from the Square Kilometre Array project.

The ‘wrong-way’ relic in Abell 3266 (Image: Christopher Riseley)

The telescopes we used are laying the foundations for revolutionary science from the Square Kilometre Array project.

“Studies like ours allow astronomers to figure out what we don’t know – but you can be sure we’re going to find out.”

Speaking to the Australian Broadcast Company (ABC), Dr Verstrom pointed out the relic was also a great deal brighter in the radio spectrum than anticipated in any models.

She said: "So we don't really understand what that's telling us.

"Maybe there's some kind of new physics going on there that we haven't fully understood when our models can't match the observations."

There are thousands of galaxy clusters in the universe, Dr Vernstrom said - but stressed "surprisingly few" objects such as those in Abell 3266 has been spotted.

She added: "They are basically just hard to detect."

Source

According to a report in the journal Science Advances, the COVID-19 pandemic has altered how individuals perceive the passing of time.

The majority of research participants (65%) reported feeling that time was moving more slowly at the conclusion of the first month of social isolation, which occurred in May 2020. This perception was termed by the researchers as “time expansion,” and they discovered that it was linked to feelings of isolation and a lack of enjoyable activities throughout the time period.

Even more people (75%) said they didn’t experience as much “time pressure,” which is the sensation that time is passing more quickly and leaving less time for activities of daily living and recreation. 90% of those surveyed claimed they were taking shelter at home during that time.

“We followed the volunteers for five months to see if this ‘snapshot’ of the start of the pandemic would change over time. We found that the feeling of time expansion diminished as the weeks went by, but we didn’t detect significant differences with regard to time pressure,” André Cravo, first author of the article, told Agência FAPESP. Cravo is a professor at the Federal University of ABC in São Paulo state, Brazil.

The research started on May 6, when 3,855 participants recruited via social media responded to a ten-item online questionnaire and completed a simple task meant to test their ability for short interval estimation (pressing start and stop buttons in 1, 3, and 12 seconds). They were then questioned about their daily activities the week before (including whether they had finished all required tasks and how much time they had set aside for leisure) as well as how they were feeling right now (happy, sad, lonely, etc).

“They were invited to return every week for further sessions, but not everyone did,” Cravo said. “In the final analysis, we considered data for 900 participants who answered the questionnaire for at least four weeks, albeit not all consecutively.”

Using time awareness scales from 0 to 100 that are standard for this type of survey, the researchers analyzed the answers and calculated the two parameters – time expansion and time pressure – to see whether they increased or decreased week by week.

“Besides a rise or fall on the scales, we also analyzed the factors that accompanied the changes. During the five-month period, we observed a similar pattern: in weeks when participants reported feeling lonely and experiencing less positive affect, they also felt time pass more slowly. In highly stressful situations, they felt time pass more quickly,” Cravo said.

When the first set of answers to the question on the passage of time was compared with the second, provided at the end of the first month of confinement, perceptions of time expansion had risen 20 points while time pressure had fallen 30 points, according to Raymundo Machado, a scientist at the Brain Institute of the Albert Einstein Jewish Hospital (HIAE) in São Paulo, and last author of the article. “These results are evidently affected by memory bias, however, because no measurements were made before the pandemic,” he said.

Time slowed most for younger participants early in the pandemic, when compliance with social distancing rules was strictest. Except for age, demographic factors such as household size, occupation, and gender, had no influence on the results.

For the authors, this may be an effect of the sample profile. Most of the volunteers (80.5%) lived in the Southeast region. A large majority were women (74.32%). Most had completed secondary school, and a great many even had a university degree (71.78%). In terms of income, roughly a third were upper middle class (33.08%). Sizable minorities worked in education (19.43%) and healthcare (15.36%).

“This is typical of online surveys, where a majority are women living in the Southeast with high levels of formal education. The influence of demographics might have been more evident if the sample had represented the Brazilian population better,” Machado said.

Internal clock

Although the pandemic changed participants’ perceptions of the passage of time, it apparently did not affect their ability to sense duration, measured by the button-pressing task. “All of us are able to estimate short intervals. When the results of this time estimation test [including overestimation and underestimation of the intervals] were compared with the time awareness scores, there was no correlation,” Machado said.

According to Cravo, evidence from the scientific literature suggests the feeling that time is passing more slowly or more quickly is influenced mainly by two factors: the relevance of time in a particular context, and unpredictability. “For example, if you’re late for work [so that time is relevant in the context] and have to wait for a bus [unpredictable timing], you have an extreme perception that the minutes aren’t passing. When you’re on vacation and having fun, time isn’t relevant and appears to fly,” he said.

The perception often changes when we recall past situations. “When you remember what you did during a vacation, time seems to have lasted longer. On the contrary, when you’re standing in line, time goes all too slowly but when you recall the situation sometime later, it feels as if it was over quickly,” Cravo said.

In the case of the COVID-19 pandemic, how people will remember the passage of time during the period of social distancing is unknown. “Several temporal milestones, such as Carnival, the June festivals, and birthdays, had to be skipped in the last two years, so the question remains open,” he concluded.

Reference: “Time experience during social distancing: A longitudinal study during the first months of COVID-19 pandemic in Brazil” by André Mascioli Cravo, Gustavo Brito de Azevedo, Cristiano Moraes Bilacchi Azarias, Louise Catheryne Barne, Fernanda Dantas Bueno, Raphael Y. de Camargo, Vanessa Carneiro Morita, Esaú Ventura Pupo Sirius, Renan Schiavolin Recio, Mateus Silvestrin and Raymundo Machado de Azevedo Neto, 13 April 2022, Science Advances.

DOI: 10.1126/sciadv.abj7205

The study was funded by FAPESP.

Source

It’s a critical time for Apple, as it prepares to launch the next generation of iPhones this fall, and suppliers are currently assembling various components for the new smartphones.

According to a report by Nikkei Asia, Pelosi’s visit “stoked fears of rising trade barriers,” making Apple nervous about “possible disruptions” if crucial shipments are delayed or even blocked in customs due to a failure to appease China’s labelling demands:

Apple told suppliers on Friday that China has started strictly enforcing a long-standing rule that Taiwanese-made parts and components must be labeled as being made either in “Taiwan, China” or “Chinese Taipei,” sources familiar with the matter told Nikkei Asia, language that indicates the island is part of China…

 Using the phrase “Made in Taiwan” on any import declaration forms, documents or cartons could cause shipments to be held and checked by Chinese customs, the sources added. Penalties for violating such a rule is a fine of up to 4,000 yuan ($592) or, in the worst-case scenario, the shipment being rejected, one of the sources said.

 This presents a dilemma for suppliers who need to ship materials, components or parts from Taiwan to China, however, as the democratically governed island also requests that all exports be labeled with product of origin, which means they must carry the words “Taiwan” or “Republic of China,” the island’s official name, according to suppliers and logistics companies.

It’s not a hypothetical problem, but rather an issue that is already happening. Shipments from Taiwan to facilities operated by Pegatron, an iPhone assembler, in Suzhou, China were “held for review” Thursday while Chinese officials inspected the import declaration forms and cartons to determine if they were labeled “Taiwan” or “Republic of China,” Nikkei Asia reported.

A senior Pegatron executive was among several Taiwanese chip industry corporate leaders who attended the lunch with Pelosi that was hosted by Taiwanese President Tsai Ing-wen Wednesday, the report noted, perhaps highlighting another reason the company found itself under increased scrutiny.

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After reviewing hundreds of scientific papers on “cultural ecosystem services,” or the nonmaterial benefits of nature, researchers have identified 227 unique pathways through which people’s interactions with nature can positively or negatively affect well-being, according to a paper published Friday in the peer-reviewed journal Science Advances.

The paper is believed to be the first of its kind to provide a comprehensive framework for understanding and quantifying the complex ways in which people and nature are connected. And its findings could have significant real-world implications, said Lam Thi Mai Huynh, the paper’s lead author and a doctoral candidate at the University of Tokyo.

“For the modernized world, people tend to disconnect from nature,” she said. “For ecosystem management, the best solution, the most sustainable solution, is to connect people back to nature and let the local people be the ones who help to maintain and manage the ecosystem services.”

For Huynh, the ambitious research — an undertaking that even her academic supervisor initially thought might not be possible — stemmed from a desire to improve understanding of the complicated underlying processes behind how nature’s intangible effects — such as opportunities for recreation and leisure or spiritual fulfillment — have an impact on well-being. One major challenge, though, is that much of the existing scientific literature on cultural ecosystem services has been “highly fragmented,” the review noted.

“You have all sorts of different people looking at [the intangible benefits of nature] through a different lens,” said Alexandros Gasparatos, an associate professor at the Institute of Future Initiatives at the University of Tokyo who co-authored the paper. Although having diverse research is critical, he said, “it becomes a little bit difficult to bring everything together.”

But the new study, a systematic review of roughly 300 peer-reviewed scientific papers, creates “an excellent knowledge base,” Gasparatos said.
“The whole point of doing this exercise is to understand the connection,” he added. “We give names to phenomena.”

The review breaks down the hundreds of possible links between individual aspects of human well-being (mental and physical health, connectedness and belonging, and spirituality, among others) and cultural ecosystem services, such as recreation and tourism, aesthetic value and social relation. The researchers then went a step further and identified more than a dozen distinct underlying mechanisms through which people’s interactions with nature can affect their well-being.

Researchers found that the highest positive contributions were seen in mental and physical health. Recreation, tourism and aesthetic value appeared to have the greatest impact on human health through the “regenerative” mechanism, or experiencing restorative effects from being in nature such as stress relief, according to the paper. Meanwhile, the highest negative effects are linked to mental health through the “destructive” mechanism, or direct damages associated with the degradation or loss of cultural ecosystem services, the researchers wrote.

“In reality, you don’t just have one pathway,” and the effects aren’t always positive, Gasparatos said. “It’s not that if I go to the forest, I receive one thing.”
A well-designed park, for example, can be a place for recreation and leisure as well as connecting with other people. You might also find yourself appreciating the sight of towering trees and lush greenery or birds and other wildlife. On the other hand, a poorly maintained natural space could lead to an ugly or visually threatening landscape that might make you feel uncomfortable or scared to be there.

The paper can provide a road map of sorts, Huynh said, to help people, particularly decision-makers, understand that there are not only various intangible benefits to interactions with nature, but also how to try to achieve them.

© Provided by The Washington Post

Nature can affect human well-being in many more ways than you think

The research was widely applauded by several outside experts who were not involved in the work.

“It’s a long time coming to have a study like this that makes some of these linkages a little clearer,” said Keith Tidball, an environmental anthropologist at Cornell University. “This stuff has been scattered all over the place for a long, long time, and this paper takes a huge step forward in sorting out what has been previously pretty muddled.”

Anne Guerry, chief strategy officer and lead scientist with the Natural Capital Project at Stanford University, agreed. “They did a really nice job of bringing together extraordinarily diverse literature,” she said. It’s been a challenge, she noted, among researchers to be able to present the science in a way that reveals where and how nature provides the greatest benefits to people, which could in turn help “inform and motivate investments in conservation and restoration that lead to better outcomes for both people and nature.”

For instance, the research could have an impact on the role nature potentially plays in human health. “What this is going to be seriously useful for is to be able to continue to work to make the case that physicians and clinicians can actually prescribe outdoor time, outdoor recreation, even outdoor space because of these pathways that they’ve identified in this paper,” Tidball said.

In one scenario, elements of this work could ultimately be included in the Diagnostic and Statistical Manual of Mental Disorders, said Elizabeth Haase, chair of the American Psychiatric Association’s Committee on Climate Change and Mental Health.

“That sets us up to be able to say that when we facilitate this kind of interaction with nature, you see this kind of benefit, and then prescribe these kinds of natural experiences, or have policies that say that you’re really depriving someone of their mental health if you destroy these natural landscapes,” she said.

But the review does have limitations, prompting some experts to caution against overinterpreting or overemphasizing its results.

One potential issue is that the existing research included in the review disproportionately focuses on individuals rather than groups.

“There are multiple times where something might be really good for an individual, but overall for the community, it might not be very good at all,” said Kevin Summers, a senior research ecologist with the Office of Research and Development at the Environmental Protection Agency.

“In many cases, there can be unintended consequences for things that look like very simple, straightforward decisions,” Summers added.

Other research gaps should also be taken into account, Guerry said. While the review suggests that some connections between certain human well-being characteristics and cultural ecosystem services appear stronger than others, it doesn’t mean those other relationships might not be significant, she said.

“We have to be careful in terms of oversimplifying the results and thinking that a lack of a documented relationship in this paper means that something isn’t important,” she said. Instead, it may mean that “it hasn’t been studied and we haven’t found ways to quantify it and bring it into the scientific literature and out of our sort of implicit understanding.”

The researchers addressed the limitations of their work, noting in the paper that future research “should explore in-depth how these pathways and mechanisms manifest in less studied ecosystems and understand their differentiated effects to various stakeholders.”

In the meantime, though, the findings serve as an important reminder of nature’s necessity.

“It can justify, very well, a mind-set like, ‘Let’s invest in nature because it has all these benefits,’ ” Gasparatos said.

With such strong positive benefits related to creativity, belonging, regeneration and more, “it’s easy from this paper to feel that your constitutional right to the pursuit of happiness requires a country to preserve natural spaces,” Haase added.

In a time when many people are becoming further separated and distanced from “our ecological selves,” efforts to link humans and nature are not only interesting in terms of science, philosophy or ethics, Tidball said, but “there are also human security implications here that are significant.” And, he said, if steps aren’t taken to reconnect people with nature, the consequences could be dire.

“If we continue on a pathway as a species of being in a state of ecological amnesia,” he said, “we’re going to find ourselves out of habitat and out of time and, therefore, out of luck.”

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On July 12, the first full-color images from the Webb Space Telescope showed countless nebulae, galaxies, and a gassy exoplanet as they had never been seen before. But Webb only collects infrared and near-infrared light, which the human eye cannot see—so where are these gorgeous colors coming from?

Image developers on the Webb team are tasked with turning the telescope’s infrared image data into some of the most vivid views of the cosmos we’ve ever had. They assign various infrared wavelengths to colors on the visible spectrum, the familiar reds, blues, yellows, etc. But while the processed images from the Webb team aren’t literally what the telescope saw, they’re hardly inaccurate.

“Something I’ve been trying to change people’s minds about is to stop getting hung up on the idea of ‘is this what this would look like if I could fly out there in a spaceship and look at it?’” said Joe DePasquale, a senior data image developer at the Space Telescope Science Institute, in a phone call with Gizmodo. “You don’t ask a biologist if you can somehow shrink down to the size of a cell and look at the coronavirus.”

Mid-infrared (left) and near-infrared (right) views of a lensing galaxy cluster, SMACS 0723.
Image: STScI

Webb’s first test images helped check its mirrors’ alignment and captured an orange-tinted shot of the Large Magellanic Cloud. Those early snapshots were not representative color images; one used a monochromatic filter (its image was grayscale) and the other just translated infrared light into the red-to-yellow visible color bands, so the team could see certain features of the cloud they imaged. But now, with the telescope up and running, the images that get released are full of blazing color, like this recent portrait of the Cartwheel Galaxy.

Astronomy is often done outside the visible spectrum, because many of the most interesting objects in space are shining brightly in ultraviolet, x-rays, and even radio waves (which category light falls into depends on the photon’s wavelength). The Webb Telescope is designed to see infrared light, whose wavelengths are longer than red visible light but shorter than microwaves.

Infrared light can penetrate thick clouds of gas and dust in space, allowing researchers to see previously hidden secrets of the universe. Especially intriguing to scientists is that light from the early universe has been stretched as the universe has expanded, meaning what was once ultraviolet or visible light may now be infrared (what’s known as “redshifted” light).

The wavelengths of the electromagnetic spectrum.
Graphic: Wikimedia Commons

“These are instruments that we’ve designed to extend the power of our vision, to go beyond what our eyes are capable of doing to see light that our eyes are not sensitive to, and to resolve objects that we can probably see with just our eyes,” DePasquale said. “I’m trying to bring out the most detail and the most richness of color and complexity that’s inherent in the data without actually changing anything.”

Webb’s raw images are so laden with data that they need to be scaled down before they can be translated into visible light. The images also need to be cleaned of artifacts like cosmic rays and reflections from bright stars that hit the telescope’s detectors. If you look at a Webb image before processing work is done, it’ll look like a black rectangle peppered with some white dots.

A raw image of the Carina Nebula as seen by NIRCam, before the infrared light is translated into visible wavelengths.
Image: Space Telescope Science Institute

The same star-forming region of the Carina Nebula, seen after the infrared data is translated to visible wavelengths. Bright stars have large diffraction spikes,

an artifact of being imaged by Webb.
Image: NASA, ESA, CSA, and STScI

“I think there’s some connotations that go along with ‘colorizing’ or ‘false color’ that imply there’s some process going on where we’re arbitrarily choosing colors to create a color image,” DePasquale said. “Representative color is the most preferred term for the kind of work that we do, because I think it encompasses the work that we do of translating light to create a true color image, but in a wavelength range that our eyes are not sensitive to.”

Longer infrared waves are assigned redder colors, and the shortest infrared wavelengths are assigned bluer colors. (Blue and violet light has the shortest wavelengths within the visible spectrum, while red has the longest.) The process is called chromatic ordering, and the spectrum is split into as many colors as the team needs to capture the full spectrum of light depicted in the image.

“We have filters on the instruments that collect certain wavelengths of light, which we then apply a color that is most closely what we think it will be on the [visible] spectrum,” said Alyssa Pagan, a science visuals developer at the Space Telescope Science Institute, in a phone call with Gizmodo.

The chromatic ordering depends too on what elements are being imaged. When working with narrow-band wavelengths in optical light—oxygen, ionized hydrogen, and sulfur, Pagan suggests—the latter two both emit in red. So the hydrogen might get shifted to green visible light, in order to give the viewer more information.

“It’s a balance between the art and the science, because you want to showcase science and the features, and sometimes those two things don’t necessarily work together,” Pagan added.

Webb’s first representative color images were released July 12, over six months after the telescope launched from an ESA spaceport in French Guiana. From there, Webb traveled about a million miles to L2, a point in space where gravitational effects allow spacecraft to stay in place without burning much fuel.

The telescope unfolded itself on the way to L2, so once it was there, mission scientists could get started on aligning the $10 billion observatory’s mirrors and commissioning its instruments. The telescope has four instruments: a near-infrared camera (NIRCam), a near-infrared spectrograph, a mid-infrared instrument (MIRI), and a fine guidance sensor and slitless spectrograph for pointing at targets precisely and characterizing exoplanet atmospheres.

The voluminous amounts of dust in some galaxies and nebulae are transparent to NIRCam, allowing it to capture bright stars at shorter wavelengths. MIRI, on the other hand, can observe discs of material that will give way to planets as well as dust warmed by starlight.

When telescope images are being assembled, image processors work with instrument scientists to decide which features of a given object should be highlighted in the image: its piping hot gas, perhaps, or a cool dusty tail.

Stephan’s quintet as seen by three MIRI filters. Galactic “skittles” are seen in the background.
Image: STScI

When Webb imaged Stephan’s Quintet, a visual grouping of five galaxies, the finished product was a 150-million-pixel image made up of 1,000 images taken by both MIRI and NIRCam. When just seen by MIRI, though, hot dust dominates the image. In the background of the MIRI images, distant galaxies glow in different colors; DePasquale said the team calls them “skittles.”

DePasquale and Pagan helped create the Webb images as we would eventually see them, rich in color and cosmic meaning. In the case of the sweeping shot of the Carina Nebula’s cosmic cliffs, different filters captured the ionized blue gas and red dust. In initial passes at the nebula image, the gas obscured the dust’s structure, scientists asked the image processing team to “tone down the gas” a bit, Pagan said.

Collecting light in Webb’s hexagonal mirrors is only half the battle when it comes to seeing the distant universe. Translating what’s there is another beast entirely.

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They're a few of the many animal species to have contracted COVID-19.

But how many species have been affected? And how many cases have there been in the animal kingdom?

Those are difficult questions to answer – just as it's hard to come up with an accurate total for human cases, since many people don't report a positive test to health authorities. Yet it's an important task, say researchers, because of the possibility that the virus could mutate into a perhaps more transmissible or virulent strain in animals and then pass back to humans.

Now there's a first effort at compiling a global database of animal counts. Amélie Desvars-Larrive, professor at the University of Veterinary Medicine Vienna, and her team of Austrian researchers combed the internet for data from official sources. On July 23, her team in collaboration with the Wildlife Conservation society published the first COVID data tracking dashboard for cases in animals in Scientific Data.

It's preliminary — but still helpful

The interactive visualization lets users explore which animals have gotten COVID, how many cases were reported for each species and the source of the data. It also covers what happened to the animals, ranging from mild symptoms like a runny nose to more severe symptoms like myocarditis or even sudden death.

This graphic, part of an interactive COVID data tracking dashboard rendered by Complexity Science Hub Vienna, shows reported clinical signs of SARS-CoV-2 infection or exposure in animals. Note: "subclinical" means no detectable symptoms.
Complexity Science Hub Vienna/Screenshot by NPR

The number of cases reported are undercounts, since there's no systematic gathering of information across countries, among other reasons. But scientists say it is a welcome addition to the body of COVID data.

"[COVID surveillance in animals] has been through either activities at a governmental level or through independent research," says Meghan Davis, professor of environmental health at Johns Hopkins, who was not involved in the study. "What these authors did very well was identifying some of the most likely sources of data and then pulling this information together into a graphical interface.

"This dashboard is incredibly useful at communicating information and bringing together data from multiple sources. People who make public health decisions or are interested in this topic can now interact with the data without needing to go to all of these different sources," says Davis.

"What was new to me was to see [how the number of COVID infections] in the different species compared," says Wim van der Poel, veterinarian and professor of zoonotic viruses at Wageningen University in the Netherlands. Van der Poel was acknowledged in the paper but not involved in the study.
And the limitations of the tracker might help highlight where better reporting or testing initiatives on COVID in animals are needed. "[The dashboard] shows us where we may need to increase our activities," says Davis. "It's really showed me where we have surveillance gaps or lack of reporting."

The study authors acknowledge the gaps.

For example, comparing case counts from country to country isn't useful for understanding which countries have the most cases in animals because "low- and middle-income countries cannot search for COVID in animals as they need to target resources for testing to humans," says Desvars-Larrive.

The statistics about death rates are likely overestimates due to the high number of unreported asymptomatic cases. "The reported cases are only the tip of the iceberg and the symptomatic ones are the tip of the tip of the iceberg," says Desvars-Larrive. "The data don't show the true mortality rate. I think the case fatality rate in animal is low, actually."

How many animals, how many species?

The dashboard has so far collected 704 cases of COVID in animals from the Program for Monitoring Emerging Diseases and the World Animal Health Information System. There are 27 different species cited from 39 different countries. Those cases are typically confirmed through a PCR test.

The most confirmed cases are in mink, with 187 cases, followed closely by cats and dogs with 177 and 160 confirmed cases respectively. More often than not, the CDC theorizes that those cats and dogs got COVID from their owners, even though there hasn't been a large study confirming that theory.

In late 2020, an outbreak of COVID among mink on fur farms led Denmark to cull 17 million animals. The photo was taken at the farm run by Stig Sørensen in Bording on Nov. 7, 2020.
Ole Jensen/Getty Images

They caught it from us. Can they infect us as well?

The question that looms over this enterprise: Can animals pass COVID back to humans?

In late 2020, an outbreak of COVID in mink fur farms resulted in some of the caretakers contracting the virus and ultimately led Denmark to cull 17 million of the animals. And late last year COVID infections transmitted from hamsters to people sparked an outbreak in Hong Kong.

Staff members of Hong Kong's Health Department collect samples at a pet store in January. Authorities linked at least 3 cases of COVID to infected hamsters.
Li Zhihua/China News Service via Getty Images

The cases of COVID transmission from minks and hamsters both happened in situations where people were caretakers for a large number of animals. But just last month, the first evidence of COVID being passed from a cat to a person was reported. According to a study published last month in Emerging Infectious Diseases, the cat sneezed in the face of a veterinary surgeon who was testing the animal for COVID. Three days later the vet tested positive for COVID, but none of the vet's close contacts did, suggesting the vet got the virus from the infected cat.

There's also a concern that wildlife infected with COVID — like a population of deer in Pennsylvania and other parts of North America — could become reservoirs for the virus, meaning the virus can circulate in them, perhaps even mutate into more transmissible or virulent strains and get passed back to humans. "That could mean that there is a continuing risk from those animals for public health," says van der Poel. "But we have not seen [evidence of a wildlife animal reservoir] yet."

Scientists still don't know how those deer got COVID. It's unlikely the deer caught it from direct contact with humans, though transmission from contaminated wastewater or other infected animals, like feral cats, are possibilities.

As for the risk of pets and other animals transmitting the virus to humans? "I don't think that there is that is that is a major risk," says van der Poel. The CDC agrees that the risk of catching COVID from an animal is very low. Says van der Poel: "The risk to contract COVID from other people is far higher than from an animal."

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For folks out there looking for a third-party perspective on the situation that does not involve Google or its ex-employee Lemoine, Standford University co-director of the Human-centered Artificial Intelligence (HAI), John Etchemendy, has stepped in. And like Google, Etchemendy is not impressed by Lemoine's claims, and has labeled the stories out there about Google's sentient AI as "pure clickbait".

He said:

Sentience is the ability to sense the world, to have feelings and emotions and to act in response to those sensations, feelings and emotions.

 LaMDA is not sentient for the simple reason that it does not have the physiology to have sensations and feelings. It is a software program designed to produce sentences in response to sentence prompts.

 When I saw the Washington Post article, my reaction was to be disappointed at the Post for even publishing it.

 They published it because, for the time being, they could write that headline about the ‘Google engineer’ who was making this absurd claim, and because most of their readers are not sophisticated enough to recognize it for what it is. Pure clickbait.

Richard Fikes, emeritus professor of computer science at Stanford, says in agreement that LaMDA was simply trying to respond like a human rather than actually becoming like one. He said:

You can think of LaMDa like an actor; it will take on the persona of anything you ask it to. [Lemoine] got pulled into the role of LaMDa playing a sentient being.

Hence, many, including Fikes, believe that Blake Lemoine fell for the ELIZA Effect which is just a tendency to unconsciously assume computer behaviors to be analogous with humans.

Source: Stanford Daily

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A new study out of Tufts University led to a multitude of fresh headlines that meat increases the risk of heart disease. It would seem that the danger of meat is now a foregone conclusion, but this paper, like so many others, is marred by significant scientific missteps and financial conflicts of interest, including a drug-development program at the Cleveland Clinic, funded in part by Procter & Gamble.

On scientific grounds alone, the paper is less-than convincing: Its findings are based on a low-quality type of data that, on the whole, can only show associations, not cause-and-effect relationships. What’s more, the associations reported are tiny: 1.15 for unprocessed red meat, 1.22 for total meat, and 1.18 for all animal foods. These numbers are close to 1 (= zero risk), and they’re all well below the threshold for ruling out other possible explanations for the observed results.

Further, the study blames a metabolite called TMAO (trimethylamine N-oxide) for red meat’s apparent harms, but the food that most boosts TMAO is not red meat, but fish!

Published in Atherosclerosis, Thrombosis, and Vascular Biology (ATVB), the study looks at data on 3,931 adults aged 65 and older from the Cardiovascular Health Study, who were followed from 1989-90 onwards, for a median of 12.5 years. Twice during the study, subjects filled out a “food frequency questionnaire” (FFQ) in which they were asked to remember the foods they’d eaten for the past year. Different questionnaires were used for each data collection, and a test of how well the two could be combined yielded correlations as low as .56 (1 is a perfect correlation).1 A well-known problem with FFQs is that people don’t report accurately the foods they eat; hardly anyone can recount what they’ve eaten two days ago much less over the past year.2

FFQ questions themselves can skew results. In this study’s merged dataset, for instance, only 4 questions were used to gather information about red-meat consumption: on bacon, hot dogs, hamburgers, and a category called “beef, pork, lamb.”3 Compare this to the 28 questions on various types of vegetables. It’s well-known that the more questions asked, the better the data, and this FFQ, named after its inventor, Walter Willett at Harvard University, was clearly designed to get better data on vegetables--less so on meat.

This post should really end here. We should feel at ease setting aside these headlines and wait for a study using better FFQs and yielding an association (measured by “relative risk”) greater than 2. Relative risks below 2 should be “viewed with caution,” said a publication of the National Cancer Institute.4

The numbers 1.15-1.22 in this study imply that other factors (called “confounders”) may be causing the slightly greater heart-disease risk observed. For instance, it’s known that red-meat eaters tend to smoke more and exercise less. People eating hot dogs and hamburgers are also likely to be accompanying those foods with milkshakes and French fries, yet the ATVB study does not report adjusting for sugar or overall carbohydrate intake.

The idea that TMAO causes heart disease and that meat consumption is its principal cause is a theory promoted by Dr. Stanley L. Hazen of the Cleveland Clinic. His first paper came out in 2011, and he started blaming red meat in 2013. The current paper, on which he’s an author, proposes the following mechanisms for TMAO’s links to heart disease:

 In experiments, TMAO promotes macrophage foam cell formation,[8] vascular inflammation and inflammasome activation,[9–12] endothelial dysfunction,[13] platelet hyperreactivity and thrombosis,[14,15] and decreases reverse cholesterol transport.[16]

It would be nice if the paper explained that eight of the nine experiments cited here (citations 8-16 in the paper) were conducted not on people but on mice or in test tubes, a type of data that is speculative and cannot be assumed to extend to humans. The one experiment performed on actual people showed “enhanced platelet aggregation” (leading potentially to thrombosis) when subjects were fed TMAO supplements. However, TMAO from supplements appears to be absorbed differently than TMAO from food, so this entire pathway is far from certain.

You might be wondering why the authors are focusing on TMAO, when we’ve been told for decades that red meat is bad for health due to saturated fat and cholesterol. What happened to those explanations? As it turns out that in recent years, the science to justify them has been shown to be weak. A major “State of the Art” review in the Journal of the American College of Cardiology, concluded in 2020 that, when it came to heart disease, the evidence was insufficient to justify continued caps on saturated fats. And the American Heart Association together with the American College of Cardiology issued a 2013 review stating that there was insufficient evidence to show a relationship between dietary cholesterol and blood cholesterol.

The ATVB authors downplay the importance of cholesterol and saturated fat. Evidently an alternative explanation is needed for heart disease and red meat as its cause.

If TMAO is their answer, however, they should really be warning against fish, not meat. Cod yields 65+ times more TMAO than beef, and halibut, at least 100 times more, according to a 1999 study that examined the effects of 46 foods on TMAO excreted in human urine. Carrots, cauliflower, peas, peanuts and potatoes also lead to far more TMAO than beef. A 2017 analysis came straight out and called the TMAO story “a red herring.” Red meat is clearly not the problem.

In many areas of science, it would be unseemly to suggest that researchers have conflicts of interest, but nutrition science is often enigmatic unless you follow the money. The funds flowing from the food and pharmaceutical industries into this field are massive—and have been since the 1940s at least.

Multinational packaged food companies would like you to eat boxed cereal instead of eggs and macaroni rather than meat. Pharmaceutical companies, for their part, may invest in certain lines of research as a foundation for the development of drugs or devices. Yet is it fair to ascribe bias to this paper?

Unfortunately, yes. The paper’s senior author, Dariush Mozaffarian, Dean of the Tufts Friedman School of Nutrition Science and Policy at Tufts University, is also the creator of the “Food Compass” rating system, which found Lucky Charms, Frosted Flakes and altogether 70 brand-named cereals from General Mills, Kellogg’s, and Post to be worthy of rankings far higher than eggs or ground beef, as I wrote about here.

The Food Compass also reflects a specific bias against red and processed meats by subtracting up to 10 points (out of 100) “simply for being themselves,” as researcher Zoe Harcombe explains in this excellent blog post. Points were also deducted for a food’s cholesterol content, even though, as explained above, there’s no evidence to show that dietary cholesterol contributes to heart disease. And the Food Compass gives no credit to red meat for containing heme iron and other needed nutrients that are in the forms more easily absorbed by humans than when consumed via plants or supplements. The top score meat could obtain in this rating system was 73, Harcombe calculates. In other words, Mozaffarian built a bias against meat into his model.

Mozaffarian discloses in the ATVB paper that he receives funding from Barilla, the world’s largest pasta company—which clearly stands to benefit if meat is sidelined off the dinner plate. (Barilla has invested heavily in nutrition researchers and in promoting the idea that meat as bad for the climate).

Mozaffarian also receives funds from the Gates Foundation, whose founder has campaigned widely against beef while also being one of the top investors in meat-replacement companies; and Bunge, a major producer of plant-based meat and dairy replacements (Mozaffarian does not disclose Bunge in the ATVB paper but reports it elsewhere).

Co-author Stanley Hazen, the ‘inventor’ of the TMAO hypothesis, turns out to have been in a partnership with Procter & Gamble (P&G) since 2015. This includes a “Joint Development Agreement” with P&G “to develop an over-the-counter product that can help people manage their TMAO levels.” P&G has participated in and paid for Hazen’s research while also employing him as a consultant, as Hazen reported in 2018 and again in the ATVB paper. Hazen also consistently discloses being named as a coinventor on “pending and issued patents held by the Cleveland Clinic relating to cardiovascular diagnostics and therapeutics.” A search of the US patent database for “Cleveland Clinic” and “trimethylamine N-oxide” yields 23 existing patents.

Of the 83 news stories now published on the new TMAO study, I’m willing to bet that few-to-none of them report on the major conflict of interest with P&G, even though it’s easy to find. Many of these stories begin with the exact same line, clearly from a press release: “A daily hamburger might raise the risk of developing heart disease…”

The motives behind this paper are clearly complex yet one thing is clear: a tenable case against red meat, this paper is not.

Further reading on TMAO:

Does Carnitine from Red Meat Cause Heart Disease? Blog by Georgia Ede on a widely covered 2013 paper by S. Hazen;

Choline and Eggs: Eggs still don't cause heart disease, Blog by Chris Kresser, 2019;

Meat, Plants, and TMAO, Blog by Zoe Harcombe, on a 2020 paper by Christopher Gardner.

1 Feskanich D, Rimm EB, Giovannucci EL, Colditz GA, Stampfer MJ, Litin LB, Willett WC. Reproducibility and validity of food intake measurements from a semiquantitative food frequency questionnaire. J Am Diet Assoc. 1993 Jul;93(7):790-6. doi: 10.1016/0002-8223(93)91754-e. PMID: 8320406, This is reference #37 in the ATVB paper. If you look at Table 1, you’ll see the correlations had large confidence intervals. The correlations for animal foods ranged from .07 to .87, which means the reliability of combining these surveys is pretty much unknown.

2 For more on the problems of nutritional epidemiology, including a recounting of how Harvard University’s Walter Willett defended epidemiology among his colleagues in a closed forum, see my book, pp.261-265.

3 Ibid.

4 There is in fact a raging debate about whether this standard, from 2002, should still be applied, since nearly all relative risks found in nutritional epidemiology fall below 2. Epidemiologists in nutrition argue that their methods have become more accurate in recent years. We can leave that debate aside for this study, however, since the data were collected from 1989 to 1996 with only phone-call follow-ups after that.

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It was a mild winter's morning at the height of the Cold War.

On January 17, 1966, at around 10:30am, a Spanish shrimp fisherman watched a misshapen white parcel fall from the sky… and silently glide towards the Alboran Sea. It had something hanging beneath it, though he couldn’t make out what it was. Then it slipped beneath the waves.

At the same time, in the nearby fishing village of Palomares, locals looked up at an identical sky and witnessed a very different scene – two giant fireballs, hurtling towards them. Within seconds, the sleepy rural idyll was shattered. Buildings shook. Shrapnel sliced towards the ground. Body parts fell to the earth.

A few weeks later, Philip Meyers received a message via a teleprinter – a device a bit like a fax that could send and receive primitive emails. At the time, he was working as a bomb disposal officer at the Naval Air Facility Sigonella, in eastern Sicily. He was told that there was a top secret emergency in Spain, and that he must report there within days.

However, the mission was not as covert as the military had hoped. "It was not a surprise to be called," says Meyers. Even the public knew what was going on. When he attended a dinner party that evening and announced his mysterious trip, its intended confidentiality became something of a joke. "It was kind of embarrassing," says Meyers. "It was supposed to be a secret but my friends were telling me why I was going."

For weeks, newspapers around the globe had been reporting rumours of a terrible accident – two US military planes had collided in mid-air, scattering four B28 thermonuclear bombs across Palomares. Three were quickly recovered on land – but one had disappeared into the sparkling blue expanse to the south east, lost to the bottom of the nearby swathe of Mediterranean Sea. Now the hunt was on to find it – along with its 1.1 megatonne warhead, with the explosive power of 1,100,000 tonnes of TNT.

The lost bombs at Palomares scattered seven pounds (3.2kg) of plutonium into the wild (Credit: Getty Images)

An unknown number

In fact, the Palomares incident is not the only time a nuclear weapon has been misplaced. There have been at least 32 so-called "broken arrow" accidents – those involving these catastrophically destructive, earth-flattening devices – since 1950. In many cases, the weapons were dropped by mistake or jettisoned during an emergency, then later recovered. But three US bombs have gone missing altogether – they're still out there to this day, lurking in swamps, fields and oceans across the planet.

"We mostly know about the American cases," says Jeffrey Lewis, director of the East Asia Non-proliferation Program at the James Martin Center for Non-proliferation Studies, California. He explains that the full list only emerged when a summary prepared by the US Department of Defense was declassified in the 1980s.

Many occurred during the Cold War, when the nation teetered on the precipice of Mutually Assured Destruction (MAD) with the Soviet Union – and consequently kept airplanes armed with nuclear weapons in the sky at all times from 1960 to 1968, in an operation known as Chrome Dome.

"We don't know as much about other countries. We don't really know anything about the United Kingdom or France, or Russia or China," says Lewis. "So I don't think we have anything like a full accounting."

The Soviet Union's nuclear past is particularly murky – it had amassed a stockpile of 45,000 nuclear weapons as of 1986. There are known cases where the country lost nuclear bombs that have never been retrieved, but unlike with the US incidents, they all occurred on submarines and their locations are known, if inaccessible.

One began on 8 April 1970, when a fire started spreading through the air conditioning system of a Soviet K-8 nuclear-powered submarine while it was diving in the Bay of Biscay – a treacherous stretch of water in the northeast Atlantic Ocean off the coasts of Spain and France, which is notorious for its violent storms and where many vessels have met their end. It had four nuclear torpedoes onboard, and when it promptly sank, it took its radioactive cargo with it.

However, these lost vessels didn't always stay where they were. In 1974, a Soviet K-129 mysteriously sank in the Pacific Ocean, along with three nuclear missiles. The US soon found out, and decided to mount a secret attempt to retrieve this nuclear prize, "which was really a pretty crazy story in and of itself", says Lewis.

Today the US' nuclear defences consist of land-based intercontinental ballistic missiles (ICBMs), bomber aircraft, and ballistic missile submarines (SSBNs) (Credit: Getty Images)

The eccentric American billionaire Howard Hughes, famous for his broad spectrum of activity, including as a pilot and film director, pretended to become interested in deep sea mining. "But in fact, it wasn't deep sea mining, it was an effort to build this giant claw that could go all the way down to the sea floor, grab the submarine, and bring it back up," says Lewis. This was Project Azorian – and unfortunately it didn't work. The submarine broke up as it was being lifted.

"And so those nuclear weapons would have fallen back to the sea floor," says Lewis. The weapons remain there to this day, trapped in their rusting tomb. Some people think the weapons remain there to this day, trapped in their rusting tomb – though others believe they were eventually recovered.

Every now and then, there are reports that some of the US' lost nuclear weapons have been found.

Back in 1998, a retired military officer and his partner were gripped with a sudden determination to discover a bomb dropped near Tybee Island, Georgia in 1958. They interviewed the pilot who had originally lost it, as well as those who had searched for the bomb all those decades ago – and narrowed down the search to Wassaw Sound, a nearby bay of the Atlantic Ocean. For years, the maverick duo scoured the area by boat, trailing a Geiger counter behind them to detect any tell-tale spikes in radiation.

And one day, there it was, in the exact spot the pilot had described – a patch with radiation 10 times the levels elsewhere. The government promptly dispatched a team to investigate. But alas, it was not the nuclear weapon. The anomaly was down to naturally occurring radiation from minerals in the seabed.

So for now, the US' three lost hydrogen bombs – and, at the very least, a number of Soviet torpedoes – belong to the ocean, preserved as monuments to the risks of nuclear war, though they have largely been forgotten. Why haven't we found all these rogue weapons yet? Is there a risk of them exploding? And will we ever get them back?

A shrouded object

When Meyers finally got to Palomares – the Spanish village where a B52 bomber came down in 1966 – the authorities were still looking for the missing nuclear bomb. Each night his team slept in tents in the village, which was freezing and damp. "It was just like an English winter," he says. During the day they did very little – it was a waiting game.

"It's a standard military thing, hurry up and wait," says Meyers. "We had to rush over and then we did nothing for two weeks. And then after that, the undersea exploration became very serious."

The submersible Alvin was almost dragged into the depths when it dropped the Palomares bomb (Credit: Getty Images)

The search team enlisted the help of two ingenious inventions. One was an obscure theorem from the 18th Century invented by a Presbyterian minister-turned-amateur mathematician, which helps people to use information about past occurrences to calculate the probability of them happening again. They used this technique of "Bayesian inference" to decide where to look for the bomb, to help them search in the most efficient way possible and maximise their chances of finding it.

The second was "Alvin", a cutting-edge deep-ocean submarine able to dive to unprecedented depths. Like a rotund white shark, each day, it descended into the deep blue Mediterranean water with a human crew in its belly, and began a visual hunt.

Three missing US bombs
 

What? One Mark 15 thermonuclear bomb. Where? Tybee Island, Georgia. When? February 5 1958. How? It was jettisoned to reduce the plane's weight for a safer landing.

What? One B43 thermonuclear bomb. Where? The Philippine Sea. When? December 5 1965. How? A bomber plane, pilot and nuclear weapon slipped off the side of a carrier boat, never to be seen again.

What? One B28FI thermonuclear bomb, second stage. Where? Thule Air Base, Greenland. When? 22 May 1968. How? A cabin fire forced the crew to eject, leaving the plane to crash with its nuclear payload onboard.

On 1 March 1966, the little sub finally spotted something: a track made by the bomb when it first hit the sea bed. Later images revealed an eerie scene – the rounded tip of the missing nuclear weapon, covered by a ghostly shroud – its white parachute, which had partially deployed when it dropped, tangling itself up with its precious cargo. This deadly tube of metal had somehow ended up resembling a person dressed up for Halloween in a bedsheet.

But the struggle was not over. Now it was Meyers' job to work out how to get this bomb off the ocean floor – where it sat 2,850ft (869m) deep. They improvised a kind of fishing line out of a few thousand feet of heavy duty nylon rope and a metal hook – the idea was to latch onto the device, and pull it up until it was close enough to the surface that a diver could go down and secure it more thoroughly. "That was the plan. It didn't work," says Meyers.

"It was all done very deliberately and cautiously and slowly," says Meyers. "So we just kind of waited around… we were anxious, wanting to see what do we do next when it comes up." They managed to hook onto the nuclear bomb, and started to hoist it out of the water. They had lifted it up off the bottom when disaster struck. The parachute, resuscitated from its sleep on the ocean floor, suddenly began doing what they do best – slowing down its cargo's speed, and making it harder to move.

The bomb lost off the side of the USS Ticonderoga is thought to lie 50 miles (80km) off the coast of Okinawa, Japan (Credit: Alamy)

"Do you realise that parachutes work just as well in water, as they do on land?" says Meyers. Eventually, the parachute was pulling so hard on the line and hook that it simply snapped – sending the nuclear bomb slowly gliding back down towards the bottom. This time, it ended up even deeper than before. (Little Alvin – with its human crew – only just managed to avoid becoming entangled and ending up on the bottom with it.)

Meyers was devastated. "It was extremely disappointing," he says. With the bomb now less accessible than ever, his improvised line wouldn't be long enough to catch it, so the task was handed over to another team, on another boat.

A month later they used a different kind of robotic submarine – a cable-controlled underwater vehicle – to grab the bomb by its parachute directly, and haul it up. It had shifted in its casing, so it couldn't be disarmed the usual way, via a special port in the side – alarmingly, the officers instead had to cut into the nuclear weapon. "[It would have been] kind of nerve wracking to drill a hole in a hydrogen bomb," says Meyers. "But they did it. They were prepared to do that."

A swampy mystery

Unfortunately, the three lost bombs still out there today did not meet with such successful recovery efforts. However, the risk of them causing a nuclear explosion is thought to be low.

To get to grips with why, it helps to look at how nuclear bombs work.

In September 1905, Albert Einstein placed his fountain pen on the pages of his scientific paper, and scribbled down an idea that would become the world's most famous equation. E = mc2, or energy equals an object's mass multiplied by the speed of light squared. It means that each atom that makes up the world can be exchanged into energy, and vice versa. If you can work out how to do this, the release of energy is so explosive, it's what powers the Sun.

Thirty-four years later, Einstein wrote to the US President, Franklin Roosevelt, to warn him that the Nazis were working on turning his theory into a weapon – and the rest is history. The Manhattan Project was rapidly formed, and in 1945 the US dropped its first nuclear weapon.

The underwater nuclear explosion at the Bikini Atoll in the Marshall Islands resulted in a low, flat mushroom cloud of water and radioactive debris (Credit: Getty Images)

The bombs used on the Japanese cities of Hiroshima and – a few days later – Nagasaki, were the original, atomic kind. These involved smashing the atoms of radioactive elements against each other, to cause them to split up and create different elements. This "fission" reaction releases so much energy, it causes other atoms to split in turn, until you end up with a massive, runaway reaction. The first time they were ever tested, scientists weren’t sure the reaction would ever stop – they considered the very real possibility that the world might end. (Read more about the moments that could have destroyed humanity.)

To achieve nuclear fission, atomic bombs usually involved a gun-like contraption that fired a hollow "bullet" of radioactive atoms such as uranium-235 into yet more uranium-235, or used conventional explosives to compress atoms of plutonium-239, until they started to split up. At Hiroshima and Nagasaki, these early weapons levelled the land for miles and killed hundreds of thousands of people, some of whom were vaporised in the blast zone and others who died of radiation burns or sickness in the days, months and years afterwards.

The next generation – the kind used in the 1950s and 60s, when the majority of the world's lost nuclear weapons were misplaced – were thousands of times more powerful. These were thermonuclear, or hydrogen bombs, and they involved a second nuclear reaction.

First there was the usual fission step as with atomic bombs, which would release staggering amounts of energy. This would then ignite a second core, this time containing isotopes of hydrogen – deuterium (heavy hydrogen) and tritium (radioactive hydrogen) – which smash together and release even more energy when they fuse to form helium and one free neutron.

This system left room for a number of safety devices.

Take the lost Tybee island bomb, which is still lying in silt somewhere in Wassaw Sound. On February 5, 1958, this 7,600-pound (3,400-kg) Mark 15 thermonuclear weapon was loaded onto a B-47 bomber, which was about to join another B-47 on a long training mission. The idea was to simulate an attack on the Soviet Union, substituting the US town of Radford, Virginia, for Moscow. The pilots set off from Florida and criss-crossed their way to their target, as a way of testing their ability to fly with the heavy weapons onboard for hours at a time.

If it's intact, with the nuclear capsule inserted, the bomb lurking near Tybee island could have an explosive yield of up to 1.7 megatons of TNT (Credit: Getty Images)

It all went well, but on the way back to the base, the planes encountered a separate training mission in South Carolina. This group's plan was to intercept one of the B-47s – but there was a mix-up and they didn't spot the second one, which was carrying the nuclear weapon. In the ensuing crash, the B-47 carrying the nuclear bomb was damaged.

The pilot decided to ditch the nuclear bomb into the water, then make an emergency landing. The bomb dropped 30,000ft (9,144m) into the water off Tybee Island – and even this impact didn't detonate it. In fact, amazingly, none of the 32 broken arrow accidents have ever led to a detonation of nuclear components – though two have contaminated a wide area with radioactive material.

One possible factor in this lucky escape is a system of keeping the nuclear material needed for the fission reaction separate from the weapon itself. The capsule or "tip" – which in this case, consisted of plutonium – could then be added to the weapon at the last minute, when it was needed. This meant that, even if the weapon's conventional explosives went off when it was onboard, the radioactive material wouldn't get hot enough to actually do any atom-splitting.

Lewis also points out that, despite the Tybee bomb's long journey from the sky to the ocean, the latter will have cushioned the blow – this is the same reason space capsules usually have "splashdown" landings rather than descending onto land.

Later bombs also included features such as "one point safety" – a way of making sure nuclear devices didn't go off without being activated. In these weapons, the conventional explosives in a bomb might go off, but they wouldn't detonate the radioactive material because this is squeezed out before it can be compressed. "If the explosive goes off, you want it to go off in an uneven way, if that's not your goal – you want that plutonium to sort of squirt out," says Lewis.

As it happens, having so many safety features is highly necessary – mostly because they don't always work. In one case in 1961, a B-52 broke up while flying over Goldsboro, North Carolina, dropping two nuclear weapons to the ground. One was relatively undamaged after its parachute deployed successfully, but a later examination revealed that three out of four safeguards had failed.

In the end, the Palomares bomb was retrieved directly by a robotic submarine (Credit: Getty Images)

In a declassified document from 1963, the then-US Secretary of Defence summed up the incident as a case where "by the slightest margin of chance, literally the failure of two wires to cross, a nuclear explosion was averted".

The other nuclear bomb fell free to the ground, where it broke apart and ended up embedded in a field. Most parts were recovered, but one part containing uranium remains stuck under more than 50ft (15m) of mud. The US Air Force purchased the land around it to deter people from digging.

Some incidents are so baffling, they almost sound made up. Perhaps one of the most extraordinary occurred when a training exercise on the USS Ticonderoga went badly wrong in 1965. An A4E Skyhawk was being rolled to a plane elevator, while loaded with a B-43 nuclear bomb. It was a disaster in slow-motion – the crew on deck quickly realised that the plane was about to fall off, and waved for the pilot to apply the brakes. Tragically, he didn't see them, and the young lieutenant, plane and weapon vanished into the Philippine Sea. They're still there to this day, under 16,000 ft (4,900 m) of water near a Japanese island.

A confused picture

Despite nearly 10 weeks of searching, the Tybee island bomb was declared irretrievably lost on the 16th of April 1958. According to a receipt written by the pilot who dropped it, the weapon did not contain the capsule – it wasn't added before the training exercise. However, some people are concerned that this may not be correct. In 1966, the then-assistant to the Secretary of Defence wrote a letter in which he described the bomb as "complete" – i.e. containing its plutonium core. If this were true, the Mark 15 might still be capable of causing a full thermonuclear explosion.

Today the bomb is thought to be nestled under 5-15ft (1.5-4.6m) of silt on the seabed. In a final report on the weapon published in 2001, the Air Force Nuclear Weapons And Counterproliferation Agency concluded that if the conventional explosives inside are still intact, it could pose a "serious explosion hazard" to personnel and the environment – and is therefore best not disturbed, even by a recovery attempt.

But can a nuclear weapon explode underwater?

The ships sunk during the Baker Test are now havens for marine life (Credit: Getty Images)

As it happens, it can. On 25 July 1946, the US detonated an atom bomb at the Bikini Atoll – a chain of postcard-perfect tropical islands surrounded by turquoise coral reefs, and beyond, the deep blue of the Pacific Ocean. They suspended the device 90ft (27m) below an assortment of ships filled with pigs and rats, and set it off. Several ships sank instantly, and the vast majority of the animals died – either from the initial blast or later of radiation poisoning. One striking image from that day shows the giant white mushroom cloud rising up like an alien weather formation, in front of a palm-fringed beach.

As a result of this and other tests, the island chain became so radioactive that plankton glowed on photographic plates. It's still contaminated to this day – the people who once lived there have never been able to return, though like Chernobyl it has become an oasis for wildlife.

A permanent loss

Lewis thinks it's unlikely that we will ever find the three missing nuclear bombs. This is partly down to the same reasons they weren't found in the first place.

One is that they're usually located via a visual search – and this is extremely difficult.

When planes crash into the ocean, the black box is often found days or weeks later by officials looking to piece together what happened. This might give the impression that it’s easy to find such objects in these vast swathes of water with modern technology. But they have a secret that helps this process along – an "underwater location beacon", which guides search teams towards them with a repeating electronic pulse.

The lost nuclear weapons came with no such equipment. Instead, teams must narrow down a search area, then scour the ocean bit by bit – a tedious and inefficient process, which requires human divers or submarines.

An alternative would be to look for spikes in radiation, as the retired military officer Derek Duke did in his search for the Tybee bomb. But this is also extremely tricky – partly because nuclear bombs are not actually particularly radioactive.

"They're designed not to be a radioactive threat to the people handling them," says Lewis. "So they do have a radioactive signature, but it's just not very significant – you have to be fairly close."

The nuclear submarine USS Scorpion, which sank with two Mark 45 torpedoes, has been underwater for 54 years (Credit: Getty Images)

In 1989, another Soviet nuclear submarine, the K-278 Komsomolets, sank in the Barents Sea off the coast of Norway. Like the K-8, it was also nuclear-powered, and it had been carrying two nuclear torpedoes at the time. For decades, its wreck has been lying under a mile (1.7km) of Arctic water.

But in 2019, scientists visited the vessel – and revealed that water samples taken from its ventilation pipe contained radiation levels up to 100,000 times higher than would normally be expected in sea water. However, this is unusual. It's thought that radioactive elements from its nuclear reactor – as opposed to its nuclear torpedoes – are leaking out through this vent, possibly due to a rupture from when it crashed. Just half a meter (1.6ft) further away from the pipe, the isotopes were so diluted, radiation levels were normal.

For Lewis, the fascination with lost nuclear weapons isn't the potential risks they pose now – it's what they represent: the fragility of our seemingly sophisticated systems for handling dangerous inventions safely.

"I think we have this fantasy that the people who handle nuclear weapons are somehow different than all the other people we know, make fewer mistakes, or that they're somehow smarter. But the reality is that the organisations that we have to handle nuclear weapons are like every other human organisation. They make mistakes. They're imperfect," says Lewis.

Even at Palomares, where all the nuclear bombs that were dropped were eventually recovered, the land is still contaminated with radiation from two that detonated with conventional explosives. Some of the US military personnel who helped with the initial clean-up efforts – involving shovelling the surface of the soil into barrels – have since developed mysterious cancers which they believe are linked. In 2020, a number of survivors filed a class action suit against the Secretary of Veterans Affairs – though many of the claimants are currently in their late 70s and 80s.

Meanwhile, the local community has been campaigning for a more thorough clean-up for decades. Palomares has been dubbed "the most radioactive town in Europe", and local environmentalists are currently protesting against a British company's plans to build a holiday resort in the area.

The lost Palomares bomb had shifted in its casing, so deactivating it was risky (Credit: Alamy)

Lewis is confident that losses of the kind that occurred during the Cold War are unlikely to happen again, mostly because operation Chrome Dome was ended in 1968, and planes carrying nuclear bombs no longer fly around on regular training exercises. "Airborne alerts ended for reasons that must be obvious to us," he says. "In the end, the decision was made that it was too dangerous."

The exception to this progress is, of course, nuclear submarines – and even today, there are near-misses. The US currently has 14 ballistic missile submarines (SSBNs) in operation, while France and the UK have four each.

To work as nuclear deterrents these submarines must remain undetected during operations at sea, and this means they can't send any signals to the surface to find out where they are. Instead, they must navigate mostly by inertia – essentially, the crew rely on machines equipped with gyroscopes to calculate where the submarine is at any given time based on where it was last, what direction it was headed and how fast it was travelling. This potentially imprecise system has resulted in a number of incidents, including as recently as 2018 when a British SSBN almost bumped into a ferry.

The era of lost nuclear weapons might not be over just yet.

* Zaria Gorvett is a senior journalist for BBC Future and tweets @ZariaGorvett

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Walking after a meal, conventional wisdom says, helps clear your mind and aids in digestion. Scientists have also found that going for a 15-minute walk after a meal can reduce blood sugar levels, which can help ward off complications such as Type 2 diabetes. But, as it turns out, even just a few minutes of walking can activate these benefits.

In a meta-analysis, recently published in the journal Sports Medicine, researchers looked at the results of seven studies that compared the effects of sitting versus standing or walking on measures of heart health, including insulin and blood sugar levels. They found that light walking after a meal, in increments of as little as two to five minutes, had a significant impact in moderating blood sugar levels.

“Each small thing you do will have benefits, even if it is a small step,” said Dr. Kershaw Patel, a preventive cardiologist at Houston Methodist Hospital who was not involved in the study.

Very light walking reduces blood sugar levels.

In five of the studies that the paper evaluated, none of the participants had pre-diabetes or Type 2 diabetes. The remaining two studies looked at people with and without such illnesses. Participants were asked to either stand or walk for two to five minutes every 20 to 30 minutes over the course of a full day.

All seven studies showed that just a few minutes of light-intensity walking after a meal were enough to significantly improve blood sugar levels compared to, say, sitting at a desk or plopping down on the couch. When participants went for a short walk, their blood sugar levels rose and fell more gradually.

For people with diabetes, avoiding sharp fluctuations in blood sugar levels is a critical component in managing their illness. It’s also thought that sharp spikes and crashes in blood sugar levels can contribute to developing Type 2 diabetes.

Standing also helped lower blood sugar levels, although not to the degree that light walking did. “Standing did have a small benefit,” Aidan Buffey, a graduate student at the University of Limerick in Ireland and an author of the paper, said. Compared to sitting or standing, “light-intensity walking was a superior intervention,” he said.

That’s because light walking requires more active engagement of muscles than standing and uses the fuel from food at a time when there is a lot of it circulating in the bloodstream. “Your muscles will soak up some of that excess glucose,” said Jessie Inchauspé, author of the book “Glucose Revolution: The Life-Changing Power of Balancing Your Blood Sugar.”

“You still had the same meal, but the impact on your body will be lessened,” she added.

Walking within 60 to 90 minutes after eating delivers the best results.

Although light walking at any time is good for your health, a short walk within 60 to 90 minutes of eating a meal can be especially useful in minimizing blood sugar spikes, as that is when blood sugar levels tend to peak.

Ms. Inchauspé also recommended getting up to do housework or finding other ways to move your body. This short amount of activity will also enhance other dietary changes that people may be making to help control their blood sugar levels.

“Moving even a little bit is worthwhile and can lead to measurable changes, as these studies showed, in your health markers,” Dr. Euan Ashley, a cardiologist at Stanford University who was not associated with the study, said.

Mini-walks are more practical during the workday.

Mr. Buffey, whose research focuses on physical activity interventions in workplace environments, noted that a mini-walk of two to three minutes is more practical during the workday. People “are not going to get up and run on a treadmill or run around the office,” he said, but they could get some coffee or even go for a stroll down the hallway.

For people working from home, he suggested a short walk around the block between Zoom meetings or after lunch. The more we normalize mini-walks during the workday, Mr. Buffey said, the more feasible they will be. “If you are in a rigid environment, that’s when the difficulties may come.”
If you cannot take those few minutes to take a walk, Dr. Ashley said, “standing will get you some of the way there.”

The benefits of physical activity are never all or nothing, Dr. Patel said, but instead exist on a continuum. “It’s a gradual effect of more activity, better health,” he said. “Each incremental step, each incremental stand or brisk walk appears to have a benefit.”

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This was the year that Larry Brilliant got Covid. In May, he traveled to Davos, Switzerland, to attend the elite global gabfest that had been postponed from its usual January staging. The 78-year-old epidemiologist had gotten through the first years of the pandemic virus-free. But, he now believes, traveling through a crowded Zurich airport exposed him to a recent variant of the disease that has infected over half a billion people worldwide and killed a million people in the United States alone.

It was further proof that this virus spares no one, not even a disease fighter who helped eradicate smallpox and had been warning the world about a potential pandemic for years. He had even advised Davos organizers on their Covid protocols. But Brilliant, of all people, knows that with ever-more virulent variants of Covid-19, even the most meticulous virus-avoider might get sick. And thus the multiple-boosted founder and CEO of Pandefense Advisory went through 17 days of testing positive and two rounds of the Paxlovid treatment.

Now recovered, Brilliant is once again speaking about what we might expect with our ongoing global crisis. I began interviewing Brilliant about the coronavirus in March 2020, and our first session was one of the most-read stories Condé Nast (which owns WIRED, the New Yorker, Vogue, and other publications) ran that year. This is the fifth installment of our ongoing conversation. We touched on how variants evolve, the humbling of the CDC, and why he thinks that rapid antigen tests are a menace. Brilliant makes predictions reluctantly—he distinguishes glimpses into his “crystal ball” from actual science, which proceeds on empirical trials and experiments. But if he’s right, we’ll still be talking Covid for a very long time.

This interview has been condensed and edited for clarity.

Steven Levy: How are you feeling?

Larry Brilliant: I think I'm 110 percent recovered, after 17 days of positivity. Do you know about the Rockefeller Foundation retreat in Bellagio, Italy, where people go to plan conferences? I think that all the variants of Covid got together there with a list of all the people who spoke bad about them and decided: “Enough of this shit. Let’s go after those people.”

It certainly seems that tons of people who had been boosted and masked have gotten Covid recently.

Fauci and Biden have gotten it, too.

Why are careful people getting it now?

Even the most careful person will get the most transmissible virus in history. Also, mRNA vaccines are based on the formulations from the original strain.

Every evolution produces a more evasive variant—it won’t win the race unless it’s the fastest pony. So instead of only finding new customers in the unvaccinated population, this BA.5 variant increases its market by being able to infect people who’ve had three doses of the vaccine, or people who have had Covid a month ago. In addition, this puppy might be infectious earlier and later than when you first have symptoms. The CDC has guidelines of ending isolation—or going back to work—after five days. With BA.5, that’s ridiculous.

You were one of those people with four doses.

That’s right, and I was also able to get a prophylactic monoclonal antibody. That’s probably why I think I got a relatively mild disease. But it persisted for 17 days, and I had to have two courses of Paxlovid.

By the way, I don't think we should call this a rebound. A better way to say it is that we don’t have the dosing schedule correct. It’s possible that Paxlovid probably requires a course of seven or 10 days.

So if I get Covid, I can ask my doctor to give me seven or 10 day’s worth of Paxlovid instead of five? [Note: The official guidance is that Paxlovid should be administered for five days, though some physicians have spoken out about the need for clearer guidance.]

Not yet. When people say they’re following the science, what they should be saying is they’re following the published science, which is always based on a study done on something that happened before. You’re always behind.

Sometimes it seems like politics, not science, is determining policy. Biden said that he’d remain in isolation longer than the recommended five days if he kept testing positive. Who’s right?

Biden is modeling very good behavior. That’s really refreshing since the last president modeled the worst.

Sure, but it’s strange that the president has to disregard his own agency to do the right thing. [Note: After this interview, Biden ended up leaving isolation after five days when he tested negative, then reentering isolation after experiencing a rebound case.]

In part, this is because when Trump was president, he attacked the CDC. There was so much political interference that there was an exodus of the CDC’s top people and a loss of its institutional memory. But there’s also been a failure of the CDC to communicate well and update their recommendations.

Also, the CDC is slow. In some ways, you’d like that to be the case—you like your doctor to be deliberative. But not too slow. Even though their advice may have been perfect a year ago, it’s not perfect now. So now the administration is talking about shifting pandemic preparedness to what used to be a small agency—ASPR [Administration for Strategic Preparedness & Response].

Why does that make sense?

The CDC’s mandate is much more than pandemics. It works on health promotion, prevention. It’s responsible for looking at heart disease and diabetes, international relations with other countries doing all health programs—all the public health units of all the different counties. But of course right now we’re necessarily focused on the pandemic and infectious diseases, and we’re really dealing with Covid and monkeypox.

I was going to mention monkeypox. What’s going on there?

Let’s go back to 1967. The WHO had the idea that the whole world should work together to eradicate smallpox. But what about other poxes? The smallpox vaccine protects against monkeypox, too. If you eradicate smallpox, and subsequently you stopped vaccinating, what happens to the other poxes that were held in check by continuing to vaccinate? We could have kept vaccinating. But we didn’t, and now no one under the age of 40 has a vaccination scar.

It was certainly justifiable to use that vaccine against the disease that killed one out of three. But monkeypox is relatively mild, killing very few people. It’s understandable that people would say, ‘Well, what’s the fuss?’ Well, there’s two reasons. First, we got over 20,000 cases. The people who are affected the most by this outbreak are men who have sex with men—but it’s also people who have sex in general, or anybody who rubs bodies with each other for any reason at all, or, of course, anybody who's immunocompromised is at greater risk of getting it, giving it, and maybe having the bad side effects of it. That’s one reason.

But there’s another reason. If we had acted sooner—when there were 100 cases, 1,000 cases—we could have eliminated it as a significant problem. We could even do this now by identifying every case and vaccinating all the contacts. We could stop this outbreak. The United States is not doing it. Because it would require identifying every case and the complicated issues around who’s getting it. We don’t want to stigmatize the gay community; we did that with HIV/AIDS, with horrific results.

Monkeypox is not a disease of gay men. It’s also not a disease of monkeys. We are not the natural host of this virus. This is primarily a disease of rodents, but it was first identified in monkeys, and that’s where it got the name.

If we don’t act right now to contain the spread of monkeypox—if it’s subjected to the same laissez-faire epidemiology, “let it rip” ideology we are using with Covid—how far are you going to let it go? A hundred thousand? Two hundred thousand? A million? Speed is critical. If we quickly work to contain monkeypox, we don’t have to worry about 20 years of having urban rodent pox that spreads to humans. That’s why I’m unhappy about what we’re not doing now. I’m unhappy about letting the cat out of the bag when we still have a bag. [Note: After our conversation, the World Health Organization declared monkeypox an emergency.]

Back to Covid. You just used the term “laissez-faire epidemiology.” Do you feel that our approach now, based on individual choices, is misguided?

Yes. Remember Trump’s Covid advisor Scott Atlas, who promoted the idea that we should do away with lockdowns? When he said that, we didn’t have vaccines. Millions more people would have died, certainly. In the United States, hundreds of thousands more people would have died. 

The death rates are down now, but it’s still very bad, for a hundred reasons. When you say, “Everybody’s on their own,” we’re forgetting that we have a duty of care. At least 20 percent of our population are either over the age of 65 or immunocompromised. They are at high risk of dying if they don’t get vaccinated and they’re not careful, they’re not wearing masks. … So if you just say, “OK, well, everybody’s gonna get it,” you endanger the people who are most vulnerable. That’s where the death rate is. That’s where the hospitalization rate is.

Second, the longer this virus continues, the more variants we’re going to have. We don’t know exactly what forms a variant, but for sure one factor is immunocompromised people who have the virus puttering around longer in their system—not for 17 days like me, but for months. The body can’t clear the virus completely. You’ve created ideal circumstances for reassortment, recombination.

Another issue is that we don’t have a good handle on numbers because we never got testing, right?

What if I said to you that antigens, those rapid at-home tests we all use now, were bad for our public health? It’s stupid that antigen tests were approved without the requirement to report positive cases.

How would you enforce that?

Through technology. It’s not that hard to build the technology to do automatic reporting. There’s now a class of at-home molecular tests that can already do that. They’re almost as good as PCR tests.

Aren’t those more expensive?

The only thing that makes them expensive is the lack of scale. Right now we can get antigen tests for as little as $5. If you’re doing a billion molecular tests, you can bring the cost down as well.

When those molecular tests go to the FDA for approval, they say that all positives should be reported. That makes them much better than antigen tests, which are great at the back end of the disease when you’re trying to determine if you’re still infectious. But they're terrible for the first two days, when the rate of false negatives is so high. Between the false negatives and the fact that they don’t report into public health, antigen tests are dangerous to the public health.

Would you ban them?

I would regulate them.

On to vaccines. The one we have works against the original version of Covid, which no one gets any more. So why didn’t we have a “warp speed” effort for a specific vaccine directed toward the newer variants?

We sort of did. Both Pfizer and Moderna are about to release vaccines specific for Omicron. You seem to be asking why we don’t have a warp speed for BA.5? We call that process whack-a-mole.

So the new vaccine will do a better job protecting us from getting it?

I hope so. You will have more immunity to Omicron. But BA.5 itself doesn’t necessarily honor a previous infection with Omicron. The vaccine will, though, better prevent you from being hospitalized or dying. But we should start talking about BA.2.75. It seems to be the next car in the train. And it’s coming on really quickly.

We’re already on to the next one?

It’s already been detected in several states. We’re just getting more variants.

There’s a controversy over whether people who are due for a booster should take it now or hold off until this new vaccine shows up in the fall.

I’m very cautious. I don’t want anybody to get it in the next two or three months before you can get the new vaccine. [Note: White House officials have said that anyone immunocompromised or over the age of 50 should get a second booster if they haven’t done so already.]

If you went back to our first conversation, in March 2020, it seemed unlikely we would be talking two and half years later and still facing huge numbers.

Why are you surprised? I wrote an article called “The Forever Virus.”

Will we ever get back to Before Times? When we don’t have to be careful and we can eat indoors and go to a Broadway show without a mask and feel safe?

That’s two separate questions. Will we ever get to a point where there’ll be no Covid? No. There will always be Covid.

Will we ever get to a point where we go to a Broadway show without a mask? Yes. We’ve probably had coronaviruses infect the world in a pandemic-like way before. And then the virus went into the retirement home for coronaviruses, and we called it a “cold virus.” And they kind of rotate. That’s why you can get two or three colds a year. They feel the same to you, but they’re different viruses. And that’s because the immunity that they give you is only good for about a year or two.

This Covid will eventually look like that. “Eventually” is the key word here. Over time, as the human population becomes more and more immune through a combination of vaccines and prior infection, repeated infection, then the coronavirus will sort of settle for being transmissible and it won't be dangerous. It won't take you to the hospital.

It doesn’t seem that way now. These variants are still getting lots of people super sick.

History does not move in a straight line.

Has getting Covid changed the way you thought about this?

Of course. I had begun to buy into the idea that for most people Covid was really like a cold or like a flu, and wasn't that big a deal. But it is a big deal. It's a terrible effing disease. For a quarter of the population or even more, it's a very serious disease. And for the fifth of the population that's not vaccinated at all, BA.5 is an extraordinarily dangerous disease.

I thought I was compassionate. But having Covid has ratcheted me up to a much higher level of compassion for people who are having it or who are at high risk, because I know how bad it could be. And I don't even have long Covid.

Larry Brilliant Says Covid Rapid Tests Are Bad for Public Health

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An Atlas V rocket launches a Space Based Infrared System satellite on Thursday morning from Cape Canaveral Space Force Base.

Trevor Mahlmann

 

Welcome to Edition 5.05 of the Rocket Report! Don't look now, but we could be fewer than four weeks away from the launch of NASA's Space Launch System rocket. I have covered this booster for a dozen years and I'm so ready for this to finally happen. I've got plenty of coverage planned in the weeks ahead.

 

As always, we welcome reader submissions, and if you don't want to miss an issue, please subscribe using the box below (the form will not appear on AMP-enabled versions of the site). Each report will include information on small-, medium-, and heavy-lift rockets as well as a quick look ahead at the next three launches on the calendar.

Georgia spaceport sues to force land sale. First Camden County citizens voted overwhelmingly against a proposed spaceport in southeastern Georgia. Then, the owner of 4,000 acres sought by the spaceport proponents said it would end an agreement to sell the land to backers of the Spaceport Camden project. Even so, Camden County commissioners refuse to give up the dream of building a spaceport that local residents don't want, and for which the land owner doesn't want to sell. So they've taken the land owner, Union Carbide Corporation, to court, News4Jax reports.

 

Ignoring the voters ... Last month, in a statement, Union Carbide said, "As a result (of the election), there is no longer an Option Agreement in existence between the County and UCC, and UCC does not intend to convey the property to the County pursuant to the prior Option Agreement." In filing the lawsuit, Steve Howard, Camden County's government administrator, wrote, "Union Carbide most certainly has a contract with Camden. The County has indicated that it is ready, willing, and able to close. We expect Union Carbide to honor its contractual commitments." At some point you have to wonder why local officials are so hellbent on building this spaceport. (submitted by zapman987 and Ken the Bin)

 

Solid rocket debut a success. Chinese launch services provider CAS Space successfully placed six small satellites in orbit early Wednesday with the first launch of the Lijian-1 solid rocket, Space News reports. Lijian-1 is now the largest operational Chinese solid launcher, and CAS Space is also developing larger rockets. The 30-meter-tall Lijian-1 rocket can carry 1,500 kilograms of payload into a 500-kilometer Sun-synchronous orbit.

 

Derivative designs ... CAS Space is a quasi-commercial spinoff from the Chinese Academy of Sciences. The parent, CAS, develops a range of spacecraft, including Beidou satellites, and has previously launched sounding rockets. Although Wednesday's orbital launch marks a big step forward, solid rockets appear to be only the start of CAS Space's ambitions. The company is also working on reusable liquid engines with the goal of developing recoverable launchers. A new website unveiled by the company recently shows launch vehicle renders similar to Falcon 9, Falcon Heavy, and New Shepard launchers. (submitted by EllPeaTea and Ken the Bin)

US companies complete August 4 launch-a-palooza. Thursday was quite a day for US launch providers. Starting at 05:00 UTC, Rocket Lab's Electron vehicle launched the NROL-199 mission into low Earth orbit for the US National Reconnaissance Office. Then, at 10:29 UTC on Thursday, United Launch Alliance's Atlas V rocket sent a Space Based Infrared System satellite into orbit for the US Space Force. Finally, at 1337 UTC, Blue Origin's New Shepard rocket launched the NS-22 suborbital space tourism mission.

 

Next up, SpaceX ... Thursday evening the focus turned toward SpaceX and its Falcon 9 rocket, which was due to launch the Korea Aerospace Research Institute's Korean Pathfinder Lunar Orbiter spacecraft to the Moon. The rocket launched at 23:09 UTC from Cape Canaveral, Florida, and was successful. I cannot recall a time when four different US rockets launched during the same calendar day, but this probably won't be the last time, given all the development of new US boosters, large and small. We truly are entering an era of launch abundance. (submitted by EllPeaTea and Ken the Bin)

 

Russia launches satellite to spysat. A Russian Soyuz rocket launched from the Plesetsk Cosmodrome on Monday around midnight local time. The military mission's payload was classified but has been designated Kosmos 2558 for tracking purposes. The Russian satellite has since been placed in a nearly circular, 435 km×452 km orbit, with an inclination of 97.25 degrees. This is notable, Ars reports, because it will allow the Kosmos 2558 satellite to come very close to a recently launched US spy satellite, which was designated NROL-87.

 

Close encounter of the satellite kind ... This US national security payload was designed and built for the National Reconnaissance Agency and launched on February 2 into orbit by a Falcon 9 rocket from Vandenberg Space Force Base in California. The Russian satellite launched into the same orbital plane as NROL-87, and this set up a close encounter between the two satellites on Thursday, August 4, when they will pass within just 75 km of one another.

 

Falcon 9 fairing recovery going well. SpaceX continues to tinker with how it recovers Falcon 9 payload fairing halves, NASASpaceflight.com reports. Most notably, the company appears to be testing a new system of a crane and rigs, with inflatables, to pluck fairing halves from the ocean after they fall to Earth. The new rig appears to have been designed with inflatables to avoid damaging the fairing if the two were ever to make contact. This video of a recent test is quite interesting.

 

Seven time's the charm? ... More than a year ago SpaceX abandoned its plan of attempting to "catch" the falling fairing halves with boats equipped with large nets, determining that it was less work to refurbish fairing halves that briefly touch the sea compared to the effort of trying to catch them. It now appears that the company has flown some of these fairing halves as many as seven times, and due to the success of its recovery effort has a factory full of them ready to fly again. (submitted by Ken the Bin)

 

OneWeb needs five more launches to complete network. OneWeb and Eutelsat announced plans in late July to merge, bringing together OneWeb's network of Internet satellites in low Earth orbit with Eutelsat's fleet of larger video, data relay, and broadband platforms in geostationary orbit, Spaceflight Now reports. OneWeb's chairman also said the company is on track to resume deploying its remaining Internet satellites as soon as September, with three SpaceX flights and two Indian launches on tap to replace Russian Soyuz rockets no longer available after Russia's invasion of Ukraine.

 

Awarding contracts for second-gen constellation ... While OneWeb still has about 220 satellites to launch before completing its first-generation network, the company is already planning an even larger constellation called Gen 2. OneWeb announced an agreement with Relativity Space last month for multiple Gen 2 satellite launches beginning as soon as 2025 on the launch company's next-generation reusable Terran R rocket.

 

Book your Russian launch online. Roskosmos' commercial arm to sell Russian launch services abroad, Glavkosmos, has opened a booking page for its launch vehicles, Anatoly Zak reports. The webpage invites users to order a "target launch" on one of four launch vehicles: Angara-1.2, Angara-A5, Soyuz-2.1, and a Proton-M. While the webpage includes basic information about each vehicle, the Russian website does not list prices.

 

Customers must be OK with genocidal war ... Zak probably said it best about the new booking website: "If you have a 4-24-ton satellite built without any Western components and you are OK with Russian genocidal war in Ukraine, you are welcome to book your ride here." I have to agree. Tangentially, if you're wondering what Glavkosmos CEO Dmitry Loskutov thinks of the Rocket Report, it's safe to say he does not have a flattering opinion of my efforts. Udachi with your sales, Dmitry!

SLS launch remains on track for late this month. It hardly seems real, but we very well could be within just a few weeks of the debut launch of the Space Launch System rocket. SLS managers and agency leaders said this week that the work to prepare the SLS and the Orion spacecraft for the Artemis 1 mission inside the Vehicle Assembly Building at the Kennedy Space Center was "on plan" to support a rollout to the pad August 18 and a launch 11 days later, Space News reports. "We are in the final stretch," Charlie Blackwell-Thompson, Artemis 1 launch director at KSC, said at a briefing to preview the mission.

 

Need to complete flight termination system work ... A rollout on August 18 would allow a launch on August 29. Since NASA announced the targeted launch date last month, crews have been working on SLS and Orion, ranging from completing repairs to the rocket to installing payloads inside the Orion capsule. Technicians also powered on Orion for the final time before launch last weekend. One remaining item to complete is testing the rocket's flight termination system in the "intertank" portion of the core stage. That testing will begin next week, Blackwell-Thompson said. (submitted by Ken the Bin)

 

Long March 5B makes uncontrolled reentry. Wreckage from a Chinese Long March 5B rocket first stage made a fiery reentry into Earth's atmosphere over Southeast Asia Saturday, six days after launching a space station module into orbit, Space News reports. The Long March 5B is a variant of China's largest rocket and consists of a core stage and four side boosters. The core stage also acts as the upper stage, inserting the payload into orbit, but because its engines cannot restart, the location of the core stage's return from low Earth orbit cannot be predetermined.

 

Where it stops nobody knows ... While much of the empty rocket stage is expected to have burned up on reentry, roughly 20 to 40 percent of a stage typically survives reentry, according to experts, such as engine components designed to withstand high temperatures. Much of this fell into the Sulu Sea, but there were reports of debris found in Borneo and Malaysia, although no one was hurt. Following the Long March 5 B's return, NASA Administrator Bill Nelson called on China's space program to share better trajectory information as part of established norms. (submitted by Ken the Bin)

 

NASA awards contracts for future SLS missions. NASA is preparing to award a contract to a Boeing-Northrop Grumman joint venture for Space Launch System missions that could run through the middle of the next decade, Space News reports. The agency's pre-solicitation notice would shift procurement of SLS launches to a services contract. Under the contract, NASA would procure launch services, rather than the vehicles themselves, for missions starting with Artemis 5 in the late 2020s. NASA envisions this approach as a means of saving money as well as opening the door to other uses of the heavy-lift rocket.

 

Keeping the trough filled ... The baseline contract would cover missions Artemis 5 through 9, with an option for missions Artemis 10 through 14 and another option for up to 10 non-Artemis launches. If the options are exercised, the contract will run through the Artemis 14 mission that NASA projects flying in 2036. NASA expects to award the contract to a new joint venture called Deep Space Transport LLC. That joint venture consists of Boeing, the prime contractor for the SLS core stage and the Exploration Upper Stage that will be used on SLS missions starting with Artemis 4, and Northrop Grumman, the prime contractor for the SLS solid rocket boosters. The contract would effectively be sole-sourced to Deep Space Transport.

Next three launches

August 6: Small Satellite Launch Vehicle | Satish Dhawan Space Center, India | 15:48 UTC

August 9: Falcon 9 | Starlink 4-26 | Kennedy Space Center, Fla. | 23:00 UTC

August 12: Falcon 9 | Starlink 3-3 | Vandenberg Space Force Base, Calif. | 21:30 UTC

 

Rocket Report: SpaceX launches Korea to the Moon, Georgia’s litigious spaceport

“Black widow” neutron star devoured its mate to become heaviest found yet

With more than half a billion coronavirus cases recorded worldwide since the start of the pandemic, there has been rising concern about the lasting symptoms seen in people with long Covid.

However almost none of the existing research has compared long Covid sufferers with people who have never been infected, making it possible that some of the health problems were not caused by the virus.

A new study published in The Lancet journal asked more than 76,400 adults in the Netherlands to fill out an online questionnaire on 23 common long Covid symptoms.

Between March 2020 and August 2021, each participant filled out the questionnaire 24 times.

During that period, more than 4,200 of them -- 5.5 percent -- reported catching Covid.

Of those with Covid, over 21 percent had at least one new or severely increased symptom three to five months after becoming infected.

However nearly nine percent of a control group which did not have Covid reported a similar increase.

This suggested that 12.7 percent of those who had Covid -- around one in eight -- suffered from long-term symptoms, the study said.

The research also recorded symptoms before and after Covid infection, allowing the researchers to further pinpoint exactly what was related to the virus.
It found that common long Covid symptoms include chest pain, breathing difficulties, muscle pain, loss of taste and smell, and general fatigue.

- 'Major advance' -

One of the study's authors, Aranka Ballering of the Dutch University of Groningen, said long Covid was "an urgent problem with a mounting human toll".

"By looking at symptoms in an uninfected control group and in individuals both before and after SARS-CoV-2 infection, we were able to account for symptoms which may have been a result of non-infectious disease health aspects of the pandemic, such as stress caused by restrictions and uncertainty," she said.

The authors of the study said its limitations included that it did not cover later variants, such as Delta or Omicron, and did not collect information about some symptoms such as brain fog, which have since been considered a common sign of long Covid.

Another study author, Judith Rosmalen, said "future research should include mental health symptoms" such as depression and anxiety, as well as aspects like brain fog, insomnia and a feeling of malaise after even minor exertion.

Christopher Brightling and Rachael Evans, experts from Britain's Leicester University who were not involved in the study, said it was "a major advance" on previous long Covid research because it had an uninfected control group.

"Encouragingly, emerging data from other studies" suggests there is a lower rate of long Covid in people who have been vaccinated or infected with the Omicron variant, they said in a linked Lancet comment.

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