Without question, inactivity is bad for us. Prolonged sitting is consistently linked to higher risks of cardiovascular disease and death. The obvious response to this frightful fate is to not sit— move. Even a few moments of exercise can have benefits, studies suggest. But in our modern times, sitting is hard to avoid, especially at the office. This has led to a range of strategies to get ourselves up, including the rise of standing desks. If you have to be tethered to a desk, at least you can do it while on your feet, the thinking goes.

However, studies on whether standing desks are beneficial have been sparse and sometimes inconclusive. Further, prolonged standing can have its own risks, and data on work-related sitting has also been mixed. While the final verdict on standing desks is still unclear, two studies out this year offer some of the most nuanced evidence yet about the potential benefits and risks of working on your feet.

Take a seat

For years, studies have pointed to standing desks improving markers for cardiovascular and metabolic health, such as lipid levels, insulin resistance, and arterial flow-mediated dilation (the ability of arteries to widen in response to increased blood flow). But it's unclear how significant those improvements are to averting bad health outcomes, such as heart attacks. One 2018 analysis suggested the benefits might be minor.

And there are fair reasons to be skeptical about standing desks. For one, standing—like sitting—is not moving. If a lack of movement and exercise is the root problem, standing still wouldn't be a solution.

Yet, while sitting and standing can arguably be combined into the single category of 'stationary,' some researchers have argued that not all sitting is the same. In a 2018 position paper published in the Journal of Occupational and Environmental Medicine, two health experts argued that the link between poor health and sitting could come down to the specific populations being examined and "the special contribution" of "sitting time at home, for example, the 'couch potato effect.'"

The two researchers—emeritus professors David Rempel, formerly at the University of California, San Francisco, and Niklas Krause, formerly of UC Los Angeles—pointed to several studies looking specifically at occupational sitting time and poor health outcomes, which have arrived at mixed results. For instance, a 2013 analysis did not find a link between sitting at work and cardiovascular disease. Though the study did suggest a link to mortality, the link was only among women. There was also a 2015 study on about 36,500 workers in Japan, who were followed for an average of 10 years. That study found that there was no link between mortality and sitting time among salaried workers, professionals, and people who worked at home businesses. However, there was a link between mortality and sitting among people who worked in farming, forestry, and fishing industries.

Still, despite some murkiness in the specifics, more recent studies continue to turn up a link between total prolonged sitting—wherever that sitting occurs—and poor health outcomes, particularly cardiovascular disease. This has kept up interest in standing desks in offices, where people don't always have the luxury of frequent movement breaks. And this, in turn, has kept researchers on their toes to try to answer whether there is any benefit to standing desks.

One study published last month in the International Journal of Epidemiology offers a clearer picture of how standing desks may relate to cardiovascular health risks. The authors, an international team of researchers led by Matthew Ahmadi at the University of Sydney in Australia, found that standing desks don't improve heart health—but they don't harm it, either, whereas sitting desks do.

Mitigating risks

For the study, the researchers tracked the health data of a little over 83,000 people in the UK over an average of about seven years. During the study, participants wore a wrist-based accelerometer device for at least four days. The devices were calibrated to determine when they were sitting, standing, walking, or running during the waking hours. With that data, the researchers linked their sitting, standing, and stationary (combined sitting and standing) times to health outcomes in their medical records.

The researchers focused on two categories of health outcomes: cardiovascular, covering coronary heart disease, heart failure, and stroke; and orthostatic circulatory disease events, including orthostatic hypotension (blood pressure drops upon standing or sitting), varicose veins, chronic venous insufficiency (veins in your legs don't move blood back up to your heart), and venous ulcers. The reasoning for this second category is that prolonged sitting and standing may pose risks for developing circulatory diseases.

The researchers found that when participants' total stationary time (sitting and standing) went over 12 hours per day, risk of orthostatic circulatory disease increased 22 percent per additional hour, while risk of cardiovascular disease went up 13 percent per hour.

For just sitting, risks increased every hour after 10 hours: for orthostatic circulatory disease, risk went up 26 percent every hour after 10 hours, and cardiovascular disease risk went up 15 percent. For standing, risk of orthostatic circulatory disease went up after just two hours, increasing 11 percent every 30 minutes after two hours of standing. But standing had no impact on cardiovascular disease at any time point.

"Contrary to sitting time, more time spent standing was not associated with a higher CVD [cardiovascular disease] risk. Overall, there was no association for higher or lower CVD risk throughout the range of standing duration," the authors report.

On the other hand, keeping sitting time under 10 hours and standing time under two hours was linked to a weak protective effect against orthostatic circulatory disease: A day of nine hours of sitting and 1.5 of standing (for a total of 11.5 hours of stationary time) lowered risk of orthostatic circulatory disease by a few percentage points, the study found.

In other words, as long as you can keep your total stationary time under 12 hours, you can use a little standing time help you keep your sitting time under 10 hours and avoid increasing both cardiovascular and orthostatic risks, according to the data.

Consistent finding

It's a very detailed formula to reduce the health risks of long days at the office, but is it set in stone? Probably not. For one thing, it's just one study that needs to be replicated in a different population. Also, the study didn't look at any specifics of occupational versus leisure standing and sitting times, let alone the use of standing desks specifically. The study also based estimates of people's sitting, standing, and total stationary time on as little as just four days of activity monitoring, which may or may not have been consistent over the nearly seven-year average follow-up period.

Still, the study's takeaway generally fits with a study published in January in JAMA Network Open. This study looked at the link between occupational sitting time, leisure physical activity, and death rates—both deaths from all causes and those specifically caused by cardiovascular disease. Researchers used a group of over 480,000 workers in Taiwan, who were followed for an average of nearly 13 years.

The workers who reported mostly sitting at work had a 16 percent increased risk of all-cause mortality and a 34 percent higher risk of dying from cardiovascular disease compared with workers who did not sit at work. The workers who reported alternating between sitting and standing, meanwhile, did not have an increased risk of all-cause or cardiovascular disease mortality. The findings held after adjusting for health factors and looking at subgroups, including by sex, age, smokers, never-smokers, and people with chronic conditions.

That said, being highly active in leisure time appeared to offset the mortality risks among those who mostly sit at work. At the highest leisure-time activity levels reported, participants who mostly sit at work had comparable risks of all-cause mortality as those who alternated sitting and standing or were didn't sit at work. Overall, the data suggested that keeping overall stationary time as low as possible and alternating sitting and standing to some extent at work can reduce risk.

The authors call for incorporating breaks in work settings and even specifically recommend allowing for standing and activity-permissive workstations.

The takeaway

While prolonged standing has its own risks, the use of standing desks at work can, to some extent, help lessen the risks of prolonged sitting. But, overall, it's important to keep total stationary time as low as possible and exercise whenever possible.

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By now, it has been firmly established that the Earth went through a series of global glaciations around 600 million to 700 million years ago, shortly before complex animal life exploded in the Cambrian. Climate models have confirmed that, once enough of a dark ocean is covered by reflective ice, it sets off a cooling feedback that turns the entire planet into an icehouse. And we've found glacial material that was deposited off the coasts in the tropics.

We have an extremely incomplete picture of what these snowball periods looked like, and Antarctic terrain provides different models for what an icehouse continent might look like. But now, researchers have found deposits that they argue were formed beneath a massive ice sheet that was being melted from below by volcanic activity. And, although the deposits are currently in Colorado's Front Range, at the time they resided much closer to the equator.

In the icehouse

Glacial deposits can be difficult to identify in deep time. Massive sheets of ice will scour the terrain down to bare rock, leaving behind loosely consolidated bits of rubble that can easily be swept away after the ice is gone. We can spot when that rubble shows up in ocean deposits to confirm there were glaciers along the coast, but rubble can be difficult to find on land.

That has made studying the snowball Earth periods a challenge. We have the offshore deposits to confirm coastal ice, and we have climate models that say the continents should be covered in massive ice sheets, but we have very little direct evidence. Antarctica gives off mixed messages, too. While there are clearly massive ice sheets, there are also dry valleys, where there's barely any precipitation and there's so little moisture in the air that any ice that makes its way into the valleys sublimates away into water vapor.

All of which raises questions about what the snowball Earth might have looked like in the continental interiors. A team of US-based geologists think they've found some glacial deposits in the form of what are called the Tavakaiv sandstones in Colorado. These sandstones are found along the Front Range of the Rockies, including areas just west of Colorado Springs. And, if the authors' interpretations are correct, they formed underneath a massive sheet of glacial ice.

There are lots of ways to form sandstone deposits, and they can be difficult to date because they're aggregates of the remains of much older rocks. But in this case, the Tavakaiv sandstone is interrupted by intrusions of dark colored rock that contains quartz and large amounts of hematite, a form of iron oxide.

These intrusions tell us a remarkable number of things. For one, some process must have exerted enough force to drive material into small faults in the sandstone. Hematite only gets deposited under fairly specific conditions, which tells us a bit more. And, most critically, hematite can trap uranium and the lead it decays into, providing a way of dating when the deposits formed.

Under the snowball

Depending on which site was being sampled, the hematite produced a range of dates, from as recent as 660 million years ago to as old as 700 million years. That means all of them were formed during what's termed the Sturtian glaciation, which ran from 715 million to 660 million years ago. At the time, the core of what is now North America was in the equatorial region. So, the Tavakaiv sandstones can provide a window into what at least one continent experienced during the most severe global glaciation of the Cryogenian Period.

Obviously, a sandstone could be formed from the fine powder that glaciers grind off rock as they flow. The authors argue that the intrusions that led to the hematite are the product of the massive pressure of the ice sheet acting on some liquid water at its base. That, they argue, would be enough to force the water into minor cracks in the deposit, producing the vertical bands of material that interrupt the sandstone.

There are plenty of ways for there to be liquid water at the base of the ice sheet, including local heating due to friction, the draining of surface melts to the base of the glacier (we're seeing a lot of the latter in Greenland at present), or simply hitting the right combination of pressure and temperature. But hematite deposits are typically formed at elevated temperatures (in the area of 220° C), which isn't consistent with either of these processes.

Instead, the researchers argue that the hematite comes from geothermal fluids. There are signs of volcanic activity in Idaho that dates from this same period, and the researchers suggest that there may have been sporadic volcanism in Colorado related to this. This would create fluids warm enough to carry the iron oxides that ended up deposited as hematite in these sandstones.

While this provides some evidence that at least one part of the continental interior was covered in ice during the snowball Earth period, that doesn't necessarily apply to all areas of all continents. As Antarctica indicates, dry valleys and massive ice sheets can coexist in close proximity when the conditions are right. But the discovery does provide a window into a key period in the Earth's history that has otherwise been quite difficult to study.

PNAS, 2024. DOI: 10.1073/pnas.2410759121 (About DOIs).

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U.S. staff receiving the notices this week will stay on Boeing's payroll until January to comply with federal requirements that give workers 60 days' notice prior to ending their employment. News that Boeing would send out the Worker Adjustment and Retraining Notification (WARN) in mid-November was widely expected.

“As previously announced, we are adjusting our workforce levels to align with our financial reality and a more focused set of priorities," Boeing said in a statement. "We are committed to ensuring our employees have support during this challenging time."

(Reporting by David Shepardson in Washington and Allison Lampert in Montreal; Editing by Chizu Nomiyama)

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A British Columbia teen who contracted Canada's first known human case of H5 bird flu has deteriorated swiftly in recent days and is now in critical condition, health officials reported Tuesday.

The teen's case was announced Saturday by provincial health officials, who noted that the teen had no obvious exposure to animals that could explain an infection with the highly pathogenic avian influenza. The teen tested positive for H5 bird flu at BC's public health laboratory, and the result is currently being confirmed by the National Microbiology Laboratory in Winnipeg.

The teen's case reportedly began with conjunctivitis, echoing the H5N1 human case reports in the US. The case then progressed to fever and cough, and the teen was admitted to BC's Children's hospital late Friday. The teen's condition varied throughout the weekend but had taken a turn for the worse by Tuesday, according to BC provincial health officer Bonnie Henry.

"This was a healthy teenager prior to this—so, no underlying conditions—and it just reminds us that in young people, this is a virus that can progress and cause quite severe illness," Bonnie Henry said in a media briefing streamed by Global News on Tuesday.

Health officials in the province have opened an investigation to understand the source of the outbreak. Around three dozen contacts of the teen have been tested, and all have been negative. "The source of exposure is very likely to be an animal or bird and is being investigated by BC’s chief veterinarian and public health teams," health officials noted in the announcement over the weekend. The teen was reportedly exposed to pets, including dogs, cats, and reptiles, but testing so far has been negative on them.

Canada has reported H5N1 bird flu in wildlife and domestic birds. This year, there have been at least 24 reports of the virus in domestic bird facilities, including at least 10 infected premises in BC in October, according to data from the Canadian Food Inspection Agency.

Unlike the US, Canada has not detected avian influenza in any of its dairy herds, and the specific strain of H5N1 that is currently swooping through US dairy farms has not been detected in birds or any other animals in Canada.

In the US, H5N1 has been detected in 492 herds across 15 states since March. Of the affected herds, 278 are in California, which first detected the virus in late August. In domestic birds, the virus has sparked nearly 1,200 outbreaks since January 2022, affecting facilities in 48 states and over 105 million birds.

To date, at least 46 human cases have been detected in the US, all of which have been mild infections, typically marked by conjunctivitis and/or flu-like symptoms. All but one of the documented human cases has been in dairy or poultry workers. The one outlier case was in a person in Missouri, who did not have any clear contact with animals, similar to the teen's case in Canada.

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“We’re very excited to see what people do with this,” says John Jumper, who leads the AlphaFold team at DeepMind and last month, along with CEO Demis Hassabis, won a share of the 2024 Chemistry Nobel Prize for their work on the AI tool.

Major AlphaFold upgrade offers boost for drug discovery

AlphaFold3, unlike its predecessors, is capable of modelling proteins in concert with other molecules. But instead of releasing its underlying code — as was done with AlphaFold2 — DeepMind provided access via a web server that restricted the number and types of predictions scientists could make.

Crucially, the AlphaFold3 server prevented scientists from predicting how proteins behave in the presence of potential drugs. But now, DeepMind’s decision to release the code means academic scientists can predict such interactions by running the model themselves.

The company initially said that making AlphaFold3 available only through a web server struck the right balance between enabling access for research and protecting commercial ambitions. Isomorphic Labs, a DeepMind spinoff company in London, is applying AlphaFold3 to drug discovery.

But the publication of AlphaFold3 without its code or model weights — parameters obtained by training the software on protein structures and other data — drew criticism from scientists, who said the move undermined reproducibility. DeepMind swiftly reversed course and said it would make an open-source version of the tool available within half a year.

Anyone can now download the AlphaFold3 software code and use it non-commercially. But for now, only scientists with an academic affiliation can access the training weights on request.

Accessible versions

DeepMind has got competition: over the past few months, several companies have unveiled open-source protein structure prediction tools based on AlphaFold3, relying on specifications described in the original paper known as pseudocode.

Two Chinese companies — technology giant Baidu and TikTok developer ByteDance — have rolled out their own AlphaFold3 inspired models, as has a start-up in San Francisco, California, called Chai Discovery.

AlphaFold3 — why did Nature publish it without its code?

A key limitation of these models is that, like AlphaFold3, none is licensed for commercial applications such as drug discovery, says Mohammed AlQuraishi, a computational biologist at Columbia University in New York City. However, Chai Discovery’s model, Chai-1, can be used via a web server for such work, says Jack Dent, a co-founder of the company.

Another firm, San Francisco-based Ligo Biosciences, has released a restriction-free version of AlphaFold3. But it doesn’t yet have the full suite of capabilities, including the capacity to model drugs and molecules other than proteins.

Other teams are working on versions of AlphaFold3 that don’t come with such limits: AlQuraishi hopes to have a fully open-source model called OpenFold3 available by the end of the year. This would enable drug companies to retrain their own versions of the model using proprietary data, such as the structures of proteins bound to different drugs, potentially improving performance.

Openness matters

The last year has seen a flood of new biological AI models released by companies with varying approaches to openness. Anthony Gitter, a computational biologist at the University of Wisconsin-Madison, has no problem with for-profit companies joining his field — so long as they play by the same rules as other scientists when they share their work in journals and preprint servers.

If DeepMind makes claims about AlphaFold3 in a scientific publication, “I and others expect them to also share information about how predictions were made and put the AI models and code out in a way that we can inspect,” Gitter adds. “My group's not going to build on and use the tools that we can't inspect.”

Not all ‘open source’ AI models are actually open: here’s a ranking

The fact that several AlphaFold3 replications have already emerged shows that model was reproducible, even without open-source code, says Pushmeet Kohli, DeepMind’s head of AI for science. He adds that in future he would like to see more discussion about the publishing norms in a field increasingly populated by both academic and corporate researchers.

The open-source nature of AlphaFold2 led to a flood of innovation from other scientists. For instance, the winners of a recent protein design contest used the AI tool to design new proteins capable of binding a cancer target. Jumper’s favourite recent AlphaFold2 hack was from a team that used the tool to identify a key protein that helps sperm attach to egg cells.

Jumper can’t wait for such surprises to emerge after sharing AlphaFold3 — even if they don’t always bear fruit. “People will use it in weird ways,” he predicts. “Sometimes it will fail and sometimes it will succeed.”

doi: https://doi.org/10.1038/d41586-024-03708-4

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The decision was a defeat for the Dutch arm of Friends of the Earth and other environmental groups, which had hailed the original 2021 ruling as a victory for the climate. Tuesday's civil ruling can be appealed to the Dutch Supreme Court.

“This hurts,” Friends of the Earth director in the Netherlands Donald Pols said. “At the same time, we see that this case has ensured that major polluters are not immune and has further stimulated the debate about their responsibility in combating dangerous climate change. That is why we continue to tackle major polluters, such as Shell.”

Outside court, Pols said the fight against climate change “is a marathon, not a sprint, and the race has just begun.”

The ruling upholding Shell’s appeal came as a 12-day U.N. climate conference was entering its second day in Azerbaijan where countries are discussing how to fund cutting planet-warming emissions and adapt to ever-increasing weather extremes.

It marked a stinging defeat for climate activists after several courtroom victories. A court in The Hague in 2015 ordered the government to cut emissions by at least 25% by the end of 2020 from benchmark 1990 levels. The Dutch Supreme Court upheld the ruling five years ago.

Earlier this year, a U.N. tribunal on maritime law said that countries are legally required to reduce greenhouse gas pollution. The International Tribunal for the Law of the Sea found that carbon emissions qualify as marine pollution and said that countries must take steps to mitigate and adapt to their adverse effects.

And in April, Europe’s highest human rights court ruled that countries must better protect their people from the consequences of climate change.

In December the top U.N. legal body, the International Court of Justice, is holding public hearings on climate change after the world body requested a nonbinding advisory opinion on “the obligations of States in respect of climate change.” Dozens of countries are set to present arguments at two weeks of hearings.

In a written summary of Tuesday's ruling, the court said that Shell has a duty of care to limit its emissions, but it annulled the lower court's decision because it was “unable to establish that the social standard of care entails an obligation for Shell to reduce its CO2 emissions by 45%, or some other percentage.

"There is currently insufficient consensus in climate science on a specific reduction percentage to which an individual company like Shell should adhere.”

Shell has emitted 36,528 million tons of carbon dioxide, or CO2, since 1854, which is 2.1% of global emissions, according to an April report by the Carbon Majors Database.

Presiding Judge Carla Joustra said that Shell already has targets for climate-warming carbon emissions that are in line with demands of Friends of the Earth — both for what it directly produces and for emissions produced by energy the company purchase from others.

The court then ruled that “for Shell to reduce CO2 emissions caused by buyers of Shell products ... by a particular percentage would be ineffective in this case. Shell could meet that obligation by ceasing to trade in the fuels it purchases from third parties. Other companies would then take over that trade.”

Joustra said that, “The court’s final judgment is that Friends of the Earth's claims cannot be granted. The court therefore annuls the district court’s judgment.”

Climate activists sitting outside on the courthouse steps hugged, and some appeared close to tears after the decision.

“To be honest I was just really disappointed," Neele Boelens said. I was almost crying. I was in there in the court and it was just like... At first it looked really good for us but then it just went down hill."

Shell, meanwhile, welcomed the ruling.

“We are pleased with the court’s decision, which we believe is the right one for the global energy transition, the Netherlands and our company,” Shell plc Chief Executive Officer Wael Sawan said in a written statement. “Our target to become a net-zero emissions energy business by 2050 remains at the heart of Shell’s strategy and is transforming our business."

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During my first semester as a computer science graduate student at Princeton, I took COS 402: Artificial Intelligence. Toward the end of the semester, there was a lecture about neural networks. This was in the fall of 2008, and I got the distinct impression—both from that lecture and the textbook—that neural networks had become a backwater.

Neural networks had delivered some impressive results in the late 1980s and early 1990s. But then progress stalled. By 2008, many researchers had moved on to mathematically elegant approaches such as support vector machines.

I didn’t know it at the time, but a team at Princeton—in the same computer science building where I was attending lectures—was working on a project that would upend the conventional wisdom and demonstrate the power of neural networks. That team, led by Prof. Fei-Fei Li, wasn’t working on a better version of neural networks. They were hardly thinking about neural networks at all.

Rather, they were creating a new image dataset that would be far larger than any that had come before: 14 million images, each labeled with one of nearly 22,000 categories.

Li tells the story of ImageNet in her recent memoir, The Worlds I See. As she worked on the project, she faced plenty of skepticism from friends and colleagues.

“I think you’ve taken this idea way too far,” a mentor told her a few months into the project in 2007. “The trick is to grow with your field. Not to leap so far ahead of it.”

It wasn’t just that building such a large dataset was a massive logistical challenge. People doubted that the machine learning algorithms of the day would benefit from such a vast collection of images.

“Pre-ImageNet, people did not believe in data,” Li said in a September interview at the Computer History Museum. “Everyone was working on completely different paradigms in AI with a tiny bit of data.”

Ignoring negative feedback, Li pursued the project for more than two years. It strained her research budget and the patience of her graduate students. When she took a new job at Stanford in 2009, she took several of those students—and the ImageNet project—with her to California.

ImageNet received little attention for the first couple of years after its release in 2009. But in 2012, a team from the University of Toronto trained a neural network on the ImageNet dataset, achieving unprecedented performance in image recognition. That groundbreaking AI model, dubbed AlexNet after lead author Alex Krizhevsky, kicked off the deep learning boom that has continued to the present day.

AlexNet would not have succeeded without the ImageNet dataset. AlexNet also would not have been possible without a platform called CUDA, which allowed Nvidia’s graphics processing units (GPUs) to be used in non-graphics applications. Many people were skeptical when Nvidia announced CUDA in 2006.

So the AI boom of the last 12 years was made possible by three visionaries who pursued unorthodox ideas in the face of widespread criticism. One was Geoffrey Hinton, a University of Toronto computer scientist who spent decades promoting neural networks despite near-universal skepticism. The second was Jensen Huang, the CEO of Nvidia, who recognized early that GPUs could be useful for more than just graphics.

The third was Fei-Fei Li. She created an image dataset that seemed ludicrously large to most of her colleagues. But it turned out to be essential for demonstrating the potential of neural networks trained on GPUs.

Geoffrey Hinton

A neural network is a network of thousands, millions, or even billions of neurons. Each neuron is a mathematical function that produces an output based on a weighted average of its inputs.

Suppose you want to create a network that can identify handwritten decimal digits like the number two in the red square above. Such a network would take in an intensity value for each pixel in an image and output a probability distribution over the ten possible digits—0, 1, 2, and so forth.

To train such a network, you first initialize it with random weights. You then run it on a sequence of example images. For each image, you train the network by strengthening the connections that push the network toward the right answer (in this case, a high-probability value for the “2” output) and weakening connections that push toward a wrong answer (a low probability for “2” and high probabilities for other digits). If trained on enough example images, the model should start to predict a high probability for “2” when shown a two—and not otherwise.

In the late 1950s, scientists started to experiment with basic networks that had a single layer of neurons. However, their initial enthusiasm cooled as they realized that such simple networks lacked the expressive power required for complex computations.

Deeper networks—those with multiple layers—had the potential to be more versatile. But in the 1960s, no one knew how to train them efficiently. This was because changing a parameter somewhere in the middle of a multi-layer network could have complex and unpredictable effects on the output.

So by the time Hinton began his career in the 1970s, neural networks had fallen out of favor. Hinton wanted to study them, but he struggled to find an academic home in which to do so. Between 1976 and 1986, Hinton spent time at four different research institutions: Sussex University, the University of California San Diego (UCSD), a branch of the UK Medical Research Council, and finally Carnegie Mellon, where he became a professor in 1982.

Geoffrey Hinton speaking in Toronto in June.

Credit: Photo by Mert Alper Dervis/Anadolu via Getty Images

In a landmark 1986 paper, Hinton teamed up with two of his former colleagues at UCSD, David Rumelhart and Ronald Williams, to describe a technique called backpropagation for efficiently training deep neural networks.

Their idea was to start with the final layer of the network and work backward. For each connection in the final layer, the algorithm computes a gradient—a mathematical estimate of whether increasing the strength of that connection would push the network toward the right answer. Based on these gradients, the algorithm adjusts each parameter in the model’s final layer.

The algorithm then propagates these gradients backward to the second-to-last layer. A key innovation here is a formula—based on the chain rule from high school calculus—for computing the gradients in one layer based on gradients in the following layer. Using these new gradients, the algorithm updates each parameter in the second-to-last layer of the model. The gradients then get propagated backward to the third-to-last layer, and the whole process repeats once again.

The algorithm only makes small changes to the model in each round of training. But as the process is repeated over thousands, millions, billions, or even trillions of training examples, the model gradually becomes more accurate.

Hinton and his colleagues weren’t the first to discover the basic idea of backpropagation. But their paper popularized the method. As people realized it was now possible to train deeper networks, it triggered a new wave of enthusiasm for neural networks.

Hinton moved to the University of Toronto in 1987 and began attracting young researchers who wanted to study neural networks. One of the first was the French computer scientist Yann LeCun, who did a year-long postdoc with Hinton before moving to Bell Labs in 1988.

Hinton’s backpropagation algorithm allowed LeCun to train models deep enough to perform well on real-world tasks like handwriting recognition. By the mid-1990s, LeCun’s technology was working so well that banks started to use it for processing checks.

“At one point, LeCun’s creation read more than 10 percent of all checks deposited in the United States,” wrote Cade Metz in his 2022 book Genius Makers.

But when LeCun and other researchers tried to apply neural networks to larger and more complex images, it didn’t go well. Neural networks once again fell out of fashion, and some researchers who had focused on neural networks moved on to other projects.

Hinton never stopped believing that neural networks could outperform other machine learning methods. But it would be many years before he’d have access to enough data and computing power to prove his case.

Jensen Huang

Jensen Huang speaking in Denmark in October.

Credit: Photo by MADS CLAUS RASMUSSEN/Ritzau Scanpix/AFP via Getty Images

The brain of every personal computer is a central processing unit (CPU). These chips are designed to perform calculations in order, one step at a time. This works fine for conventional software like Windows and Office. But some video games require so many calculations that they strain the capabilities of CPUs. This is especially true of games like Quake, Call of Duty, and Grand Theft Auto, which render three-dimensional worlds many times per second.

So gamers rely on GPUs to accelerate performance. Inside a GPU are many execution units—essentially tiny CPUs—packaged together on a single chip. During gameplay, different execution units draw different areas of the screen. This parallelism enables better image quality and higher frame rates than would be possible with a CPU alone.

Nvidia invented the GPU in 1999 and has dominated the market ever since. By the mid-2000s, Nvidia CEO Jensen Huang suspected that the massive computing power inside a GPU would be useful for applications beyond gaming. He hoped scientists could use it for compute-intensive tasks like weather simulation or oil exploration.

So in 2006, Nvidia announced the CUDA platform. CUDA allows programmers to write “kernels,” short programs designed to run on a single execution unit. Kernels allow a big computing task to be split up into bite-sized chunks that can be processed in parallel. This allows certain kinds of calculations to be completed far faster than with a CPU alone.

But there was little interest in CUDA when it was first introduced, wrote Steven Witt in The New Yorker last year:

When CUDA was released, in late 2006, Wall Street reacted with dismay. Huang was bringing supercomputing to the masses, but the masses had shown no indication that they wanted such a thing.

 

“They were spending a fortune on this new chip architecture,” Ben Gilbert, the co-host of “Acquired,” a popular Silicon Valley podcast, said. “They were spending many billions targeting an obscure corner of academic and scientific computing, which was not a large market at the time—certainly less than the billions they were pouring in.”

 

Huang argued that the simple existence of CUDA would enlarge the supercomputing sector. This view was not widely held, and by the end of 2008, Nvidia’s stock price had declined by seventy percent…

 

Downloads of CUDA hit a peak in 2009, then declined for three years. Board members worried that Nvidia’s depressed stock price would make it a target for corporate raiders.

Huang wasn’t specifically thinking about AI or neural networks when he created the CUDA platform. But it turned out that Hinton’s backpropagation algorithm could easily be split up into bite-sized chunks. So training neural networks turned out to be a killer app for CUDA.

According to Witt, Hinton was quick to recognize the potential of CUDA:

In 2009, Hinton’s research group used Nvidia’s CUDA platform to train a neural network to recognize human speech. He was surprised by the quality of the results, which he presented at a conference later that year. He then reached out to Nvidia. “I sent an e-mail saying, ‘Look, I just told a thousand machine-learning researchers they should go and buy Nvidia cards. Can you send me a free one?’ ” Hinton told me. “They said no.”

Despite the snub, Hinton and his graduate students, Alex Krizhevsky and Ilya Sutskever, obtained a pair of Nvidia GTX 580 GPUs for the AlexNet project. Each GPU had 512 execution units, allowing Krizhevsky and Sutskever to train a neural network hundreds of times faster than would be possible with a CPU. This speed allowed them to train a larger model—and to train it on many more training images. And they would need all that extra computing power to tackle the massive ImageNet dataset.

Fei-Fei Li

Fei-Fei Li at the SXSW conference in 2018.

Credit: Photo by Hubert Vestil/Getty Images for SXSW

Fei-Fei Li wasn’t thinking about either neural networks or GPUs as she began a new job as a computer science professor at Princeton in January of 2007. While earning her PhD at Caltech, she had built a dataset called Caltech 101 that had 9,000 images across 101 categories.

That experience had taught her that computer vision algorithms tended to perform better with larger and more diverse training datasets. Not only had Li found her own algorithms performed better when trained on Caltech 101, but other researchers also started training their models using Li’s dataset and comparing their performance to one another. This turned Caltech 101 into a benchmark for the field of computer vision.

So when she got to Princeton, Li decided to go much bigger. She became obsessed with an estimate by vision scientist Irving Biederman that the average person recognizes roughly 30,000 different kinds of objects. Li started to wonder if it would be possible to build a truly comprehensive image dataset—one that included every kind of object people commonly encounter in the physical world.

A Princeton colleague told Li about WordNet, a massive database that attempted to catalog and organize 140,000 words. Li called her new dataset ImageNet, and she used WordNet as a starting point for choosing categories. She eliminated verbs and adjectives, as well as intangible nouns like “truth.” That left a list of 22,000 countable objects ranging from “ambulance” to “zucchini.”

She planned to take the same approach she’d taken with the Caltech 101 dataset: use Google’s image search to find candidate images, then have a human being verify them. For the Caltech 101 dataset, Li had done this herself over the course of a few months. This time she would need more help. She planned to hire dozens of Princeton undergraduates to help her choose and label images.

But even after heavily optimizing the labeling process—for example, pre-downloading candidate images so they’re instantly available for students to review—Li and her graduate student Jia Deng calculated that it would take more than 18 years to select and label millions of images.

The project was saved when Li learned about Amazon Mechanical Turk, a crowdsourcing platform Amazon had launched a couple of years earlier. Not only was AMT’s international workforce more affordable than Princeton undergraduates, but the platform was also far more flexible and scalable. Li’s team could hire as many people as they needed, on demand, and pay them only as long as they had work available.

AMT cut the time needed to complete ImageNet down from 18 to two years. Li writes that her lab spent two years “on the knife-edge of our finances” as the team struggled to complete the ImageNet project. But they had enough funds to pay three people to look at each of the 14 million images in the final data set.

ImageNet was ready for publication in 2009, and Li submitted it to the Conference on Computer Vision and Pattern Recognition, which was held in Miami that year. Their paper was accepted, but it didn’t get the kind of recognition Li hoped for.

“ImageNet was relegated to a poster session,” Li writes. “This meant that we wouldn’t be presenting our work in a lecture hall to an audience at a predetermined time but would instead be given space on the conference floor to prop up a large-format print summarizing the project in hopes that passersby might stop and ask questions… After so many years of effort, this just felt anticlimactic.”

To generate public interest, Li turned ImageNet into a competition. Realizing that the full dataset might be too unwieldy to distribute to dozens of contestants, she created a much smaller (but still massive) dataset with 1,000 categories and 1.4 million images.

The first year’s competition in 2010 generated a healthy amount of interest, with 11 teams participating. The winning entry was based on support vector machines. Unfortunately, Li writes, it was “only a slight improvement over cutting-edge work found elsewhere in our field.”

The second year of the ImageNet competition attracted fewer entries than the first. The winning entry in 2011 was another support vector machine, and it just barely improved on the performance of the 2010 winner. Li started to wonder if the critics had been right. Maybe “ImageNet was too much for most algorithms to handle.”

“For two years running, well-worn algorithms had exhibited only incremental gains in capabilities, while true progress seemed all but absent,” Li writes. “If ImageNet was a bet, it was time to start wondering if we’d lost.”

But when Li reluctantly staged the competition a third time in 2012, the results were totally different. Geoff Hinton’s team was the first to submit a model based on a deep neural network. And its top-5 accuracy was 85 percent—10 percentage points better than the 2011 winner.

Li’s initial reaction was incredulity: “Most of us saw the neural network as a dusty artifact encased in glass and protected by velvet ropes.”

“This is proof”

Yann LeCun testifies before the US Senate in September.

Credit: Photo by Kevin Dietsch/Getty Images

The ImageNet winners were scheduled to be announced at the European Conference on Computer Vision in Florence, Italy. Li, who had a baby at home in California, was planning to skip the event. But when she saw how well AlexNet had done on her dataset, she realized this moment would be too important to miss: “I settled reluctantly on a twenty-hour slog of sleep deprivation and cramped elbow room.”

On an October day in Florence, Alex Krizhevsky presented his results to a standing-room-only crowd of computer vision researchers. Fei-Fei Li was in the audience. So was Yann LeCun.

Cade Metz reports that after the presentation, LeCun stood up and called AlexNet “an unequivocal turning point in the history of computer vision. This is proof.”

The success of AlexNet vindicated Hinton’s faith in neural networks, but it was arguably an even bigger vindication for LeCun.

AlexNet was a convolutional neural network, a type of neural network that LeCun had developed 20 years earlier to recognize handwritten digits on checks. (For more details on how CNNs work, see the in-depth explainer I wrote for Ars in 2018.) Indeed, there were few architectural differences between AlexNet and LeCun’s image recognition networks from the 1990s.

AlexNet was simply far larger. In a 1998 paper, LeCun described a document-recognition network with seven layers and 60,000 trainable parameters. AlexNet had eight layers, but these layers had 60 million trainable parameters.

LeCun could not have trained a model that large in the early 1990s because there were no computer chips with as much processing power as a 2012-era GPU. Even if LeCun had managed to build a big enough supercomputer, he would not have had enough images to train it properly. Collecting those images would have been hugely expensive in the years before Google and Amazon Mechanical Turk.

And this is why Fei-Fei Li’s work on ImageNet was so consequential. She didn’t invent convolutional networks or figure out how to make them run efficiently on GPUs. But she provided the training data that large neural networks needed to reach their full potential.

The technology world immediately recognized the importance of AlexNet. Hinton and his students formed a shell company with the goal to be “acquihired” by a big tech company. Within months, Google purchased the company for $44 million. Hinton worked at Google for the next decade while retaining his academic post in Toronto. Ilya Sutskever spent a few years at Google before becoming a cofounder of OpenAI.

AlexNet also made Nvidia GPUs the industry standard for training neural networks. In 2012, the market valued Nvidia at less than $10 billion. Today, Nvidia is one of the most valuable companies in the world, with a market capitalization north of $3 trillion. That high valuation is driven mainly by overwhelming demand for GPUs like the H100 that are optimized for training neural networks.

Sometimes the conventional wisdom is wrong

“That moment was pretty symbolic to the world of AI because three fundamental elements of modern AI converged for the first time,” Li said in a September interview at the Computer History Museum. “The first element was neural networks. The second element was big data, using ImageNet. And the third element was GPU computing.”

Today, leading AI labs believe the key to progress in AI is to train huge models on vast data sets. Big technology companies are in such a hurry to build the data centers required to train larger models that they’ve started to lease out entire nuclear power plants to provide the necessary power.

You can view this as a straightforward application of the lessons of AlexNet. But I wonder if we ought to draw the opposite lesson from AlexNet: that it’s a mistake to become too wedded to conventional wisdom.

“Scaling laws” have had a remarkable run in the 12 years since AlexNet, and perhaps we’ll see another generation or two of impressive results as the leading labs scale up their foundation models even more.

But we should be careful not to let the lessons of AlexNet harden into dogma. I think there’s at least a chance that scaling laws will run out of steam in the next few years. And if that happens, we’ll need a new generation of stubborn nonconformists to notice that the old approach isn’t working and try something different.

Tim Lee was on staff at Ars from 2017 to 2021. Last year, he launched a newsletter, Understanding AI, that explores how AI works and how it's changing our world. You can subscribe here.

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Montana Mountain King, a sheep cloned from near threatened Marco Polo argali sheep as part of an unlawful

scheme to create large, hybrid sheep for hunting in the US.Photograph: AP

In September, a man from Montana was sentenced to six months in prison after he trafficked a clone of one of the world’s largest sheep species. Court documents allege that Arthur Schubarth trafficked body parts of a near threatened Marco Polo argali sheep into the US from Kyrgyzstan and in 2015 contracted with a lab to create a cloned sheep he later named Montana Mountain King (MMK). Later, the documents allege, Schubarth used MMK’s semen to impregnate ewes and then sold offspring—each carrying some Marco Polo argali genetics—to people involved in big game hunting.

It’s a weird case. It’s likely only the second time that an American has been prosecuted for a wildlife crime that involved animal cloning. (In 2011 a man was fined $1.5 million and ordered to surrender smuggled deer as well as nearly $1 million of deer semen—which investigators believed he intended to use to clone whitetail deer—in a case that involved the unlawful purchase and transportation of deer.)

There’s another strange element to Schubarth’s story: Potentially dozens of MMK’s descendants may now be at large in the US. These sheep that contain genetics from MMK are defined as contraband in the handful of plea agreements that were signed by men who were alleged to have bought sheep from Schubarth or transported ewes to his ranch in Montana to be impregnated. What isn’t clear is how many sheep are at large, and what exactly has happened to them.

However, legal documents offer some clues. One legal filing in the case against Schubarth alleges that in November 2018 one person transported 26 ewes to Schubarth’s ranch in Montana to be inseminated with MMK semen, and a year later the same person later transported another 48 ewes. In July 2020, the same document alleges, two other people transported another 43 sheep to Schubarth’s ranch. That’s at least several dozen sheep that may have carried MMK’s offspring—and each of those may have had several lambs.

The same document also alleges that one of MMK’s offspring was transported from Minnesota to Schubarth’s ranch in Montana in May 2019. Then in July 2020 Schubarth agreed to sell 11 of MMK’s grandchildren for a total of $13,200 and one of MMK’s children, a sheep called Montana Black Magic, for $10,000. It’s also alleged that Schubarth sold another Marco Polo hybrid sheep to a man who lives in South Dakota.

At least one sheep is accounted for: MMK himself. The sheep had initially been taken to a Zoological Association of America accredited facility in Oregon, says Christina Meister of the US Fish and Wildlife Service (USFWS) Office of Public Affairs. On October 2, MMK was flown across the country to Rosamond Gifford Zoo in Syracuse, New York, where he will be housed for the long term. MMK is expected to be on exhibition at the zoo in mid-November, Meister says. (The USFWS declined to answer other questions posed by WIRED.)

The fate of the other sheep is less clear. The four men who have been indicted in these interlinked cases all signed plea agreements that require them to quarantine any sheep in their possession containing Marco Polo argali genetics. The plea agreements also require the men to “abandon all property rights” in the sheep and allow the USFWS to neuter the animals. The men also have to submit autopsy reports to the USFWS when any of the sheep die.

“It was an extremely interesting case,” says Chris Tenoglia, an attorney who represented Michael Ball—a man charged with false labeling of wildlife under the Lacey Act, which prohibits the transportation, trade, and mislabeling of certain species. Ball pleaded guilty to the Lacey Act violation and was ordered to serve one year’s probation and pay a fine of $20,000. Tenoglia says that Ball euthanized the nine sheep in his possession that had been crossbred with the cloned sheep.

“[Ball] is in the animal husbandry and breeding business and he did not want one of the cloned sheep he had to crossbreed with the stock he had on hand, accidentally,” Tenoglia wrote in an email to WIRED. “He was worried that no matter how hard he might try to keep them separated, it might not work, and he did not want to have a problem, assuming that could happen in the future.”

Attorney Carl Jensen represented another defendant, Riley Niewenhuis, who pleaded guilty to a count of trafficking under the Lacey Act. Niewenhuis was sentenced to serve a 12-month term of probation and pay a fine of $20,000. Jensen says that he does not know if Niewenhuis has any of the hybrid sheep in his position, but is sure “he is doing everything to comply with whatever the government required of him.”

A trafficking case that involves animal cloning is extremely unusual, says Monique Sosnowski, a wildlife crime and security analyst at Farmingdale State College in New York state. It raises all kinds of strange questions, she says, like whether a cloned sheep should be considered an endangered or invasive species. According to Tenoglia, one of the government’s worries was that if MMK’s offspring were left to roam in the wild, they could dominate and outcompete native species in the US. When WIRED asked the Department of Justice about this concern, spokesperson Matthew Nies said that the department had nothing to add.

The Schubarth case also raises the question of whether regulations on cloning companies should be tightened to ensure they’re not involved in cloning endangered species. Cloning is catching on, with thousands of dogs, cats, and horses having been cloned in the US already. Legal documents allege that in 2015 Schubarth paid a deposit of $4,200 to enter into a “ovine cloning contract” to clone the Marco Polo argali sheep illegally trafficked into the US.

Blake Russell, president at pet cloning company ViaGen Pets, says his company requires its clients to sign a document stating they have the legal rights to clone from the tissue they’re providing. “If it is something of ‘sensitive’ origin, then we would investigate, and we have many friends in regulatory roles—they can investigate anything suspicious,” Russell wrote in an email to WIRED. The Schubarth case was a “one-off bad deal for all involved. We were not the party involved in the cloning. This case will increase diligence for all of us in the field to make certain that we are not violating any regulations.”

In the meantime, there is still the matter of those hybrid sheep. A fourth man implicated in the Schubarth case was sentenced to three years probation and $25,000 in fines. He has also signed a plea agreement requiring him to quarantine any hybrid sheep in his possession. He is alleged to have bought 12 hybrid Marco Polo argali sheep from Schubarth.

As cloning technology becomes more widespread and cheaper, it’s likely that wildlife law will have to play catch-up, says Sosnowski. There are a lot of exotic species out there that people will be interested in cloning, she says. “I’m sure this is only going to be the first of many cases.”

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THIS ARTICLE IS republished from The Conversation under a Creative Commons license.

Clouds form when water vapor—an invisible gas in the atmosphere—sticks to tiny floating particles, such as dust, and turns into liquid water droplets or ice crystals. In a newly published study, we show that microplastic particles can have the same effects, producing ice crystals at temperatures 5 to 10 degrees Celsius (9 to 18 degrees Fahrenheit) warmer than droplets without microplastics.

This suggests that microplastics in the air may affect weather and climate by producing clouds in conditions where they would not form otherwise.

We are atmospheric chemists who study how different types of particles form ice when they come into contact with liquid water. This process, which occurs constantly in the atmosphere, is called nucleation.

Clouds in the atmosphere can be made up of liquid water droplets, ice particles or a mixture of the two. In clouds in the mid- to upper atmosphere where temperatures are between 32 and –36 degrees Fahrenheit (0 to –38 degrees Celsius), ice crystals normally form around mineral dust particles from dry soils or biological particles, such as pollen or bacteria.

Microplastics are less than 5 millimeters wide—about the size of a pencil eraser. Some are microscopic. Scientists have found them in Antarctic deep seas, the summit of Mount Everest, and fresh Antarctic snow. Because these fragments are so small, they can be easily transported in the air.

Why It Matters

Ice in clouds has important effects on weather and climate because most precipitation typically starts as ice particles.

Many cloud tops in nontropical zones around the world extend high enough into the atmosphere that cold air causes some of their moisture to freeze. Then, once ice forms, it draws water vapor from the liquid droplets around it, and the crystals grow heavy enough to fall. If ice doesn’t develop, clouds tend to evaporate rather than causing rain or snowfall.

While children learn in grade school that water freezes at 32 degrees Fahrenheit (0 degrees Celsius), that’s not always true. Without something to nucleate onto, such as dust particles, water can be supercooled to temperatures as low as –36 degrees Fahrenheit (–38 degrees Celsius) before it freezes.

For freezing to occur at warmer temperatures, some kind of material that won’t dissolve in water needs to be present in the droplet. This particle provides a surface where the first ice crystal can form. If microplastics are present, they could cause ice crystals to form, potentially increasing rain or snowfall.

Clouds also affect weather and climate in several ways. They reflect incoming sunlight away from Earth’s surface, which has a cooling effect, and absorb some radiation that is emitted from Earth’s surface, which has a warming effect.

The amount of sunlight reflected depends on how much liquid water versus ice a cloud contains. If microplastics increase the presence of ice particles in clouds compared with liquid water droplets, this shifting ratio could change clouds’ effect on Earth’s energy balance.

How We Did Our Work

To see whether microplastic fragments could serve as nuclei for water droplets, we used four of the most prevalent types of plastics in the atmosphere: low density polyethylene, polypropylene, polyvinyl chloride, and polyethylene terephthalate. Each was tested both in a pristine state and after exposure to ultraviolet light, ozone, and acids. All of these are present in the atmosphere and could affect the composition of the microplastics.

We suspended the microplastics in small water droplets and slowly cooled the droplets to observe when they froze. We also analyzed the plastic fragments’ surfaces to determine their molecular structure, since ice nucleation could depend on the microplastics’ surface chemistry.

For most of the plastics we studied, 50 percent of the droplets were frozen by the time they cooled to –8 degrees Fahrenheit (–22 degrees Celsius). These results parallel those from another recent study by Canadian scientists, who also found that some types of microplastics nucleate ice at warmer temperatures than droplets without microplastics.

Exposure to ultraviolet radiation, ozone, and acids tended to decrease ice nucleation activity on the particles. This suggests that ice nucleation is sensitive to small chemical changes on the surface of microplastic particles. However, these plastics still nucleated ice, so they could still affect the amount of ice in clouds.

What Still Isn’t Known

To understand how microplastics affect weather and climate, we need to know their concentrations at the altitudes where clouds form. We also need to understand the concentration of microplastics compared with other particles that could nucleate ice, such as mineral dust and biological particles, to see whether microplastics are present at comparable levels. These measurements would allow us to model the impact of microplastics on cloud formation.

Plastic fragments come in many sizes and compositions. In future research, we plan to work with plastics that contain additives, such as plasticizers and colorants, as well as with smaller plastic particles.

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Sunday, 10 November

• Who: SpaceX
• What: Falcon 9
• When: 21:28 - 01:28 UTC
• Where: Florida, United States
• Why: SpaceX will use a Falcon 9 rocket to launch 24 Starlink satellites into a low Earth orbit. This group of satellites will be known as Starlink Group 6-69. If you want to find them after launch, you can use apps like ISS Detector to see when they will pass overhead where you live. After the launch, the first stage of the rocket will likely perform a landing.

Monday, 11 November

• Who: CAS Space
• What: Kinetica 1
• When: 04:05 - 04:26
• Where: Jiuquan Satellite Launch Center, China
• Why: CAS Space will use its Kinetica 1 rocket to launch 15 satellites into orbit. It's unclear what these satellites will be used for.

• Who: SpaceX
• What: Falcon 9
• When: 17:07 UTC
• Where: Florida, US
• Why: SpaceX will launch a Falcon 9 carrying the Koreasat 6A satellite for KT Sat. The satellite will replace the current Koreasat 6 satellite and will deliver fixed satellite service (FSS) and broadcasting satellite service (BSS) in South Korea.

Wednesday, 13 November

• Who: SpaceX
• What: Starlink
• When: 11:00 - 15:00 UTC
• Where: Florida, US
• Why: SpaceX will use a Falcon 9 rocket to launch 23 Starlink satellites to low Earth orbit. This group is Starlink Group 6-68. The first stage of the rocket will likely land so it can be reused.

• Who: CNSA
• What: Long March 4C
• When: 22:50 UTC
• Where: Taiyuan Satellite Launch Center, China
• Why: China will launch the Long March 4C carrying an unknown payload.

Thursday, 14 November

• Who: SpaceX
• What: Falcon 9
• When: 04:21 - 08:21 UTC
• Where: California, US
• Why: SpaceX will launch yet another Falcon 9 carrying 20 Starlink satellites called Starlink Group 9-11. Notably, this batch includes 13 direct-to-cell Starlink satellites. The first stage will also likely try to land for reuse.

Friday, 15 November

• Who: CNSA
• What: Long March
• When: 15:12 UTC
• Where: Wenchang Satellite Launch Center, China
• Why: China will launch a Long March 7 rocket carrying the 8th Tianzhou cargo craft which is heading to the Chinese Space Station (CSS). The Tianzhou 8 will supply the astronauts with their needs and operate for about 9 months in space.

Recap

The first launch we saw last week was Mitsubishi H3's fourth launch. It took off from JAXA Tanegashima Space Center at 06:48 UTC carrying the X-band defense communication satellite 3, also known as Kirameki 3.

The second launch saw Roscosmos launch a Soyuz 2.1b from Vostochny Cosmodrome in Russia at 23:18 UTC. It was carrying two Ionosfera-M satellites and 53 small satellites. The Ionosfera-M satellites will observe the Earth's ionosphere.

Next up, SpaceX launched a Falcon 9 carrying the CRS-31 Dragon spacecraft to the International Space Station. Following the launch, the first stage of the rocket landed at Cape Canaveral.

The fourth launch came from Mahia, New Zealand, where Rocket Lab launched an Electron rocket in a mission called "Changes In Latitudes, Changes in Attitudes". In this mission, it launched a single commercial satellite into low Earth orbit for a confidential commercial customer.

Next, we got a Falcon 9 launch from SpaceX carrying Starlink satellites with the first stage performing a landing.

The sixth launch was a Long March 2C taking off from Jiuquan Satellite Launch Center in China carrying four PIESAT 2 satellites. The satellites will be used to synthetic aperture radar imaging with high-precision imaging capability.

The seventh and final launch saw SpaceX launch another Falcon 9 carrying 20 Starlink satellites designated Starlink Group 9-10. The first stage of the rocket landed on a drone ship in the Pacific Ocean.

That's all for this week, check back next time!

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If you need any inspiration for cutting loose and relaxing this weekend, look no further than a free-wheeling troop of monkeys that broke out of their South Carolina research facility Wednesday and, as of noon Friday, were still "playfully exploring" with their newfound freedom.

In an update Friday, the police department of Yemassee, SC said that the 43 young, female rhesus macaque monkeys are still staying around the perimeter of the Alpha Genesis Primate Research Facility. "The primates are exhibiting calm and playful behavior, which is a positive indication," the department noted.

The fun-loving furballs got free after a caretaker "failed to secure doors" at the facility.

Alpha Genesis staff have been keeping an eye on the escapees, trying to entice them back in with food. But, instead of taking the bait, the primates have been playing on the perimeter fence while still keeping in touch with the monkeys inside by cooing to them.

"They're just being goofy monkeys jumping back and forth playing with each other," Alpha Genesis CEO Greg Westergaard told CBS News Thursday. "It's kind of like a playground situation here."

Yemassee police note that the monkeys are very young and small—only about 6 or 7 pounds each. They have not been used for any testing yet, don't carry any disease, and pose no health risk to the public. Still, area residents have been advised to keep their doors and windows locked in case the wee primates try to pay a visit.

This isn't the first time—or even the second time—Alpha Genesis has had trouble keeping its monkeys under control. In 2018, the US Department of Agriculture fined the company $12,600 for violations between 2014 and 2016 that included four monkey breakouts. In those incidents, a total of 30 monkeys escaped. One was never found.

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DNA evidence rewrites histories of those buried in Pompeii when Vesuvius erupted.

Credit: Archeological Park of Pompeii

People have long been fascinated by the haunting plaster casts of the bodies of people who died in Pompeii when Mount Vesuvius erupted in 79 CE. Archaeologists have presented certain popular narratives about who these people might have been and how they might have been related. But ancient DNA analysis has revealed that those preferred narratives were not entirely accurate and may reflect certain cultural biases, according to a new paper published in the journal Current Biology. The results also corroborate prior research suggesting that the people of ancient Pompeii were the descendants of immigrants from the Eastern Mediterranean.

As previously reported, the eruption of Mount Vesuvius released thermal energy roughly equivalent to 100,000 times the atomic bombs dropped on Hiroshima and Nagasaki at the end of World War II, spewing molten rock, pumice, and hot ash over the cities of Pompeii and Herculaneum in particular. The vast majority of people in Pompeii and Herculaneum—the cities hardest hit—perished from asphyxiation, choking on the thick clouds of noxious gas and ash. But at least some of the Vesuvian victims probably died instantaneously from the intense heat of fast-moving lava flows, with temperatures high enough to boil brains and explode skulls.

In the first phase, immediately after the eruption, a long column of ash and pumice blanketed the surrounding towns, most notably Pompeii and Herculaneum. By late night or early morning, pyroclastic flows (fast-moving hot ash, lava fragments, and gases) swept through and obliterated what remained, leaving the bodies of the victims frozen in seeming suspended action.

In the 19th century, an archaeologist named Giuseppe Fiorelli figured out how to make casts of those frozen bodies by pouring liquid plaster into the voids where the soft tissue had been. Some 1,000 bodies have been discovered in the ruins, and 104 plaster casts have been preserved. Restoration efforts of 86 of those casts began about 10 years ago, during which researchers took CT scans and X-rays to see if there were complete skeletons inside. Those images revealed that there had been a great deal of manipulation of the casts, depending on the aesthetics of the era in which they were made, including altering some features of the bodies' shapes or adding metal rods to stabilize the cast, as well as frequently removing bones before casting.

Pompeii body cast in the Villa of the Mysteries.

Credit: Pompeii body casts

The authors of this latest paper argue that these manipulations should call into question some of the popular interpretations of the identities of Pompeii victims. Drawing on multiple studies demonstrating that it is possible to retrieve DNA from both human and animal remains in Pompeii, they managed to extract genetic information from some of those plaster casts containing highly fragmented skeletal remains, in hopes of putting some of those popular interpretations to the test.

Four Pompeii victims were found in 1974 in what is known as the "House of the golden bracelet." Three (two adults and one child) were found at the foot of a staircase leading to a garden and the seafront. Archaeologists thought this was likely a father, mother, and their child because of the arrangement of the bodies, as well as a golden bracelet worn on the arm of one of the bodies. But it wasn't possible to definitely determine the sex of any of the bodies. The hypothesis was that the trio had taken shelter in the stairwell but were killed when it collapsed. A fourth body of a child, about age 4, was found nearby, presumed to have died while trying to escape to the garden.

This new DNA analysis showed that this conventional interpretation was incorrect. All the bodies were male, including the one with the golden bracelet, and none of them were genetically related. It wasn't possible to glean much information about physical characteristics, but one person had black hair and dark skin, and two others probably had brown eyes. The ancestry of all four was consistent with origins in North Africa or the Mediterranean.

In 1914, nine bodies were found in the garden in front of the "House of the cryptoporticus," so named because there is an underground passage running along three sides of that garden. Only four were preserved in plaster, including two bodies that seemed to be embracing. Archaeologists suggested they were lovers, mother/daughter, or two sisters. The authors were only able to extract DNA from one of those bodies, revealing that it was male, excluding two of those possible interpretations. His ancestry was of Near Eastern/North African origin.

Pompeii plaster casts in the House of the Golden Bracelet.

Credit: Archeological Park of Pompeii

Several bodies were found in the "Villa of the Mysteries" in 1909–1910, known for its decorative frescoes dedicated to Bacchus, the god of wine, religious ecstasy, and fertility. The villa even had a wine press, since it was common for wealthy families to make their own wine and olive oil, among other products. The authors focused on one particular body found lying on top of a layer of ash, wearing an engraved iron and carnelian ring on the left hand. Archaeologists suggested he was probably the custodian of the villa rather than a family member.

The DNA analysis confirmed that this body was a male of mixed genetic ancestry, primarily Eastern Mediterranean and European origin. In short, “The scientific data we provide do not always align with common assumptions,” said co-author David Reich, a geneticist at Harvard University. “These findings challenge traditional gender and familial assumptions.”

Reich also cautioned against making similar mistakes with DNA analysis. "Instead of establishing new narratives that might also misrepresent these people's experiences, the genetic results encourage reflection on the dangers of making up stories about gender and family relationships in past societies based on present-day expectations," he said.

“Our findings have significant implications for the interpretation of archaeological data and the understanding of ancient societies,” said co-author Alissa Mittnik, also of Harvard University. “They highlight the importance of integrating genetic data with archaeological and historical information to avoid misinterpretations based on modern assumptions. This study also underscores the diverse and cosmopolitan nature of Pompeii’s population, reflecting broader patterns of mobility and cultural exchange in the Roman Empire.”

DOI: Current Biology, 2024. 10.1016/j.cub.2024.10.007  (About DOIs).

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• Rindermann, H., Klauk, B. & Thompson, J. (2024). Intelligence of refugees in Germany: levels, differences and possible determinants. Journal of Controversial Ideas, 4(2). https://doi.org/10.35995/jci04020020; https://journalofcontroversialideas.org/article/4/2/281

Intelligence is the best predictor and the most important causal factor in job performance. Measuring intelligence therefore provides information about future job performance and employment. This applies to different professions and social groups, including immigrants and refugees. Two previous German studies with N=29 and N=552 refugees found average intelligence scores of IQ 92 and 86, respectively. A newer study with N=499 refugees and immigrants from N=15 countries conducted in 2017 to 2018 using the BOMAT, a German non-verbal and purely figural matrices test, found an average IQ of 90 (using the norms of the manual, 84 using a recent German comparison sample). Overall (as a result of our “mini-meta-analysis”), refugees’ cognitive abilities are about (5 to) 10 IQ points higher than the average abilities of people in their home countries (measured by student assessments or intelligence tests and compiled by various research groups), but 12 (to 15) IQ points below the German average. Positive selection, people that are more intelligent being more likely to leave their countries of origin, and accessibility to testing all likely play a role. At the individual level, refugees’ IQ was correlated with education: Each additional year of schooling corresponded to about 2 IQ points (r=.41). At the cross-national level, education was again significantly correlated with immigrants’ average IQ, but so were the level of cognitive ability in the home country (five different measures), income (GDP per capita as indicator of standard of living), positively valued policies (e.g., democracy), indicators of evolutionary ancestry, and culture (religion is used as a measure here). Individuals’ cognitive abilities could be better predicted with individual-level data than with country-level data (multiple R=.50 vs. .34). However, if individual predictors are not available, group predictors are not useless. Path analyses at different data levels showed indirect effects of country of origin cognitive ability on refugee intelligence via income and level of education.

The intelligence of nations is very important for projecting its future level of development. As such, examining both the internal and external forces on the evolution of intelligence is important. Internal forces meaning the direction of natural selection within the population (fertility correlation with traits). External forces meaning changes to the population, either from immigration or emigration.

Even if a population has neutral natural selection (no correlation between intelligence and fertility), the genetic level of intelligence may go up or down depending on who is leaving (elites? criminals?) and who is entering (elites? criminals?).

Rindermann and colleagues report a new study of about 500 immigrants in Germany. Their new result indicates a nonverbal IQ of about 85. This compares with an IQ of 86 from another recent study of 552 immigrants.

Using the Danish army test data for male second/third generation immigrants in Denmark, I found an average of 87 IQ. Denmark and Germany have a similar similar profile of immigrants, so we are happy the results are also similar.

The test was another matrix reasoning test ('Raven clone') called BOMAT, with 15 tiles:

Their main table of results gives the scores by country of origin:

Most of the sample consists of 'Syrians', while many of the other samples are quite small. Still, most of them find reasonable estimates, e.g., the 6 Somalis obtained a score of 78, which when using proper norms is about 73. This compares with a home country IQ of about 70.

They helpfully list several estimates of home country IQs. On the other hand, the 24 Polish refugees (?) obtained a score of 86 or so, strangely low (authors do not provide any speculation as to why). The standard error is 3 IQ, so this value is highly incongruent with the typical results of ~98 IQ in Poland.

Despite the small samples, the correlation between sample IQs and country of origin IQs was about .70. Regarding the norms, the authors say:

Comparison with the additional new German BOMAT sample of adults: In raw values, the average result of the immigrant sample was 12.04 solved BOMAT tasks (Klauk, 2019, p. 68). The two adult samples chosen for comparison, those predominantly working people and those entirely working people, solved on average 17.03 tasks (using a weighted average would result in a harder norm). The average standard deviation is 4.82. Using these two samples and their standard deviation would result in 84.47 IQ points (instead of IQ 90.03 in Table 2).16 The applied BOMAT norms from young persons therefore do not lead to an underestimation of migrant IQ, but rather to an overestimation. We then varied the group composition (working people, age) and also looked at newly collected data again later (October/November 2023).

Everything indicates that such variations would tend to lead to even slightly harder norms (lower migrant IQ). Over and beyond, it should be borne in mind that the norms obtained from samples from North Rhine-Westphalia (BOMAT manual, majority in the comparison sample) can be somewhat lenient relative to Germany (North Rhine-Westphalia always performs somewhat weaker in ability studies within Germany). In any case, there is no evidence of an underestimation of migrants’ IQs. Finally, it should be pointed out that questions of standardization have no consequences for the later correlative analyses (correlations are independent of the mean).

In short, the test manual used a too young cohort for comparison and from a German state with somewhat below average performance. They therefore collected new adult data, which resulted in a 5 IQ decrease in scores. Nothing mysterious about this correction.

Remember that the IQ metric is only a relative metric. It's not like grams or Kelvin degrees. It just means how well a given person performs relative to his age peers on a given test. International norms are obtained by designating some sample as the reference group (usually the British, Greenwich mean IQ) and comparing everybody else to them. Since European samples are generally used for norms, non-Europeans generally obtain scores below 100.

The study itself is pretty basic. The more interesting thing is that it took 3 years to get published. Why? The editorial by the editors of Journal of Controversial Ideas, Jeff McMahan , Francesca Minerva , Peter Singer, explain:

We are also publishing a paper that deals with one of the most controversial topics in academia: group differences in IQ. Academic freedom exists (or should exist) to protect exactly this kind of discussion, the kind that makes many of us uncomfortable, angry, shocked, and even disgusted. This doesn’t mean, of course, that this kind of discussion, or any discussion on a controversial topic, should be taken lightly. Indeed, we think the opposite is true: taking it lightly means automatically dismissing it, rather than responding to it with good counterarguments.

This paper was originally submitted to the journal in September 2021, so it took us an unusually long time to complete the review. In part, the delay was due to the fact that the paper involves empirical research and analysis of raw data in German, which required us to find a trusted German-speaking data analyst to check the raw data and ensure the results could be reproduced. We had also sent the paper to an English-speaking data analyst who had conducted a preliminary analysis and provided the authors with some initial feedback about the more technical parts of the paper, which the authors incorporated, but we felt that it was important to find someone who could rerun the analysis in the original language.

As we understand it, not all journals go to these lengths when reviewing a paper. But we believe that having an external data analyst rerun the analysis of the raw data is good practice, and we plan to continue to do this in the future to guard against faulty or distorted analysis of data. The topic itself adds a second layer of complexity. Because the topic of group differences in IQ is so taboo, there are not many qualified academics working in this area, so it took us some time to find qualified reviewers. But we are confident that the four reviewers were highly qualified for the task. The paper went through three rounds of reviews, and at each round of review, the paper was amended and sent back to the reviewers. After three rounds, the four reviewers were satisfied with how the authors had addressed their comments. We editors also read the paper twice and sent our comments to the authors at various stages of the review process.

The paper argues that asylum seekers coming from some Middle Eastern, Central Asian, and African countries have a lower average IQ than Germans.

The authors consider various possible explanations, from genetic factors to trauma and lack of education in the country of origin, but they don’t come down in favour of one or more of these explanations.

They also find that refugees who moved to Germany have a higher average IQ than their co-citizens who didn’t flee the country, and consider at least two plausible explanations: the people who found a way to flee the country have higher IQs, or education in Germany is of better quality and facilitates an increase in IQ. It makes sense that in countries ravaged by war, where schools are often closed for reasons of safety or are destroyed by bombs, children don’t develop their full cognitive potential.

According to the authors, each year of education is associated with two additional IQ points, so it’s not surprising that people who haven’t attended school for several years don’t fare as well as those who attend school regularly. In the paper, the authors report an interview with a teacher, in which it is said that “About 80% of these young people have missed nine years of schooling”. There could also be something about the quality of the education system in these countries that makes the education less effective even when it’s regularly provided. At the very least, this paper raises the important issue of education in countries where the education system does not provide continuous (and perhaps not high-quality) education.

The authors also argue that people scoring relatively low on IQ tests are less likely to be economically productive than people who obtain higher scores. The implication of the second claim seems to be that immigration to Germany from groups whose members have lower average scores on IQ tests should be restricted, because it is economically costly. The authors don’t explain how and to what extent these groups’ immigration should be restricted.

So, what should we make of the claim that recent asylum seekers have not contributed as much as expected to the German economy, possibly because of lower cognitive ability than that of the general German population? We genuinely don’t know if these claims are true: we don’t know if it’s true that asylum seekers haven’t helped German economic growth, and we don’t know if it’s true that their cognitive capacities are lower than those of the general German population. The authors have presented some evidence, but, as is the case for almost all academic articles, the evidence they have presented is not beyond dispute.

This level of scrutiny was unnecessary for such a simple study. It seems there is little point in submitting to this journal unless one has all the time in the world. We have also found that it rejected our papers. A pity. Yet another useless 'heterodox' journal that indirectly makes it nearly impossible to get work done.

Amusingly, they also solicited some egalitarians to reply. Naturally, their sentiment, here represented by Eric Turkheimer and former student Kathryn Paige Harden is that we need less science and more censorship:

One of the commentaries is by K. Paige Harden and E. Turkheimer, two respected psychologists who are familiar with the literature on IQ testing and group differences in IQ. Harden and Turkheimer are critical not only of the authors’ methodology and analysis, but also of our editorial decision to publish the paper, which they argue should not have passed peer review. 

We would like to clarify that the decision to publish the paper was made by the three editors (not by the editorial board, which is not involved in editorial decisions) on the basis of the comments of four reviewers and two data analysts. It’s possible that all these reviewers were mistaken and failed to detect the problems raised by Harden and Turkheimer, but as already explained, the paper passed a strict process of peer review (three of the four reviewers are also respected psychology professors), and we had no reason to reject the paper on the basis of the peer-review process. We could have rejected the paper only because of fear of criticism for publishing it, which obviously would be contrary to the mission of the journal.

I didn't bother reading their commentaries, but in case you want to, they are here:

Controversy Requires Competence: Comment on Rindermann et al. (2024), Eric Turkheimer , K. Paige Harden

Rindermann, Klauk, and Thompson (2024) purport to give evidence regarding the determinants of intelligence test scores among refugees who have immigrated to Germany from different countries of origin, and they speculate these intelligence test score differences have negative implications for future economic development in Germany. We describe critical flaws in their measurement, statistical analysis, and interpretation of individual- and country-level differences among the immigrant participants, particularly regarding the authors’ specious reference to “evolutionary ancestry.” We contrast their pseudoscientific approach with valid scientific methods. Human intelligence and human evolution are controversial areas of scientific inquiry that require the highest levels of scientific rigor and editorial discretion, which are absent here.

Read: authors are stupid, their science is fake, and we are morally righteous

Intelligence and Immigration, Christopher Heath Wellman

The relative intelligence of prospective migrants likely does little to move the needle on the central issue in the ethics of immigration, namely, whether states are morally entitled to forcibly exclude outsiders. Even so, I argue that varying levels of intelligence may be relevant to a number of theoretically interesting and practically pressing issues. In particular, such variations may in some cases (1) affect the number of refugees a country is obligated to accept, (2) be relevant to the advisability of encouraging refugees to resettle rather than attempting to help them where they are, and (3) have implications for relational egalitarians who are especially concerned with inequalities among fellow citizens.

On What Matters for Obligations to Refugees, Bradley Hillier-Smith

Rindermann et al.’s article concludes that certain refugees may have a lower IQ and as a result may not provide as significant an economic contribution to host states compared to the average citizen, and so may be an economic cost. This commentary first casts doubt on this conclusion. It then, and most importantly, demonstrates that even if this conclusion were true, it would be irrelevant insofar as it would have no moral or legal significance in mitigating or defeating obligations towards refugees. The commentary shows that any normative view that IQ and economic contributions can mitigate or defeat obligations to provide protection has unacceptable implications. The commentary then demonstrates that legal and moral obligations to refugees are in no part contingent on IQ and economic contributions and to suppose otherwise would simply represent a fundamental misunderstanding of the nature, grounds, and weight of obligations towards refugees. Hence, supposed IQ or economic contributions are entirely irrelevant to, and cannot undermine the strength of, refugees’ claims to protection nor states’ obligations to provide it.

Certainly, the JoCI bent over backwards to satisfy the egalitarians, and they are still not happy. Who is surprised? No one I hope. Their goal is not science, so they cannot be made happy with science. They can only be made happy with silence.

Source

Welcome to Edition 7.19 of the Rocket Report! Okay, we get it. We received more submissions from our readers on Australia's approval of a launch permit for Gilmour Space than we've received on any other news story in recent memory. Thank you for your submissions as global rocket activity continues apace. We'll cover Gilmour in more detail as they get closer to launch. There will be no Rocket Report next week as Eric and I join the rest of the Ars team for our 2024 Technicon in New York.

As always, we welcome reader submissions. 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.

Gilmour Space has a permit to fly. Gilmour Space Technologies has been granted a permit to launch its 82-foot-tall (25-meter) orbital rocket from a spaceport in Queensland, Australia. The space company, founded in 2012, had initially planned to lift off in March but was unable to do so without approval from the Australian Space Agency, the Australian Broadcasting Corporation reports. The government approved Gilmour's launch permit Monday, although the company is still weeks away from flying its three-stage Eris rocket.

A first for Australia ... Australia hosted a handful of satellite launches with US and British rockets from 1967 through 1971, but Gilmour's Eris rocket would become the first all-Australian launch vehicle to reach orbit. The Eris rocket is capable of delivering about 670 pounds (305 kilograms) of payload mass into a Sun-synchronous orbit. Eris will be powered by hybrid rocket engines burning a solid fuel mixed with a liquid oxidizer, making it unique among orbital-class rockets. Gilmour completed a wet dress rehearsal, or practice countdown, with the Eris rocket on the launch pad in Queensland in September. The launch permit becomes active after 30 days, or the first week of December. "We do think we've got a good chance of launching at the end of the 30-day period, and we're going to give it a red hot go," said Adam Gilmour, the company's co-founder and CEO. (submitted by Marzipan, mryall, ZygP, Ken the Bin, Spencer Willis, MarkW98, and EllPeaTea)

North Korea tests new missile. North Korea apparently completed a successful test of its most powerful intercontinental ballistic missile on October 31, lofting it nearly 4,800 miles (7,700 kilometers) into space before the projectile fell back to Earth, Ars reports. This solid-fueled, multi-stage missile, named the Hwasong-19, is a new tool in North Korea's increasingly sophisticated arsenal of weapons. It has enough range—perhaps as much as 9,320 miles (15,000 kilometers), according to Japan's government—to strike targets anywhere in the United States. It also happens to be one of the largest ICBMs in the world, rivaling the missiles fielded by the world's more established nuclear powers.

Quid pro quo? ... The Hwasong-19 missile test comes as North Korea deploys some 10,000 troops inside Russia to support the country's war against Ukraine. The budding partnership between Russia and North Korea has evolved for several years. Russian President Vladimir Putin has met with North Korean leader Kim Jong Un on multiple occasions, most recently in Pyongyang in June. This has fueled speculation about what Russia is offering North Korea in exchange for the troops deployed on Russian soil. US and South Korean officials have some thoughts. They said North Korea is likely to ask for technology transfers in diverse areas related to tactical nuclear weapons, ICBMs, and reconnaissance satellites.

Virgin Galactic is on the hunt for cash. Virgin Galactic is proposing to raise $300 million in additional capital to accelerate production of suborbital spaceplanes and a mothership aircraft the company says can fuel its long-term growth, Space News reports. The company, founded by billionaire Richard Branson, suspended operations of its VSS Unity suborbital spaceplane earlier this year. VSS Unity hit a monthly flight cadence carrying small groups of space tourists and researchers to the edge of space, but it just wasn't profitable. Now, Virgin Galactic is developing larger Delta-class spaceplanes it says will be easier and cheaper to turn around between flights.

All-in with Delta ... Michael Colglazier, Virgin Galactic's CEO, announced the company's appetite for fundraising in a quarterly earnings call with investment analysts Wednesday. He said manufacturing of components for Virgin Galactic's first two Delta-class ships, which the company says it can fund with existing cash, is proceeding on schedule at a factory in Arizona. Virgin Galactic previously said it would use revenue from paying passengers on its first two Delta-class ships to pay for development of future vehicles. Instead, Virgin Galactic now says it wants to raise money to speed up work on the third and fourth Delta-class vehicles, along with a second airplane mothership to carry the spaceplanes aloft before they release and fire into space. (submitted by Ken the Bin and EllPeaTea)

ESA breaks its silence on Themis. The European Space Agency has provided a rare update on the progress of its Themis reusable booster demonstrator project, European Spaceflight reports. ESA is developing the Themis test vehicle for atmospheric flights to fine-tune technologies for a future European reusable rocket capable of vertical takeoffs and vertical landings. Themis started out as a project led by CNES, the French space agency, in 2018. ESA member states signed up to help fund the project in 2019, and the agency awarded ArianeGroup a contract to move forward with Themis in 2020. At the time, the first low-altitude hop test was expected to take place in 2022.

Some slow progress ... Now, the first low-altitude hop is scheduled for 2025 from Esrange Space Centre in Sweden, a three-year delay. This week, ESA said engineers have completed testing of the Themis vehicle's main systems, and assembly of the demonstrator is underway in France. A single methane-fueled Prometheus engine, also developed by ArianeGroup, has been installed on the rocket. Teams are currently adding avionics, computers, electrical systems, and cable harnesses. Themis' stainless steel propellant tanks have been manufactured, tested, and cleaned and are now ready to be installed on the Themis demonstrator. Then, the rocket will travel by road from France to the test site in Sweden for its initial low-altitude hops. After those flights are complete, officials plan to add two more Prometheus engines to the rocket and ship it to French Guiana for high-altitude test flights. (submitted by Ken the Bin and EllPeaTea)

SpaceX will give the ISS a boost. A Cargo Dragon spacecraft docked to the International Space Station on Tuesday morning, less than a day after lifting off from Florida. As space missions go, this one is fairly routine, ferrying about 6,000 pounds (2,700 kilograms) of cargo and science experiments to the space station. One thing that's different about this mission is that it delivered to the station a tiny 2 lb (900 g) satellite named LignoSat, the first spacecraft made of wood, for later release outside the research complex. There is one more characteristic of this flight that may prove significant for NASA and the future of the space station, Ars reports. As early as Friday, NASA and SpaceX have scheduled a "reboost and attitude control demonstration," during which the Dragon spacecraft will use some of the thrusters at the base of the capsule. This is the first time the Dragon spacecraft will be used to move the space station.

Dragon's breath ... Dragon will fire a subset of its 16 Draco thrusters, each with about 90 pounds of thrust, for approximately 12.5 minutes to make a slight adjustment to the orbital trajectory of the roughly 450-ton space station. SpaceX and NASA engineers will analyze the results from the demonstration to determine if Dragon could be used for future space station reboost opportunities. The data will also inform the design of the US Deorbit Vehicle, which SpaceX is developing to perform the maneuvers required to bring the space station back to Earth for a controlled, destructive reentry in the early 2030s. For NASA, demonstrating Dragon's ability to move the space station will be another step toward breaking free of reliance on Russia, which is currently responsible for providing propulsion to maneuver the orbiting outpost. Northrop Grumman's Cygnus supply ship also previously demonstrated a reboost capability. (submitted by Ken the Bin and N35t0r)

Russia launches Soyuz in service of Iran. Russia launched a Soyuz rocket Monday carrying two satellites designed to monitor the space weather around Earth and 53 small satellites, including two Iranian ones, Reuters reports. The primary payloads aboard the Soyuz-2.1b rocket were two Ionosfera-M satellites to probe the ionosphere, an outer layer of the atmosphere near the edge of space. Solar activity can alter conditions in the ionosphere, impacting communications and navigation. The two Iranian satellites on this mission were named Kowsar and Hodhod. They will collect high-resolution reconnaissance imagery and support communications for Iran.

A distant third ... This was only the 13th orbital launch by Russia this year, trailing far behind the United States and China. We know of two more Soyuz flights planned for later this month, but no more, barring a surprise military launch (which is possible). The projected launch rate puts Russia on pace for its quietest year of launch activity since 1961, the year Yuri Gagarin became the first person to fly in space. A major reason for this decline in launches is the decisions of Western governments and companies to move their payloads off of Russian rockets after the invasion of Ukraine. For example, OneWeb stopped launching on Soyuz in 2022, and the European Space Agency suspended its partnership with Russia to launch Soyuz rockets from French Guiana. (submitted by Ken the Bin)

H3 deploys Japanese national security satellite. Japan launched a defense satellite Monday aimed at speedier military operations and communication on an H3 rocket and successfully placed it into orbit, the Associated Press reports. The Kirameki 3 satellite will use high-speed X-band communication to support Japan's defense ministry with information and data sharing, and command and control services. The satellite will serve Japanese land, air, and naval forces from its perch in geostationary orbit alongside two other Kirameki communications satellites.

Gaining trust ... The H3 is Japan's new flagship rocket, developed by Mitsubishi Heavy Industries (MHI) and funded by the Japan Aerospace Exploration Agency (JAXA). The launch of Kirameki 3 marked the third consecutive successful launch of the H3 rocket, following a debut flight in March 2023 that failed to reach orbit. This was the first time Japan's defense ministry put one of its satellites on the H3 rocket. The first two Kirameki satellites launched on a European Ariane 5 and a Japanese H-IIA rocket, which the H3 will replace. (submitted by Ken the Bin, tsunam, and EllPeaTea)

Rocket Lab enters the race for military contracts. Rocket Lab is aiming to chip away at SpaceX’s dominance in military space launch, confirming its bid to compete for Pentagon contracts with its new medium-lift rocket, Neutron, Space News reports. Last month, the Space Force released a request for proposals from launch companies seeking to join the military's roster of launch providers in the National Security Space Launch (NSSL) program. The Space Force will accept bids for launch providers to "on-ramp" to the NSSL Phase 3 Lane 1 contract, which doles out task orders to launch companies for individual missions. In order to win a task order, a launch provider must be on the Phase 3 Lane 1 contract. Currently, SpaceX, United Launch Alliance, and Blue Origin are the only rocket companies eligible. SpaceX won all of the first round of Lane 1 task orders last month.

Joining the club ... The Space Force is accepting additional risk for Lane 1 missions, which largely comprise repeat launches deploying a constellation of missile-tracking and data-relay satellites for the Space Development Agency. A separate class of heavy-lift missions, known as Lane 2, will require rockets to undergo a thorough certification by the Space Force to ensure their reliability. In order for a launch company to join the Lane 1 roster, the Space Force requires bidders to be ready for a first launch by December 2025. Peter Beck, Rocket Lab's founder and CEO, said he thinks the Neutron rocket will be ready for its first launch by then. Other new medium-lift rockets, such as Firefly Aerospace's MLV and Relativity's Terran-R, almost certainly won't be ready to launch by the end of next year, leaving Rocket Lab as the only company that will potentially join incumbents SpaceX, ULA, and Blue Origin. (submitted by Ken the Bin)

Next Starship flight is just around the corner. Less than a month has passed since the historic fifth flight of SpaceX's Starship, during which the company caught the booster with mechanical arms back at the launch pad in Texas. Now, another test flight could come as soon as November 18, Ars reports. The improbable but successful recovery of the Starship first stage with "chopsticks" last month, and the on-target splashdown of the Starship upper stage halfway around the world, allowed SpaceX to avoid an anomaly investigation by the Federal Aviation Administration. Thus, the company was able to press ahead on a sixth test flight if it flew a similar profile. And that's what SpaceX plans to do, albeit with some notable additions to the flight plan.

Around the edges … Perhaps the most significant change to the profile for Flight 6 will be an attempt to reignite a Raptor engine on Starship while it is in space. SpaceX tried to do this on a test flight in March but aborted the burn because the ship's rolling motion exceeded limits. A successful demonstration of a Raptor engine relight could pave the way for SpaceX to launch Starship into a higher stable orbit around Earth on future test flights. This is required for SpaceX to begin using Starship to launch Starlink Internet satellites and perform in-orbit refueling experiments with two ships docked together. (submitted by EllPeaTea)

China's version of Starship. China has updated the design of its next-generation heavy-lift rocket, the Long March 9, and it looks almost exactly like a clone of SpaceX's Starship rocket, Ars reports. The Long March 9 started out as a conventional-looking expendable rocket, then morphed into a launcher with a reusable first stage. Now, the rocket will have a reusable booster and upper stage. The booster will have 30 methane-fueled engines, similar to the number of engines on SpaceX's Super Heavy booster. The upper stage looks remarkably like Starship, with flaps in similar locations. China intends to fly this vehicle for the first time in 2033, nearly a decade from now.

A vehicle for the Moon … The reusable Long March 9 is intended to unlock robust lunar operations for China, similar to the way Starship, and to some extent Blue Origin's Blue Moon lander, promises to support sustained astronaut stays on the Moon's surface. China says it plans to land its astronauts on the Moon by 2030, initially using a more conventional architecture with an expendable rocket named the Long March 10, and a lander reminiscent of NASA's Apollo lunar lander. These will allow Chinese astronauts to remain on the Moon for a matter of days. With Long March 9, China could deliver massive loads of cargo and life support resources to sustain astronauts for much longer stays.

Ta-ta to the tripod. The large three-legged vertical test stand at SpaceX's engine test site in McGregor, Texas, is being decommissioned, NASA Spaceflight reports. Cranes have started removing propellant tanks from the test stand, nicknamed the tripod, towering above the Central Texas prairie. McGregor is home to SpaceX's propulsion test team and has 16 test cells to support firings of Merlin, Raptor, and Draco engines multiple times per day for the Falcon 9 rocket, Starship, and Dragon spacecraft.

Some history … The tripod might have been one of SpaceX's most important assets in the company's early years. It was built by Beal Aerospace for liquid-fueled rocket engine tests in the late 1990s. Beal Aerospace folded, and SpaceX took over the site in 2003. After some modifications, SpaceX installed the first qualification version of its Falcon 9 rocket on the tripod for a series of nine-engine test-firings leading up to the rocket's inaugural flight in 2010. SpaceX test-fired numerous new Falcon 9 boosters on the tripod before shipping them to launch sites in Florida or California. Most recently, the tripod was used for testing of Raptor engines destined to fly on Starship and the Super Heavy booster.

Next three launches

Nov. 9: Long March 2C | Unknown Payload | Jiuquan Satellite Launch Center, China | 03:40 UTC

Nov. 9: Falcon 9 | Starlink 9-10 | Vandenberg Space Force Base, California | 06:14 UTC

Nov. 10: Falcon 9 | Starlink 6-69 | Cape Canaveral Space Force Station, Florida | 21:28 UTC

Source

Hope you enjoyed this news post.

Thank you for appreciating my time and effort posting news every day for many years.

2023: Over 5,800 news posts | 2024 (till end of October): 4,832 news posts

RIP Matrix | Farewell my friend  

Clouds form when water vapor—an invisible gas in the atmosphere—sticks to tiny floating particles, such as dust, and turns into liquid water droplets or ice crystals. In a newly published study, we show that microplastic particles can have the same effects, producing ice crystals at temperatures 5° to 10° Celsius (9° to 18° Fahrenheit) warmer than droplets without microplastics.

 

This suggests that microplastics in the air may affect weather and climate by producing clouds in conditions where they would not form otherwise.

 

We are atmospheric chemists who study how different types of particles form ice when they come into contact with liquid water. This process, which occurs constantly in the atmosphere, is called nucleation.

 

Clouds in the atmosphere can be made up of liquid water droplets, ice particles, or a mixture of the two. In clouds in the mid- to upper atmosphere where temperatures are between 32° and minus 36° F (0° to minus 38° C), ice crystals normally form around mineral dust particles from dry soils or biological particles, such as pollen or bacteria.

 

Microplastics are less than 5 millimeters wide—about the size of a pencil eraser. Some are microscopic. Scientists have found them in Antarctic deep seas, the summit of Mount Everest, and fresh Antarctic snow. Because these fragments are so small, they can be easily transported in the air.

 

Why it matters

Ice in clouds has important effects on weather and climate because most precipitation typically starts as ice particles.

 

Many cloud tops in nontropical zones around the world extend high enough into the atmosphere that cold air causes some of their moisture to freeze. Then, once ice forms, it draws water vapor from the liquid droplets around it, and the crystals grow heavy enough to fall. If ice doesn’t develop, clouds tend to evaporate rather than causing rain or snowfall.

 

While children learn in grade school that water freezes at 32° F (0° C), that’s not always true. Without something to nucleate onto, such as dust particles, water can be supercooled to temperatures as low as minus 36° F (minus 38° C) before it freezes.

 

For freezing to occur at warmer temperatures, some kind of material that won’t dissolve in water needs to be present in the droplet. This particle provides a surface where the first ice crystal can form. If microplastics are present, they could cause ice crystals to form, potentially increasing rain or snowfall.

 

Clouds also affect weather and climate in several ways. They reflect incoming sunlight away from Earth’s surface, which has a cooling effect, and absorb some radiation that is emitted from Earth’s surface, which has a warming effect.

 

The amount of sunlight reflected depends on how much liquid water vs. ice a cloud contains. If microplastics increase the presence of ice particles in clouds compared with liquid water droplets, this shifting ratio could change clouds’ effect on Earth’s energy balance.

 

The Earth constantly receives energy from the Sun and reflects it back into space. Clouds have both warming and cooling effects in this process.

Credit: NOAA

How we did our work

To see whether microplastic fragments could serve as nuclei for water droplets, we used four of the most prevalent types of plastics in the atmosphere: low-density polyethylene, polypropylene, polyvinyl chloride, and polyethylene terephthalate. Each was tested both in a pristine state and after exposure to ultraviolet light, ozone, and acids. All of these are present in the atmosphere and could affect the composition of the microplastics.

 

We suspended the microplastics in small water droplets and slowly cooled the droplets to observe when they froze. We also analyzed the plastic fragments’ surfaces to determine their molecular structure, since ice nucleation could depend on the microplastics’ surface chemistry.

 

For most of the plastics we studied, 50 percent of the droplets were frozen by the time they cooled to minus 8° F (minus 22° C). These results parallel those from another recent study by Canadian scientists, who also found that some types of microplastics nucleate ice at warmer temperatures than droplets without microplastics.

 

Exposure to ultraviolet radiation, ozone, and acids tended to decrease ice nucleation activity on the particles. This suggests that ice nucleation is sensitive to small chemical changes on the surface of microplastic particles. However, these plastics still nucleated ice, so they could still affect the amount of ice in clouds.

What still isn’t known

To understand how microplastics affect weather and climate, we need to know their concentrations at the altitudes where clouds form. We also need to understand the concentration of microplastics compared with other particles that could nucleate ice, such as mineral dust and biological particles, to see whether microplastics are present at comparable levels. These measurements would allow us to model the impact of microplastics on cloud formation.

 

Plastic fragments come in many sizes and compositions. In future research, we plan to work with plastics that contain additives, such as plasticizers and colorants, as well as with smaller plastic particles.

 

Miriam Freedman is professor of chemistry, Penn State and Heidi Busse is a PhD student in chemistry, Penn State

 

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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From its halo-like orbit nearly a million miles from Earth, the James Webb Space Telescope is seeing farther than human eyes have ever seen.

In May, astronomers announced that Webb detected the most distant galaxy found so far, a fuzzy blob of red light that we see as it existed just 290 million years after the Big Bang. Light from this galaxy, several hundreds of millions of times the mass of the Sun, traveled more than 13 billion years until photons fell onto Webb's gold-coated mirror.

A few months later, in July, scientists released an image Webb captured of a planet circling a star slightly cooler than the Sun nearly 12 light-years from Earth. The alien world is several times the mass of Jupiter and the closest exoplanet to ever be directly imaged. One of Webb's science instruments has a coronagraph to blot out bright starlight, allowing the telescope to resolve the faint signature of a nearby planet and use spectroscopy to measure its chemical composition.

These are just a taste of the discoveries made by the $10 billion Webb telescope since it began science observations in 2022. Judging by astronomers' interest in using Webb, there are many more to come.

Breaking records

The Space Telescope Science Institute, which operates Webb on behalf of NASA and its international partners, said last week that it received 2,377 unique proposals from science teams seeking observing time on the observatory. The institute released a call for proposals earlier this year for the so-called "Cycle 4" series of observations with Webb.

This volume of proposals represents around 78,000 hours of observing time with Webb, nine times more than the telescope's available capacity for scientific observations in this cycle. The previous observing cycle had a similar "oversubscription rate" but had less overall observing time available to the science community.

This composite image of Arp 107, created with data from two of the James Webb Space Telescope’s infrared

instruments, reveals a wealth of information about the star formation taking place in these two galaxies and

how they collided hundreds of million years ago.

Credit: NASA, ESA, CSA, STScI

More than 600 scientists will review the proposals and select the most promising ones for time on Webb. The largest share of proposals would involve observing "high-redshift" galaxies among the first generation of galaxies that formed after the Big Bang. Galaxies this old and distant have their light stretched to longer wavelengths due to the expansion of the Universe. Research involving exoplanet atmospheres and stars and stellar populations were the second- and third-most popular science categories in this cycle.

Webb is a joint project of NASA, the European Space Agency, and the Canadian Space Agency. The observatory's 21.3-foot (6.5-meter) primary mirror and four infrared instruments, tuned to detect faint thermal energy coming from the cold blackness of space, make it a particularly useful general-purpose research platform. In this cycle, astronomers asked for time on Webb to look at targets within the Solar System, exoplanets in our stellar neighborhood, gas and dust suspended in the space between the stars, supermassive black holes, and nearby galaxies.

This is a remarkable range of scientific targets. Only the Hubble Space Telescope can match the breadth of Webb's scientific targets, but Webb's larger mirror allows it to observe objects 100 times fainter than Hubble can see.

This image of the gas-giant exoplanet Epsilon Indi Ab was taken with the coronagraph on the James Webb

Space Telescope’s Mid-Infrared Instrument A star symbol marks the location of the host star Epsilon Indi A,

whose light has been blocked by the coronagraph.

Credit: ESA/Webb, NASA, CSA, STScI, E. Matthews (Max Planck Institute for Astronomy)

In less than two-and-a-half years of science operations, Webb has only teased astronomers of its potential productivity. There is a high probability that Webb will see galaxies even older and more distant than the faint red beacon announced in May. There are thousands more known exoplanets for Webb to study, worlds of all sizes in our own Solar System, and unspeakable grandeur Webb will assuredly reveal in the years ahead.

It seems astronomers have no shortage of ideas about where to look. Maybe one day, new super heavy-lift rockets or advancements in in-space assembly will make it possible to deploy space telescopes even more sensitive than Webb. Until then, we can be thankful that Webb is performing well and has a good shot of far outliving its original five-year design life. Let's continue enjoying the show.

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In an experiment to test the durability of the material, the world's first wooden satellite, developed by Japanese researchers, has been sent to space. Created by researchers from Kyoto University in collaboration with Sumitomo Forestry, the wooden satellite is called "LingoSat," derived from the Latin word for wood.

The wooden satellite was transported to the International Space Station (ISS) on a SpaceX mission and later released in orbit 400 kilometers (250 miles) above the Earth to test how it behaves in space conditions. The LingoSat, a palm-sized satellite, was developed using timber wood.

Takao Doi, an astronaut who has flown on the Space Shuttle and studies human space activities at Kyoto University, said, "With timber, a material we can produce by ourselves, we will be able to build houses, live and work in space forever." He further added that since "Metal satellites might be banned in the future if we can prove our first wooden satellite works, we want to pitch it to Elon Musk’s SpaceX."

The milestone marks the first step in the 50-year plan of planting trees and building timber houses and spaces on the Moon and even on Mars. Discussing the feasibility of a wooden satellite, Kyoto University forest science professor Koji Murata said, "Early 1900s airplanes were made of wood. A wooden satellite should be feasible, too."

The two main reasons for sending a wooden satellite to space are, first, to test the durability of wood when put against the harsh conditions of space. If the results are positive, then researchers will get a nod to build wooden structures for space missions.

Second, a wooden satellite minimizes the environmental impact when it reaches the end of its life. Decommissioned satellites are required to re-enter the atmosphere to avoid becoming space debris. Metal satellites produce aluminum oxide when they re-enter the atmosphere, while wooden satellites just burn up and vanish. Given the large number of satellites orbiting the Earth, wooden satellites could significantly help reduce space debris.

Source: CNN

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A Cargo Dragon spacecraft docked to the International Space Station on Tuesday morning, less than a day after lifting off from Florida.

As space missions go, this one was fairly routine, ferrying about 6,000 pounds (2,700 kg) of cargo and science experiments to the space station. Over the course of nearly a dozen years, this was the 31st cargo supply mission that SpaceX has flown for NASA to the orbiting laboratory.

However, there is one characteristic of this flight that may prove significant for NASA and the future of the space station. As early as Friday, NASA and SpaceX have scheduled a "reboost and attitude control demonstration," during which the Dragon spacecraft will use some of the thrusters at the base of the capsule. This is the first time the Dragon spacecraft will be used to move the space station.

Dragon Dracos firing for a dozen minutes

"This is an important flight test objective for the mission as we continue to increase the capabilities of all the vehicles on ISS," said NASA's Bill Spetch, space station operations integration manager, during a teleconference with reporters in advance of the launch.

There are 16 Draco thrusters on the spacecraft, each with about 90 pounds of thrust. Some are near the top of the spacecraft or at its nose, and these are the primary means of raising the vehicle's orbit and conducting a de-orbit burn.

However, the vehicle also has Dracos near the backside of the capsule in what is known as the "service section." Typically, these thrusters are only used for maneuvering the spacecraft while in orbit, and they are the ones that will be employed during the upcoming test.

According to Jared Metter, the director of flight reliability for SpaceX, the burn will last 12.5 minutes.

"The data that we're going to collect from this reboost and attitude control demonstration will be very helpful in informing SpaceX analyses on how the system performs," he said during the teleconference. "And this data is going to lead to future capabilities, mainly the US Deorbit vehicle. We're excited to gather this data."

SpaceX is developing a significantly modified version of the Dragon spacecraft to deorbit the aging space station at the end of 2030. And indeed, this test will produce data on how much performance the Draco thrusters can provide in moving the much larger orbiting laboratory and ultimately guiding it to a safe landing in the Pacific Ocean.

More than just a deborbit capability

But there's another important element of this week's Draco demonstration. Notably, the primary means of maneuvering the International Space Station—both to periodically raise its altitude and avoid collisions with space debris—comes from the Russian segment of the station and the Progress spacecraft.

Since Russia's invasion of Ukraine in 2022, tensions between the United States and Russia have increased, and this has strained the relationship between NASA and its counterpart Roscosmos. Engineer to engineer, the working relationship remains good, but at higher diplomatic levels there are definitely concerns.

With regard to space station relations, the public war of words has quieted down since Dmitry Rogozin was sacked as director general of Roscosmos in July 2022. However, there remains the threat that an escalation in the war might necessitate a breaking of the bond between Russia and the United States in space, or Russian officials could decide the partnership is no longer working for them. Additionally, Russia has only committed to flying the station through 2028, two years fewer than NASA's goal of 2030.

Northrop Grumman and NASA have previously demonstrated the capability of the Cygnus cargo spacecraft to provide propulsive capabilities for the space station, but Dragon is more useful in that one or more of the vehicles is almost always attached to the space station. Therefore, should the Russian side of the space station go dark or even be separated from the Western side of the facility, NASA would have a fighting chance to keep the station flying on its own.

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Following a number of Freedom of Information requests to the Met Office and diligent field work visiting individuals stations, Sanders has discovered that 103 stations out of 302 sites supplying temperature averages do not exist. “How would any reasonable observer know that the data was not real and simply ‘made up’ by a Government agency,” asks Sanders. He calls for an “open declaration” of likely inaccuracy of existing published data, “to avoid other institutions and researchers using unreliable data and reaching erroneous conclusions”.

In his home county of Kent, Sanders charges that four of the eight sites identified by the Met Office, namely Dungeness, Folkestone, Dover and Gillingham – which all produce rolling temperature averages to the second decimal place of a degree – are “fiction”. Sanders notes that there has been no weather station at Dungeness since 1986. The Daily Sceptic is able to confirm that none of the four stations appear in the list of Met sites with a classification from the World Meteorological Organisation (WMO). The Met Office directs online inquiries about Dover to the ”nearest climate station” at Dover Harbour (Beach) and provides a full set of rolling 30-year averages.

According to Met Office co-ordinates, the site is on Dover beach as the Google Earth photo below shows. It seems unlikely that any scientific organisation would site a temperature monitoring station that is likely to be submerged on a regular basis. Who is running this station on the beach, have accurate records been kept for 30 years and why is it not listed under the 380 sites that are given a WMO rating?

Of the 302 sites quoted, Sanders notes that the Met Office “declined to advise me” exactly how or where the alleged ‘data’ were derived for these 103 non-existent sites.

The practice of ‘inventing’ temperature data from non-existent stations is a controversial issue in the United States where the local weather service NOAA has been charged with fabricating data for more than 30% of its reporting sites. Data are retrieved from surrounding stations and the resulting averages are given an ‘E’ for estimate. “The addition of the ghost station data means NOAA’s monthly and yearly reports are not representative of reality,” says meteorologist Anthony Watts. “If this kind of process were used in a court of law, then the evidence would be thrown out as being polluted,” he added.

In its historical data section, the Met Office lists a number of sites with long records of temperature data. Lowestoft provides records going back to 1914 but it closed in 2010. Since that date the figures have been complied on an estimated basis. The stations at Nairn Druim, Paisley and Newton Rigg are similarly closed but still reporting estimated monthly data. “Why would any scientific organisation feel the need to publish what can only be described as fiction?” asks Sanders. “No scientific purpose can possibly be served by fabrication,” he suggests.

It is possible that the Met Office has a reasonable scientific explanations for the way it collects temperature data. Temperature calculation is an imprecise science but concerns have mounted because the data are being used for overtly political purposes to promote the Net Zero fantasy. Alarmists claim that very small temperature rises can make a large climatic difference. To whip up global fear, temperature figures supposedly compiled with an accuracy to one hundredth of a degree centigrade are quoted from sources such as the Met Office and NOAA. To date, the Met Office has been silent over the gathering storm surrounding its figures and the organisation refuses to return the calls of the Daily Sceptic.

Sanders refers to another large temperature measurement problem at the Met Office surrounding the WMO classification of its sites. Almost eight in 10 sites are rated in junk classes 4 and 5 with possible “uncertainties” of 2°C and 5°C respectively. This means, notes Sanders, that they are not suitable for climate data reporting purposes according to international standards which the Met Office was party to establishing. Only 52 Met Office stations, or a paltry 13.7%, are in Class 1 and 2 with no suggested margin of error. Actually, mark that down by at least one. In his travels, Sanders pointed out the possible heat corruptions at Class 1 Hastings and this site has now been dropped to Class 4. The Met Office is said to have confirmed that the default classification for stations is set at Class 1, “unless manually adjusted”.

The Daily Sceptic has investigated the poor siting of many Met Office stations with obvious heat corruptions making a mockery of attempts to measure the naturally occurring air temperature. Sanders lists the problems of many of these unsuitable sites including those placed in walled kitchen gardens and botanical gardens specifically designed to produce artificially increased temperatures and microclimates. Other unsuitable sites include in or near car parks, airports, domestic gardens, sewage and water treatment plants, electricity sub-stations and solar farms.

Sanders has an interesting take on the recent closure of many rural temperature measuring sites. In 1974 there were 32 operational sites in Kent, but this has now fallen to seven. The switch to new electrically-operated platinum resistance thermometers required a reliable electricity supply and data communication. Many rural sites were closed down because such facilities were not available in the early days of automation. But by eliminating cooler recording sites from the overall data record, this left predominantly urbanised sites to cause an unrepresentative temperature uplift from the slewed averages. “Statistical sleight of hand (however inadvertent it may have been) produced inaccurate historic misrepresentation,” observes Sanders.

In his open letter to Peter Kyle MP, Sanders states that he has demonstrated with hard evidence that the Met Office is “clearly fabricating” data. In addition, it is failing to meet high standards of scientific integrity and is not producing reliable or accurate data for climate reporting purposes from a network of poorly sited and inadequately maintained locations. Peter Kyle is the Minister responsible for the Met Office and has yet to respond to Sanders’s allegations.

Ray Sanders has done an excellent research job in providing new and highly relevant details in what is becoming a significant scientific scandal. To date, despite repeated requests, the Met Office has refused to make any comment and defend its own temperature measurements and calculations. While the silence in Government, Parliament and the Met Office, aided by a total lack of interest in the mainstream media, is maintained, it can only be assumed that the interests of the Net Zero promotion override any concerns about the underlying scientific data.

Chris Morrison is the Daily Sceptic’s Environment Editor.

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Striking workers at embattled plane maker Boeing voted Monday to accept the company’s most recent offer, ending the costliest strike in the United States in more than 25 years.

The International Association of Machinists (IAM) said rank-and-file members voted by 59% to approve the deal. IAM members had voted almost unanimously against Boeing’s first offer on the eve of the start of the strike, and then 64% voted against the second offer less than two weeks ago, extending the strike.

“I’m proud of our members. It is a win,” said Jon Holden, president of the largest IAM local at Boeing and the union’s chief negotiator. “They achieved a lot, and we’re ready to move forward.”

Asked what prompted a positive vote this time after two previous rejections, Holden told reporters: “Members are ready, ready to come back. I look forward to getting them back to work.”

Boeing said it was pleased with the outcome.

“While the past few months have been difficult for all of us, we are all part of the same team,” CEO Kelly Ortberg said in a statement. “We will only move forward by listening and working together. There is much work ahead to return to the excellence that made Boeing an iconic company.”

The 33,000 union members, who have been on strike since September 13, will start returning to work Wednesday.

The deal calls for an immediate raise of 13% and raises of 9% for each of the next two years, and then another 7% in the fourth and final year of the contract. Taken together, members will receive a pay raise that exceeds 43%.

Workers also get a ratification bonus of $12,000, part of which they can contribute to 401(k) retirement accounts. But the deal did not restore the traditional pension plan they lost in 2014 from their previous labor deal.

Workers’ continued anger at the loss of that pension plan was seen as a major factor in the rejection of Boeing’s (BA) previous two offers and had raised uncertainty about the outcome of Monday’s vote.

Pension problem

Holden acknowledged the pension was likely a major issue for many of the 41% who voted against the deal.

“Fifty-nine percent is a lot, but there are definitely those who were not happy with the agreement,” he said. “Many of the members were fighting to get the pensions back. It’s a righteous fight.”

Companies, both unionized and nonunion, have generally moved away from a traditional pension plan, known as defined benefit plans, in recent decades. Such plans generally pay retirees a set amount every month no matter how long they live, or how well pension fund assets perform.

Such plans place the risk with the companies. For that reason, defined benefit plans are only available to about 8% of US workers in the private sector today, according to data from the Employee Benefit Research Institute. That compares to 39% in 1980.

Boeing employees have what’s known as a defined contribution plan, such as 401(k) plans, where the company’s obligations end after it contributes to the individual workers’ account. Boeing agreed to increase the contributions it was making to those accounts, but refused to go back to the defined benefit plan as the union and many members had demanded.

“Our members deserve pensions just like every worker deserves a safe, fair retirement in the future,” Holden said Monday following the vote. “They weren’t wrong in feeling the way they did. I agree with them. We just couldn’t get the pension out of this company. We’ll continue working on that issue.”

Leadership support

Union leadership had urged members to accept the latest offer, even though it was not significantly different from the one they rejected on October 23. The union had urged members “to lock in these gains and confidently declare victory,” and warned members that another rejection could “risk a regressive or lesser offer in the future.”

The strikers have lost more than $600 million in combined wages but the cost to Boeing has been significantly greater, according to estimates from Anderson Economic Group, a Michigan-based research firm, which puts Boeing’s losses through the end of last week at $6.5 billion. Overall, the cost to the US economy has topped $11.5 billion.

Those losses come on top of the nearly $40 billion in core operating losses that Boeing has reported since two fatal crashes led to a 20-month grounding of its best-selling jet, the 737 Max, in 2019 and 2020. The company has already warned that its losses would continue through at least the end of 2025 no matter how quickly the strike ended.

But despite the deep financial problems, Boeing had little choice but to settle the strike and get the workers back on the job. The strike has choked off its major source of revenue, since it gets most of the cash from the sale of commercial jets at the time it is delivered to airlines. Deliveries of all 737 Max planes as well as freighter models have been halted by the strike.

The wages that Boeing pays to its workers make up far less than 10% of its overall cost of producing a plane, with most of the cost going into raw materials and purchases from suppliers who produce everything from avionics to the fuselage of the planes themselves.

Boeing’s economic impact

Despite its problems, Boeing is still a major contributor to the US economy, as it is the largest American exporter.

The strike has caused problems and layoffs at many of Boeing’s 10,000 suppliers, which are spread across all 50 states. Boeing estimates its own annual contribution to the US economy at $79 billion, supporting 1.6 million jobs directly and indirectly. It has 150,000 US employees, including the strikers.

The Labor Department’s latest monthly employment report showed that 44,000 jobs were impacted in October, counting not just the 33,000 strikers, but also workers at Boeing and its suppliers who aren’t on strike but have been temporarily laid off as the strike halts commercial aircraft manufacturing at the aviation giant entirely.

There have been short-term problems for airlines, too. While they’ve been able to continue to fly the Boeing planes already in their fleets, promised deliveries of new jets have come to a halt. And that delay comes on top of ongoing delays, due to questions about the quality and safety of Boeing jets.

Those problems were worsened by a January incident in which a door plug blew out of an Alaska Airlines jet soon after takeoff, leaving a gaping hole in its fuselage. Investigators discovered Boeing had delivered the plane without the four bolts needed to keep the door plug in place.

Ending the strike is important for Boeing’s Ortberg, who started in the job just five weeks before the strike began. He has said he wants to “reset” the company’s relationship with the union.

This story has been updated with additional reporting and context.

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On Friday, TriStar Pictures released Here, a $50 million Robert Zemeckis-directed film that used real time generative AI face transformation techniques to portray actors Tom Hanks and Robin Wright across a 60-year span, marking one of Hollywood's first full-length features built around AI-powered visual effects.

The film adapts a 2014 graphic novel set primarily in a New Jersey living room across multiple time periods. Rather than cast different actors for various ages, the production used AI to modify Hanks' and Wright's appearances throughout.

The de-aging technology comes from Metaphysic, a visual effects company that creates real time face swapping and aging effects. During filming, the crew watched two monitors simultaneously: one showing the actors' actual appearances and another displaying them at whatever age the scene required.

Here - Official Trailer (HD)

Metaphysic developed the facial modification system by training custom machine-learning models on frames of Hanks' and Wright's previous films. This included a large dataset of facial movements, skin textures, and appearances under varied lighting conditions and camera angles. The resulting models can generate instant face transformations without the months of manual post-production work traditional CGI requires.

Unlike previous aging effects that relied on frame-by-frame manipulation, Metaphysic's approach generates transformations instantly by analyzing facial landmarks and mapping them to trained age variations.

"You couldn't have made this movie three years ago," Zemeckis told The New York Times in a detailed feature about the film. Traditional visual effects for this level of face modification would reportedly require hundreds of artists and a substantially larger budget closer to standard Marvel movie costs.

This isn't the first film that has used AI techniques to de-age actors. ILM's approach to de-aging Harrison Ford in 2023's Indiana Jones and the Dial of Destiny used a proprietary system called Flux with infrared cameras to capture facial data during filming, then old images of Ford to de-age him in post-production. By contrast, Metaphysic's AI models process transformations without additional hardware and show results during filming.

Rumbles in the unions

The film Here arrives as major studios explore AI applications beyond just visual effects. Companies like Runway have been developing text-to-video generation tools, while others create AI systems like Callaia for script analysis and pre-production planning. However, recent guild contracts place strict limits on AI's use in creative processes like scriptwriting.

Meanwhile, as we saw with the SAG-AFTRA union strike last year, Hollywood studios and unions continue to hotly debate AI's role in filmmaking. While the Screen Actors Guild and Writers Guild secured some AI limitations in recent contracts, many industry veterans see the technology as inevitable. "Everyone's nervous," Susan Sprung, CEO of the Producers Guild of America, told The New York Times. "And yet no one's quite sure what to be nervous about."

Even so, The New York Times says that Metaphysic's technology has already found use in two other 2024 releases. Furiosa: A Mad Max Saga employed it to re-create deceased actor Richard Carter's character, while Alien: Romulus brought back Ian Holm's android character from the 1979 original. Both implementations required estate approval under new California legislation governing AI recreations of performers, often called deepfakes.

Not everyone is pleased with how AI technology is unfolding in film. Robert Downey Jr. recently said in an interview that he would instruct his estate to sue anyone attempting to digitally bring him back from the dead for another film appearance. But even with controversies, Hollywood still seems to find a way to make death-defying (and age-defying) visual feats take place on screen—especially if there is enough money involved.

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The hull of Henry VIII's favorite warship, the Mary Rose, and many thousands of recovered artifacts are

housed in the Mary Rose Museum in Portsmouth, England.

Credit: Johnny Black

Henry VIII's favorite warship, the Mary Rose, sank in battle in 1545. Archaeologists successfully raised the ship in 1982, along with thousands of articles and the remains of 179 crew members—all remarkably well preserved thanks to the anaerobic conditions of the shipwreck created by the layers of soft sediment that accumulated over the wreckage.

A new analysis of some of the recovered bones reveals that whether someone is right- or left-handed could affect how their collarbone chemistry changes as they age, according to a new paper published in the journal PLoS ONE. This has implications for our understanding not just of aging, but of bone conditions like fracture risk and osteoarthritis.

As previously reported, the earliest-known reference to the Mary Rose appears in a January 29, 1510, letter ordering the construction of two new ships for the young king: the Mary Rose and her sister ship, dubbed the Peter Pomegranate. Once the newly built ship had launched, Henry VIII wasted no time defying his advisers and declaring war on France in 1512. The Mary Rose served the monarch well through that conflict, as well as during a second war with the French that ran roughly from 1522 through 1525, after which it underwent a substantial overhaul.

Alas, the ship's luck ran out during yet another outbreak of war with France. During the Battle of the Solent, French ships tried to land troops on English soil in the straits just north of the Isle of Wight. On July 19, 1545, contemporary accounts report that the Mary Rose suddenly heeled over to the starboard side—perhaps due to a sudden shift in the wind—and the crew couldn't correct the imbalance. Because the gunports were open, water rushed in and sank the Mary Rose. The exact cause of the sinking is still a matter of heated debate, but it was likely a convergence of factors, including overloading, crew error, and that sudden gust of wind.

Conservationists have worked tirelessly to preserve the ship's remains ever since it was raised from its watery resting place. For many years after it was recovered, the hull was housed in dry dock as conservationists worked to preserve the structure. That required keeping the entire thing saturated with water initially. Later, they applied a polyethylene glycol solution to add mechanical stability. The ship's remains are now displayed in the official Mary Rose Museum, built right over the original dry dock in Portsmouth.

The Mary Rose as depicted in the Anthony Roll, a record of ships of the English Tudor navy of 1540.

Credit: Public domain

In 2020, a high-energy X-ray analysis of chain-mail links salvaged from the wreckage by a team of British scientists revealed that the material composition of the armor is similar to modern brass alloys. There were also traces of lead and gold whose origin has not been decisively determined. Many of those traces possibly came later; during World War II, the Portsmouth Dockyard was the target of heavy bombing, which deposited lead, mercury, and cadmium, for instance, into the Solent waters.

In 2021, conservators turned their attention to analyzing the wood hull of the Mary Rose. There is evidence from prior studies of metal sulfides from anaerobic bacteria and corroded iron fixtures. Under atmospheric conditions, those sulfides can oxidize into acids as well, further adding to the hull's deterioration. The 2021 analysis revealed that the wood hull is now riddled with zinc sulfide nanoparticles. In addition, the study found significant polymer deposits—evidence that the polyethylene glycol solution applied to the hull for preservation purposes is now starting to break down and form acids, which also threaten the continued mechanical integrity of the hull.

For this latest analysis, researchers at Lancaster University joined forces with the Mary Rose Museum to examine the bones of some of the human remains using a non-invasive technique called Raman spectroscopy, in which a laser is used to excite molecules in a given sample. The changes in vibration give rise to a distinct biochemical fingerprint, enabling scientists to identify specific organic and inorganic substances. Raman spectroscopy has previously been used to examine the lower leg bones of some of the Mary Rose crew members for evidence of bone disease.

Dem collarbones

A schematic to illustrate the approximate location from which the measurements were taken; an example right clavicle from each age group.

Credit: S.I. Shalnkland et al., PLOS ONE 2024

Most of the recovered human remains were jumbled up, but over the years, preservationists have partially reconstructed some 98 individuals, all men between 10 and 40 years of age. The new study focused on 12 clavicle (collar) bones, which links the upper limb to the torso and is one of the most commonly fractured bones. Per the authors, it's one of the first bones to start ossifying in utero, but the last to fully fuse, usually between 22 and 25 years old.

That was a boon for determining the age of the Mary Rose crew members, but the authors thought differences in bone mineral and protein chemistry could also shed light on bone changes related not just to aging, but also to lifestyle or disease, and even whether a crewman was right- or left-handed had an impact on those changes. They specifically looked at changes in phosphate, carbonate, and amine (the foundation of collagen), all major components of bone.

The results: mineral content of the bones of all 12 men increased with age, while the protein content decreased. Those changes were more significant in right clavicles rather than left ones, an intriguing result suggesting a preference for right-handed crew members. The authors note that this might be because, at the time, being left-handed was often associated with witchcraft. Perhaps those right-handed crew members put more stress on their right side while performing their duties, and this, in turn, asymmetrically altered their clavicle chemistry.

“Having grown up fascinated by the Mary Rose, it has been amazing to have the opportunity to work with these remains," said co-author Sheona Shankland of Lancaster University. "The preservation of the bones and the non-destructive nature of the technique allows us to learn more about the lives of these sailors, but also furthers our understanding of the human skeleton, relevant to the modern world.”

PLoS ONE, 2024. DOI: 10.1371/journal.pone.0311717  (About DOIs).

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The Reuters report says it's based on four sources who have knowledge of an arrangement between the two companies, which included a hefty discount on 3nm wafers. Reuters says TSMC was offering Intel a steep 40% discount on the the wafers, which it says cost Intel $23,000 each. That deal was being floated until Gelsinger made disparaging comments about Taiwan in May 2021, when he said, "You don't want all of your eggs in the basket of a Taiwan fab." He then doubled down in December of that year by stating, "Taiwan is not a stable place," seemingly referring to the geopolitical tensions with China as he also contrasted TSMC with Samsung in Korea and Intel in the US.

Those comments were allegedly enough for TSMC to cancel the deal, which then required Intel to pay full price for each wafer. It's currently using TSMC's 3nm process for both its Core Ultra 200 series desktop and upcoming 200H-series mobile CPUs, and its Lunar Lake Core Ultra 200V CPUs, so TSMC is likely making a lot of chips for Intel right now and will continue to do so into 2025 as well. It's the first time Intel has had all of its client-focused chips made by one of its competitors in the foundry business. By losing the previously offered deal, Intel has to pay more for each wafer, which cuts deeply into its margins.

TSMC founder Morris Chang sort of responded to Gelsinger's comments in 2021, calling him "very discourteous," but his comments were in regards to a meeting he had with him around the same time frame. He also described Gelsinger as "a bit cocky," saying he would deal with him the same way Gelsinger dealt with TSMC, which sounds like a reference to a bare-knuckles business arrangement. He added that he was initially impressed by Gelsinger's intelligence when he was the CEO of VMWare, but that he said his goal of building a complete semiconductor supply chain in the United States would not be possible.

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The Dallas-based company filed for Chapter 11 bankruptcy protection in a Texas federal court.

TGI Fridays Executive Chairman Rohit Manocha in a statement said the “primary driver of our financial challenges resulted from COVID-19 and our capital structure.”

Sit-down chain restaurants have more broadly faced challenges in recent years as diners choose to get food delivered or visit upscale fast food chains like Chipotle and Shake Shack.

A US bankruptcy judge in September approved a reorganization plan for seafood chain Red Lobster after years of mounting losses and dwindling customers.

Founded in 1965, the popularity of TGI Fridays peaked in 2008 with 601 restaurants in the US and a $2 billion business, according to Kevin Schimpf, director of industry research at Technomic.

Its sales in the US were $728 million in 2023, down 15% from the prior year, according to Technomic.

It now counts 163 restaurants in the US, down from 269 last year. It closed 36 in January and dozens more in the past week.

TGI Fridays Inc. said it only owns and operates 39 restaurants in the US, which is just a fraction of the 461 TGI Friday-branded restaurants around the world.

A separate entity, TGI Fridays Franchisor, owns the intellectual property and has franchised the brand to 56 independent owners in 41 countries.

Those remain open.

Staff from Boeing’s DEI office will be combined with another human resources team focused on talent and employee experience, according to people familiar with the matter. Sara Liang Bowen, a Boeing vice president who led the now-defunct department, left the company on Thursday.

“The team achieved so much — sometimes imperfectly, never easily — and dreamed of doing much more still,” Bowen wrote in a farewell post on LinkedIn. 

Boeing’s new Chief Executive Officer Kelly Ortberg is streamlining the planemaker’s operations and trimming its executive ranks as part of a broader 10% reduction in headcount. The shift also comes as large US companies face increasing pressure from conservative activists to dismantle or downplay their efforts on diversity, equity and inclusion. 

While Boeing’s workforce has traditionally skewed White and male, the company stepped up its efforts to recruit more Black employees and people from other minority groups under former CEO Dave Calhoun, who stepped down in early August.

‘Remains Committed’

Anti-DEI activist Robby Starbuck, who claims credit for convincing Toyota Motor Corp. and Harley-Davidson Inc. to scale back DEI, said he had reached out to Ortberg and board chair Steve Mollenkopf by e-mail earlier this month to alert them he was considering an online campaign against their diversity programs.  

“Boeing remains committed to recruiting and retaining top talent and creating an inclusive work environment where every teammate around the world can perform at their best while supporting the company’s mission,” the planemaker said in a statement. 

The company added that it prohibits discriminatory hiring practices and maintains “a merit-based performance system with procedures aimed at encouraging an equality of opportunity, not of outcomes.”

The dismantling of Boeing’s DEI department throws into question the future of its existing programs to promote more diversity among its workforce.

Boeing had promised to increase opportunities for under-represented workers, including Black employees, in the aftermath of George Floyd’s death in 2020. As part of that effort, the company pledged to increase overall Black employment by 20% by 2025. Boeing was already closing in on that goal last year, as Black employment rose to 7.5% in 2023 — a 17% increase, according to data reported to the US federal government.

Under Pressure

Asked by a Texas judge to explain its DEI policy, Boeing reiterated its goals on diversity and inclusion, in an Oct. 25 filing, and said it doesn’t use racial quotas in hiring or promotion decisions. 

“An inclusive culture fosters a workplace where employees feel free to speak up and raise concerns — including concerns related to quality and safety — without fear of retaliation,” Boeing told the court. 

Boeing has been under pressure for its quality and safety practices following two fatal jet crashes involving its workhorse 737 Max model, and a door failure on an Alaska Air flight in January.

The company has been specifically targeted on social media by billionaire Elon Musk and other conservative activists who blame some of its problems with aircraft quality on its decision to add diversity goals to its 2022 bonus targets. Boeing refocused its incentive plan on quality and safety earlier this year.

Ortberg has vowed to streamline operations and return focus to Boeing’s core planemaking and defense businesses. With the company on pace to burn through $14 billion in cash this year, and facing a further drag on its finances because of a seven-week labor strike, Ortberg is now trying to slash 10% of its workforce in an effort to turn around the troubled aerospace and defense manufacturer.

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