"It's ridiculous just how virulent some of these bacteria get over time," says Dwayne Roach, assistant professor of bacteriophages, infectious disease and immunology at San Diego State University.

But now CNN says doctors are fighting multi-drug-resistant superbugs with "nature's oldest predators — tiny tripod-looking viruses called phages designed to find, attack and gobble up bacteria." The microscopic creatures have saved the lives of patients dying from superbug infections and are being used in clinical trials as a potential solution to the growing problem of antibiotic resistance...

In labs around the country, phage scientists are taking research and discovery to the next level... [Yale scientists] are busy mapping which phages and antibiotics are most symbiotic in the fight against a pathogen. Roach's San Diego State lab is investigating the body's immune response to phages while developing new phage purification techniques to prepare samples for intravenous use in patients. Currently, clinical trials are underway to test the effectiveness of phages against intractable urinary tract infections, chronic constipation, joint infections, diabetic foot ulcers, tonsillitis and the persistent, reoccurring infections that occur in patients with cystic fibrosis. The chronic infections common in cystic fibrosis are typically due to various strains of drug-resistant Pseudomonas aeruginosa — the same pathogen responsible for Horton's ear infection and the artificial tears outbreak.

A number of labs are developing libraries of phages, stockpiled with strains found in nature that are known to be effective against a particular pathogen. In Texas, a new facility is taking that a step further — speeding up evolution by creating phages in the lab. "Rather than just sourcing new phages from the environment, we have a bioreactor that in real time creates billions upon billions of phages," said Anthony Maresso, associate professor at Baylor College of Medicine in Houston. "Most of those phages won't be active against the drug-resistant bacteria, but at some point there will be a rare variant that has been trained, so to speak, to attack the resistant bacteria, and we'll add that to our arsenal," Maresso said. "It's a next-generation approach on phage libraries." Maresso's lab published a study last year on the treatment of 12 patients with phages customized to each patient's unique bacterial profile. It was a qualified success: The antibiotic-resistant bacteria in five patients were eradicated, while several more patients showed improvements.

"There's a lot of approaches right now that are happening in parallel," Roach said. "Do we engineer phages? Do we make a phage cocktail, and then how big is the cocktail? Is it two phages or 12 phages? Should phages be inhaled, applied topically or injected intravenously? There's a lot of work underway on exactly how to best do this...." Genetically engineering phages would allow scientists to target each person's unique mix of antibiotic-resistant pathogens instead of searching sewage, bogs, ponds, the bilge of boats and other prime breeding grounds for bacteria to find just the right phage for the job.

Along with phage libraries, genetic engineering is also a key to churning out phages in mass, to distribute on a wider scale. In Russia and the country of Georgia, where phage therapy has been used for decades, patients can buy phage cocktails off the shelf in pharmacies.

"A familiar shadow looms in a fresh image of the heart of the nearby galaxy M87," reports Science magazine.

"It confirms that the galaxy harbors a gravitational sinkhole so powerful that light cannot escape, one generated by a black hole 6.5 billion times the mass of the Sun." But compared with a previous image from the network of radio dishes called the Event Horizon Telescope (EHT), the new one reveals a subtle shift in the bright ring surrounding the shadow, which could provide clues to how gases churn around the black hole. "We can see that shift now," says team member Sera Markoff of the University of Amsterdam. "We can start to use that." The new detail has also whetted astronomers' desire for a proposed expansion of the EHT, which would deliver even sharper images of distant black holes.

The new picture, published this week in Astronomy & Astrophysics, comes from data collected 1 year after the observing campaign that led to the first-ever picture of a black hole, revealed in 2019 and named as Science's Breakthrough of the Year. The dark center of the image is the same size as in the original image, confirming that the image depicts physical reality and is not an artifact. "It tells us it wasn't a fluke," says Martin Hardcastle, an astrophysicist at the University of Hertfordshire who was not involved in the study. The black hole's mass would not have grown appreciably in 1 year, so the comparison also supports the idea that a black hole's size is determined by its mass alone. In the new image, however, the brightest part of a ring surrounding the black hole has shifted counterclockwise by about 30 degrees.

That could be because of random churning in the disk of material that swirls around the black hole's equator. It could also be associated with fluctuations in one of the jets launched from the black hole's poles — a sign that the jet isn't aligned with the black hole's spin axis, but precesses around it like a wobbling top. That would be "kind of exciting," Markoff says. "The only way to know is to keep taking pictures...."

[T]he team wants to add more telescopes to the network, which would further sharpen its images and enable it to see black holes in more distant galaxies.
Thanks to Slashdot reader sciencehabit for sharing the news.

"The discovery of a second ultra-large structure in the remote universe has further challenged some of the basic assumptions about cosmology," writes SciTechDaily: The Big Ring on the Sky is 9.2 billion light-years from Earth. It has a diameter of about 1.3 billion light-years, and a circumference of about four billion light-years. If we could step outside and see it directly, the diameter of the Big Ring would need about 15 full Moons to cover it.

It is the second ultra-large structure discovered by University of Central Lancashire (UCLan) PhD student Alexia Lopez who, two years ago, also discovered the Giant Arc on the Sky. Remarkably, the Big Ring and the Giant Arc, which is 3.3 billion light-years across, are in the same cosmological neighborhood — they are seen at the same distance, at the same cosmic time, and are only 12 degrees apart on the sky. Alexia said: "Neither of these two ultra-large structures is easy to explain in our current understanding of the universe. And their ultra-large sizes, distinctive shapes, and cosmological proximity must surely be telling us something important — but what exactly?

"One possibility is that the Big Ring could be related to Baryonic Acoustic Oscillations (BAOs). BAOs arise from oscillations in the early universe and today should appear, statistically at least, as spherical shells in the arrangement of galaxies. However, detailed analysis of the Big Ring revealed it is not really compatible with the BAO explanation: the Big Ring is too large and is not spherical." Other explanations might be needed, explanations that depart from what is generally considered to be the standard understanding in cosmology...

And if the Big Ring and the Giant Arc together form a still larger structure then the challenge to the Cosmological Principle becomes even more compelling... Alexia said, "From current cosmological theories we didn't think structures on this scale were possible. "
Possible explanations include a Conformal Cyclic Cosmology, or the effect of cosmic strings passing through...

Thanks to long-time Slashdot reader schwit1 for sharing the article.

The Hubble Space Telescope's discovery of GN-z11 in 2016 marked it as the most distant galaxy known at that time, notable for its unexpected luminosity despite its ancient formation just 400 million years after the Big Bang. Now, in a paper published in Nature, astrophysicist Roberto Maiolino proposes that this brightness could be due to a supermassive black hole, challenging current understanding of early black hole formation and growth. NPR reports: This wasn't just any black hole. First -- assuming that the black hole started out small -- it could be devouring matter at a ferocious rate. And it would have needed to do so to reach its massive size. "This black hole is essentially eating the [equivalent of] an entire Sun every five years," says Maiolino. "It's actually much higher than we thought could be feasible for these black holes." Hence the word "vigorous" in the paper's title. Second, the black hole is 1.6 million times the mass of our Sun, and it was in place just 400 million years after the dawn of the universe. "It is essentially not possible to grow such a massive black hole so fast so early in the universe," Maiolino says. "Essentially, there is not enough time according to classical theories. So one has to invoke alternative scenarios."

Here's scenario one -- rather than starting out small, perhaps supermassive black holes in the early universe were simply born big due to the collapse of vast clouds of primordial gas. Scenario two is that maybe early stars collapsed to form a sea of smaller black holes, which could have then merged or swallowed matter way faster than we thought, causing the resulting black hole to grow quickly. Or perhaps it's some combination of both. In addition, it's possible that this black hole is harming the growth of the galaxy GN-z11. That's because black holes radiate energy as they feed. At such a high rate of feasting, this energy could sweep away the gas of the host galaxy. And since stars are made from gas, it could quench star formation, slowly strangling the galaxy. Not to mention that without gas, the black hole wouldn't have anything to feed on and it too would die.

Keith Cooper reports via Space.com: A European Space Agency (ESA) probe has found enough water to cover Mars in an ocean between 4.9 and 8.9 feet (1.5 and 2.7 meters) deep, buried in the form of dusty ice beneath the planet's equator. The finding was made by ESA's Mars Express mission, a veteran spacecraft that has been engaged in science operations around Mars for 20 years now. While it's not the first time that evidence for ice has been found near the Red Planet's equator, this new discovery is by far the largest amount of water ice detected there so far and appears to match previous discoveries of frozen water on Mars.

"Excitingly, the radar signals match what we expect to see from layered ice and are similar to the signals we see from Mars' polar caps, which we know to be very ice rich," said lead researcher Thomas Watters of the Smithsonian Institution in the United States in an ESA statement. The deposits are thick, extended 3.7km (2.3) miles underground, and topped by a crust of hardened ash and dry dust hundreds of meters thick. The ice is not a pure block but is heavily contaminated by dust. While its presence near the equator is a location more easily accessible to future crewed missions, being buried so deep means that accessing the water-ice would be difficult.

Geoffrey.landis writes: The Japan SLIM spacecraft has successfully landed on moon, but power problems mean it may be short mission. The good news is that the landing was successful, making Japan only the fifth nation to successfully make a lunar landing, and the ultra-miniature rover and the hopper both deployed. The bad news is that the solar arrays aren't producing power, and unless they can fix the problem in the next few hours, the batteries will be depleted and it will die. But, short mission or long, hurrah for Japan for being the fifth country to successfully land a mission on the surface of the moon (on their third try; two previous missions didn't make it). It's a rather amazing mission. I've never seen a spacecraft concept that lands under rocket power vertically but then rotates over to rest horizontally on the surface.

An anonymous reader shares a report: These cafes had all adopted similar aesthetics and offered similar menus, but they hadn't been forced to do so by a corporate parent, the way a chain like Starbucks replicated itself. Instead, despite their vast geographical separation and total independence from each other, the cafes had all drifted toward the same end point. The sheer expanse of sameness was too shocking and new to be boring. Of course, there have been examples of such cultural globalisation going back as far as recorded civilisation. But the 21st-century generic cafes were remarkable in the specificity of their matching details, as well as the sense that each had emerged organically from its location. They were proud local efforts that were often described as "authentic," an adjective that I was also guilty of overusing. When travelling, I always wanted to find somewhere "authentic" to have a drink or eat a meal.

If these places were all so similar, though, what were they authentic to, exactly? What I concluded was that they were all authentically connected to the new network of digital geography, wired together in real time by social networks. They were authentic to the internet, particularly the 2010s internet of algorithmic feeds. In 2016, I wrote an essay titled Welcome to AirSpace, describing my first impressions of this phenomenon of sameness. "AirSpace" was my coinage for the strangely frictionless geography created by digital platforms, in which you could move between places without straying beyond the boundaries of an app, or leaving the bubble of the generic aesthetic. The word was partly a riff on Airbnb, but it was also inspired by the sense of vaporousness and unreality that these places gave me. They seemed so disconnected from geography that they could float away and land anywhere else. When you were in one, you could be anywhere.

My theory was that all the physical places interconnected by apps had a way of resembling one another. In the case of the cafes, the growth of Instagram gave international cafe owners and baristas a way to follow one another in real time and gradually, via algorithmic recommendations, begin consuming the same kinds of content. One cafe owner's personal taste would drift toward what the rest of them liked, too, eventually coalescing. On the customer side, Yelp, Foursquare and Google Maps drove people like me -- who could also follow the popular coffee aesthetics on Instagram -- toward cafes that conformed with what they wanted to see by putting them at the top of searches or highlighting them on a map. To court the large demographic of customers moulded by the internet, more cafes adopted the aesthetics that already dominated on the platforms. Adapting to the norm wasn't just following trends but making a business decision, one that the consumers rewarded. When a cafe was visually pleasing enough, customers felt encouraged to post it on their own Instagram in turn as a lifestyle brag, which provided free social media advertising and attracted new customers. Thus the cycle of aesthetic optimisation and homogenisation continued.

Dan Rockmore, the director of the Neukom Institute for Computational Sciences at Dartmouth College, writing for The New Yorker: Recently, statistical modelling has taken on a new kind of importance as the engine of artificial intelligence -- specifically in the form of the deep neural networks that power, among other things, large language models, such as OpenAI's G.P.T.s. These systems sift vast corpora of text to create a statistical model of written expression, realized as the likelihood of given words occurring in particular contexts. Rather than trying to encode a principled theory of how we produce writing, they are a vertiginous form of curve fitting; the largest models find the best ways to connect hundreds of thousands of simple mathematical neurons, using trillions of parameters.They create a vast data structure akin to a tangle of Christmas lights whose on-off patterns attempt to capture a chunk of historical word usage. The neurons derive from mathematical models of biological neurons originally formulated by Warren S. McCulloch and Walter Pitts, in a landmark 1943 paper, titled "A Logical Calculus of the Ideas Immanent in Nervous Activity." McCulloch and Pitts argued that brain activity could be reduced to a model of simple, interconnected processing units, receiving and sending zeros and ones among themselves based on relatively simple rules of activation and deactivation.

The McCulloch-Pitts model was intended as a foundational step in a larger project, spearheaded by McCulloch, to uncover a biological foundation of psychiatry. McCulloch and Pitts never imagined that their cartoon neurons could be trained, using data, so that their on-off states linked to certain properties in that data. But others saw this possibility, and early machine-learning researchers experimented with small networks of mathematical neurons, effectively creating mathematical models of the neural architecture of simple brains, not to do psychiatry but to categorize data. The results were a good deal less than astonishing. It wasn't until vast amounts of good data -- like text -- became readily available that computer scientists discovered how powerful their models could be when implemented on vast scales. The predictive and generative abilities of these models in many contexts is beyond remarkable. Unfortunately, it comes at the expense of understanding just how they do what they do. A new field, called interpretability (or X-A.I., for "explainable" A.I.), is effectively the neuroscience of artificial neural networks.

This is an instructive origin story for a field of research. The field begins with a focus on a basic and well-defined underlying mechanism -- the activity of a single neuron. Then, as the technology scales, it grows in opacity; as the scope of the field's success widens, so does the ambition of its claims. The contrast with climate modelling is telling. Climate models have expanded in scale and reach, but at each step the models must hew to a ground truth of historical, measurable fact. Even models of covid or elections need to be measured against external data. The success of deep learning is different. Trillions of parameters are fine-tuned on larger and larger corpora that uncover more and more correlations across a range of phenomena. The success of this data-driven approach isn't without danger. We run the risk of conflating success on well-defined tasks with an understanding of the underlying phenomenon -- thought -- that motivated the models in the first place.

Part of the problem is that, in many cases, we actually want to use models as replacements for thinking. That's the raison detre of modelling -- substitution. It's useful to recall the story of Icarus. If only he had just done his flying well below the sun. The fact that his wings worked near sea level didn't mean they were a good design for the upper atmosphere. If we don't understand how a model works, then we aren't in a good position to know its limitations until something goes wrong. By then it might be too late. Eugene Wigner, the physicist who noted the "unreasonable effectiveness of mathematics," restricted his awe and wonder to its ability to describe the inanimate world. Mathematics proceeds according to its own internal logic, and so it's striking that its conclusions apply to the physical universe; at the same time, how they play out varies more the further that we stray from physics. Math can help us shine a light on dark worlds, but we should look critically, always asking why the math is so effective, recognizing where it isn't, and pushing on the places in between.

Researchers have developed a way to apply quantum measurement to something no matter its mass or energy. "Our proposed experiment can test if an object is classical or quantum by seeing if an act of observation can lead to a change in its motion," says physicist Debarshi Das from UCL. ScienceAlert reports: Quantum physics describes a Universe where objects aren't defined by a single measurement, but as a range of possibilities. An electron can be spinning up and down, or have a high chance of existing in some areas more than others, for example. In theory, this isn't limited to tiny things. Your own body can in effect be described as having a very high probability of sitting in that chair and a very (very!) low probability of being on the Moon. There is just one fundamental truth to remember -- you touch it, you've bought it. Observing an object's quantum state, whether an electron, or a person sitting in a chair, requires interactions with a measuring system, forcing it to have a single measurement. There are ways to catch objects with their quantum pants still down, but they require keeping the object in a ground state -- super-cold, super-still, completely cut off from its environment. That's tricky to do with individual particles, and it gets a lot more challenging as the size of the scale goes up.

The new proposal uses an entirely novel approach, one that uses a combination of assertions known as Leggett-Garg Inequalities and No-Signaling in Time conditions. In effect, these two concepts describe a familiar Universe, where a person on a chair is sitting there even if the room is dark and you can't see them. Switching on the light won't suddenly reveal they're actually under the bed. Should an experiment find evidence that somehow conflicts with these assertions, we just might be catching a glimpse of quantum fuzziness on a larger scale.

The team proposes that objects can be observed as they oscillate on a pendulum, like a ball at the end of a piece of string. Light would then be flashed at the two halves of the experimental setup at different times -- counting as the observation -- and the results of the second flash would indicate if quantum behavior was happening, because the first flash would affect whatever was moving. We're still talking about a complex setup that would require some sophisticated equipment, and conditions akin to a ground state -- but through the use of motion and two measurements (light flashes), some of the restrictions on mass are removed. [...] "The next step is to try this proposed setup in an actual experiment," concludes the reports. "The mirrors at the Laser Interferometer Gravitational-Wave Observatory (LIGO) in the US have already been proposed as suitable candidates for examination."

"Those mirrors act as a single 10-kilogram (22-pound) object, quite a step up from the typical size of objects analyzed for quantum effects -- anything up to about a quintillionth of a gram."

The findings have been published in the journal Physical Review Letters.

Private equity firms are increasingly buying hospitals across the US, and when they do, patients suffer, according to two separate reports. Specifically, the equity firms cut corners, slash services, lay off staff, lower quality of care, take on substantial debt, and reduce charity care, leading to lower ratings and more medical errors, the reports collectively find. ArsTechnica: Last week, the financial watchdog organization Private Equity Stakeholder Project (PESP) released a report delving into the state of two of the nation's largest hospital systems, Lifepoint and ScionHealth -- both owned by private equity firm Apollo Global Management. Through those two systems, Apollo runs 220 hospitals in 36 states, employing around 75,000 people. The report found that some of Apollo's hospitals were among the worst in their respective states, based on a ranking by The Lown Institute Hospital Index. The index ranks hospitals and health systems based on health equity, value, and outcomes, PESP notes. The hospitals also have dismal readmission rates and government rankings.

The Center for Medicare and Medicaid Services (CMS) ranks hospitals on a one- to five-star system, with the national average of 3.2 stars overall and about 30 percent of hospitals at two stars or below. Apollo's overall average is 2.8 stars, with nearly 40 percent of hospitals at two stars or below. The other report, a study published in JAMA late last month, found that the rate of serious medical errors and health complications increases among patients in the first few years after private equity firms take over. The study examined Medicare claims from 51 private equity-run hospitals and 259 matched control hospitals. Specifically, the study, led by researchers at Harvard University, found that patients admitted to private equity-owned hospitals had a 25 percent increase in developing hospital-acquired conditions compared with patients in the control hospitals. In private equity hospitals, patients experienced a 27 percent increase in falls, a 38 percent increase in central-line bloodstream infections (despite placing 16 percent fewer central lines than control hospitals), and surgical site infections doubled.

With NASA's Artemis moon program now targeting September 2025 for its Artemis 2 mission and September 2026 for Artemis 3, some members of Congress are concerned about the potential repercussions, particularly with China's growing ambitions in lunar exploration. "For the United States and its partners not to be on the moon when others are on the moon is unacceptable," said Mike Griffin, former NASA administrator. "We need a program that is consistent with that theme. Artemis is not that program. We need to restart it, not keep it on track." Space.com reports: The U.S. House of Representatives' Committee on Science, Space and Technology held a hearing about the new Artemis plan today (Jan. 17), and multiple members voiced concern about the slippage. "I remind my colleagues that we are not the only country interested in sending humans to the moon," Committee Chairman Frank Lucas (R-OK) said in his opening remarks. "The Chinese Communist Party is actively soliciting international partners for a lunar mission -- a lunar research station -- and has stated its ambition to have human astronauts on the surface by 2030," he added. "The country that lands first will have the ability to set a precedent for whether future lunar activities are conducted with openness and transparency, or in a more restricted manner."

The committee's ranking member, California Democrat Zoe Lofgren (D-CA), voiced similar sentiments. "Let me be clear: I support Artemis," she said in her opening remarks. "But I want it to be successful, especially with China at our heels. And we want to be helpful here in the committee in ensuring that Artemis is strong and staying on track as we look to lead the world, hand-in-hand with our partners, in the human exploration of the moon and beyond." Several other committee members stressed that the new moon race is part of a broader competition with China, and that coming in second could imperil U.S. national security.

"It's no secret that China has a goal to surpass the United States by 2045 as global leaders in space. We can't allow this to happen," Rich McCormick (R-GA) said during the hearing. "I think the leading edge that we have in space technology will protect the United States -- not just the economy, but technologies that can benefit humankind." And Bill Posey (R-FL) referred to space as the "ultimate military high ground," saying that whoever leads in the final frontier "will control the destiny of this Earth."

An anonymous reader quotes a report from MIT Technology Review: Google DeepMind has created an AI system that can solve complex geometry problems. It's a significant step towards machines with more human-like reasoning skills, experts say. Geometry, and mathematics more broadly, have challenged AI researchers for some time. Compared with text-based AI models, there is significantly less training data for mathematics because it is symbol driven and domain specific, says Thang Wang, a coauthor of the research, which is published in Nature today. Solving mathematics problems requires logical reasoning, something that most current AI models aren't great at. This demand for reasoning is why mathematics serves as an important benchmark to gauge progress in AI intelligence, says Wang.

DeepMind's program, named AlphaGeometry, combines a language model with a type of AI called a symbolic engine, which uses symbols and logical rules to make deductions. Language models excel at recognizing patterns and predicting subsequent steps in a process. However, their reasoning lacks the rigor required for mathematical problem-solving. The symbolic engine, on the other hand, is based purely on formal logic and strict rules, which allows it to guide the language model toward rational decisions. These two approaches, responsible for creative thinking and logical reasoning respectively, work together to solve difficult mathematical problems. This closely mimics how humans work through geometry problems, combining their existing understanding with explorative experimentation.

DeepMind says it tested AlphaGeometry on 30 geometry problems at the same level of difficulty found at the International Mathematical Olympiad, a competition for top high school mathematics students. It completed 25 within the time limit. The previous state-of-the-art system, developed by the Chinese mathematician Wen-Tsun Wu in 1978, completed only 10. "This is a really impressive result," says Floris van Doorn, a mathematics professor at the University of Bonn, who was not involved in the research. "I expected this to still be multiple years away." DeepMind says this system demonstrates AI's ability to reason and discover new mathematical knowledge. "This is another example that reinforces how AI can help us advance science and better understand the underlying processes that determine how the world works," said Quoc V. Le, a scientist at Google DeepMind and one of the authors of the research, at a press conference.

Cancer deaths in the United States are falling, with four million deaths prevented since 1991, according to the American Cancer Society's annual report. At the same time, the society reported that the number of new cancer cases had ticked up to more than two million in 2023, from 1.9 million in 2022. The New York Times: Cancer remains the second leading cause of death in the United States, after heart disease. Doctors believe that it is urgent to understand changes in the death rate, as well as changes in cancer diagnoses. The cancer society highlighted three chief factors in reduced cancer deaths: declines in smoking, early detection and greatly improved treatments. Breast cancer mortality is one area where treatment had a significant impact. In the 1980s and 1990s, metastatic breast cancer "was regarded as a death sentence," said Donald Berry, a statistician at the University of Texas MD Anderson Cancer Center and an author of a new paper on breast cancer with Sylvia K. Plevritis of Stanford University and other researchers (several authors of the paper reported receiving payments from companies involved in cancer therapies).

The paper, published Tuesday in JAMA, found that the death rate from breast cancer had fallen to 27 per 100,000 women in 2019 from 48 per 100,000 in 1975. That includes metastatic cancer, which counted for nearly 30 percent of the reduction in the breast cancer death rate. Breast cancer treatment has improved so much that it has become a bigger factor than screening in saving lives, said Ruth Etzioni, a biostatistician at the Fred Hutchinson Cancer Center. Death rates have even declined among women in their 40s, who generally did not have regular mammograms, said Dr. Mette Kalager, a professor of medicine at the University of Oslo and Oslo University Hospital, "indicating a substantial effect of treatment," she said.

In a new paper published in the journal Science Progress, author Joseph Merz argues that climate issues are symptoms of ecological overshoot, driven by exploited human behaviors such as overconsumption, waste, and population growth. The paper emphasizes the need to change societal norms and behaviors through various means, including using marketing and media strategies to promote sustainable living, rather than solely focusing on technological or policy solutions. The Guardian reports: Merz and colleagues believe that most climate "solutions" proposed so far only tackle symptoms rather than the root cause of the crisis. This, they say, leads to increasing levels of the three "levers" of overshoot: consumption, waste and population. They claim that unless demand for resources is reduced, many other innovations are just a sticking plaster. "We can deal with climate change and worsen overshoot," says Merz. "The material footprint of renewable energy is dangerously underdiscussed. These energy farms have to be rebuilt every few decades -- they're not going to solve the bigger problem unless we tackle demand."

"Overshoot" refers to how many Earths human society is using up to sustain -- or grow -- itself. Humanity would currently need 1.7 Earths to maintain consumption of resources at a level the planet's biocapacity can regenerate. Where discussion of climate often centers on carbon emissions, a focus on overshoot highlights the materials usage, waste output and growth of human society, all of which affect the Earth's biosphere. "Essentially, overshoot is a crisis of human behavior," says Merz. "For decades we've been telling people to change their behavior without saying: 'Change your behavior.' We've been saying 'be more green' or 'fly less', but meanwhile all of the things that drive behavior have been pushing the other way. All of these subtle cues and not so subtle cues have literally been pushing the opposite direction -- and we've been wondering why nothing's changing."

The paper explores how neuropsychology, social signaling and norms have been exploited to drive human behaviors which grow the economy, from consuming goods to having large families. The authors suggest that ancient drives to belong in a tribe or signal one's status or attract a mate have been co-opted by marketing strategies to create behaviors incompatible with a sustainable world. "People are the victims -- we have been exploited to the point we are in crisis. These tools are being used to drive us to extinction," says the evolutionary behavioral ecologist and study co-author Phoebe Barnard. "Why not use them to build a genuinely sustainable world?" Just one-quarter of the world population is responsible for nearly three-quarters of emissions. The authors suggest the best strategy to counter overshoot would be to use the tools of the marketing, media and entertainment industries in a campaign to redefine our material-intensive socially accepted norms. "We're talking about replacing what people are trying to signal, what they're trying to say about themselves. Right now, our signals have a really high material footprint -- our clothes are linked to status and wealth, their materials sourced from all over the world, shipped to south-east Asia most often and then shipped here, only to be replaced by next season's trends. The things that humans can attach status to are so fluid, we could be replacing all of it with things that essentially have no material footprint -- or even better, have an ecologically positive one."

Japanese startup EX-Fusion plans to eliminate small pieces of space junk with laser beams fired from the ground. Nikkei Asia reports: EX-Fusion stands apart in that it is taking the ground-based approach, with the startup tapping its arsenal of laser technology originally developed in pursuit of fusion power. In October, EX-Fusion signed a memorandum of understanding with EOS Space Systems, an Australian contractor that possesses technology used to detect space debris. EX-Fusion plans to place a high-powered laser inside an observatory operated by EOS Space outside of Canberra. The first phase will be to set up laser technology to track debris measuring less than 10 cm. Pieces of this size have typically been difficult to target from the ground using lasers.

For the second phase, EX-Fusion and EOS Space will attempt to remove the space debris by boosting the power of the laser beams fired from the surface. The idea is to fire the laser intermittently against the debris from the opposing direction of its travel in order to slow it down. With a decreased orbiting speed, the debris will enter the Earth's atmosphere to burn up. High-powered lasers are often associated with weapons that blast objects into smithereens. Indeed, the EOS Space group supplies laser weapon systems used to destroy drones. But lasers designed to remove space debris are completely different from weapon-grade lasers, EOS Space's executive vice president James Bennett said during a visit to Japan in November.

Current laser weaponry often uses fiber lasers, which are capable of cutting and welding metal and can destroy targets like drones through heat created from continuous firing. Capturing and removing space junk instead involves diode-pumped solid-state (DPSS) lasers, which are pulsed to apply force to fast moving debris, stopping it like a brake. EX-Fusion's signature laser fusion process also involves DPSS lasers, which strike the surface of a hydrogen fuel pellet just millimeters in diameter, compressing it to trigger a fusion reaction. This makes space debris removal a useful test along the path to commercializing the fusion technology.