Singularity: The Dark Side of AI (100% AI Generated Non-Fiction Film)
In a world increasingly shaped by artificial intelligence, humanity stands at a crossroads. As AI technology advances rapidly, we must consider both its benefits and dangers. In this video, we will explore the negative aspects of AI, discussing the potential risks and serious consequences of its uncontrolled use. We will explore the hidden dangers and face the uncomfortable truths about our world that is becoming more and more reliant on AI.
Created by Maksim Shmeljov using several neural networks:
On a spring day 66 million years ago, paddlefish and sturgeon swam in a river that meandered through a flourishing landscape populated by mighty dinosaurs and small mammals at North America's southwestern corner. Death came from outer space that day.
Scientists examined well-preserved fish fossils to get a deeper understanding of one of the worst days in the history of life on Earth and shedding light on the global calamity triggered by an asteroid 7.5 miles (12 km) wide striking Mexico's Yucatan Peninsula. The ensuing mass extinction erased about three-quarters of Earth's species, including the dinosaurs at the end of the Cretaceous Period, paving the way for mammals - eventually humans - to become dominant on the planet.
The researchers determined that it was springtime at the fossil site called the Tanis deposit - and throughout the Northern hemisphere, including the spot where the asteroid hit - based on sophisticated examinations of bones from three paddlefishes and three sturgeons that died within about 30 minutes of the impact that occurred 2,200 miles (3500 km) away.
They found evidence that a hail of glass pelted the site, finding small spherules - molten material blasted by the impact into space that crystallized before falling back to Earth - embedded in fish gills. The Tanis fossils also indicated that a huge standing wave of water swept through after the impact, burying the local denizens alive. Among the dinosaurs living in the Tanis area was apex predator Tyrannosaurus rex.
"Every living thing in Tanis on that day saw nothing coming and was killed almost instantaneously," said Melanie During, a paleontology doctoral student at Uppsala University in Sweden and lead author of the research published in the journal Nature. During compared the fossils deposited at Tanis to "a car crash frozen in place."
Multiple lines of evidence pointed to a springtime impact. Annual growth rings in certain fish bones - resembling those in tree trunks - showed increased growth levels associated with springtime after reduced growth in leaner winter months. Chemical evidence from one of the paddlefishes indicated that food availability was increasing as it does in springtime, but not at peak summer levels.
Springtime marks a time of growth and reproduction for many organisms. "This season is crucial for the survival of species," said study co-author Sophie Sanchez, an Uppsala University senior lecturer in paleohistology. In the southern hemisphere, it was autumn at the time, Sanchez noted, a season when many creatures prepare for the deprivations of winter. Dinosaurs - aside from their bird descendants - went extinct, as did major marine groups, including the carnivorous reptiles that dominated the seas. Among the survivors were paddlefishes and sturgeons, which survive to this day.
The Tanis fossils helped the researchers better understand the events following the impact, which left a crater about 110 miles (180 km) wide at a Yucatan site called Chicxulub. The asteroid rocked the continental plate, generated earthquakes, sparked extensive wildfires, unleashed a massive shockwave in the air and seismic waves on the ground, and spawned massive standing waves called seiche waves - perhaps hundreds of yards tall - in water bodies. These waves, carrying immense amounts of sediment and debris, inundated the Tanis site within approximately 15 to 30 minutes after the impact, burying alive all the inhabitants, including the fish whose fossils were studied.
The peril did not end that day. A cloud of dust enrobed Earth, precipitating a climate catastrophe akin to a "nuclear winter" that blocked sunlight for perhaps years, condemning countless species to oblivion. "Although most of the extinction unfolded during the aftermath of the impact, which lasted much longer, zero hour - the exact timing of the impact - determined the course of the mass extinction," said study co-author Jeroen van der Lubbe, a geochemist and paleoclimatologist at Vrije Universiteit Amsterdam in the Netherlands.
Adobe Illustrator is a widely used vector graphics tool for graphic artists and it’s about to join the generative AI era with the launch of the Firefly Vector Model at Adobe’s MAX conference today. Adobe describes the new model as “the world’s first generative AI model focused on producing vector graphics.” Like Firefly for creating images and photos, Firefly for Illustrator will be able to create entire vector graphics from scratch. And like the other Firefly models, the vector model, too, was trained on data from Adobe Stock.
In its beta, Illustrator will now let you create entire scenes through a text prompt. What’s nifty here is that those scenes can consist of multiple objects. So this isn’t just a jumble of vectors that make up the overall graphic but Illustrator will automatically generate these different objects and you can manipulate them individually to your heart’s content, just like any other group or layer in Illustrator.
Alexandru Costin, Adobe’s VP for generative AI and Sensei, told me the company used tens of millions of vector images in Adobe Stock to train Firefly to enable this new capability. Costin described the process as “a journey” and since there hasn’t been as much work done on using generative AI to create vector drawings compared to the work on creating other images, this surely took a bit more work on the team’s part. He noted that the team focused on creating a model that could generate these images with the fewest possible points, too.
Another new feature that’s coming to Illustrator is called Mockup, which allows Illustrator users to take any 3D scene and then take any vector art and apply it to that 3D scene. That could be a design for a drink can, for example, or a mockup of a new logo on a t-shirt. “Mockup is really exciting to show your customers the art in context so they understand what they’re buying when they contract you as a freelancer,” Costin explained. Also new is Retype, which converts static text in images to editable text — and it’ll find matching fonts, too — and Illustrator is now available on the web, too!
The universe is humming with gravitational radiation—a very low-frequency rumble that rhythmically stretches and compresses spacetime and the matter embedded in it. That is the conclusion of several groups of researchers from around the world who simultaneously published a slew of journal articles in June describing more than 15 years of observations of millisecond pulsars within our corner of the Milky Way galaxy. At least one group—the North American Nanohertz Observatory for Gravitational Waves (NANOGrav) collaboration—has found compelling evidence that the precise rhythms of these pulsars are affected by the stretching and squeezing of spacetime by these long-wavelength gravitational waves.
"This is key evidence for gravitational waves at very low frequencies," says Vanderbilt University's Stephen Taylor, who co-led the search and is the current chair of the collaboration. "After years of work, NANOGrav is opening an entirely new window on the gravitational-wave universe."
Gravitational waves were first detected by the Laser Interferometer Gravitational-Wave Observatory (LIGO) in 2015. The short-wavelength fluctuations in spacetime were caused by the merger of smaller black holes, or occasionally neutron stars, all of them weighing in at less than a few hundred solar masses. The question now is: Are the long-wavelength gravitational waves—with periods from years to decades—also produced by black holes?
In one recent paper from the NANOGrav consortium, published in The Astrophysical Journal Letters, University of California, Berkeley, physicist Luke Zoltan Kelley and the NANOGrav team argued that the hum is likely produced by hundreds of thousands of pairs of supermassive black holes—each weighing billions of times the mass of our sun—that over the history of the universe have gotten close enough to one another to merge. The team produced simulations of supermassive black hole binary populations containing billions of sources and compared the predicted gravitational wave signatures with NANOGrav's most recent observations.
The black holes' orbital dance prior to merging vibrates spacetime analogous to the way waltzing dancers rhythmically vibrate a dance floor. Such mergers over the 13.8-billion-year age of the universe produced gravitational waves that today overlap, like the ripples from a handful of pebbles tossed into a pond, to produce the background hum. Because the wavelengths of these gravitational waves are measured in light years, detecting them required a galaxy-sized array of antennas—a collection of millisecond pulsars.
"I guess the elephant in the room is we're still not 100% sure that it's produced by supermassive black hole binaries. That is definitely our best guess, and it's fully consistent with the data, but we're not positive," said Kelley, UC Berkeley assistant adjunct professor of astronomy. "If it is binaries, then that's the first time that we've actually confirmed that supermassive black hole binaries exist, which has been a huge puzzle for more than 50 years now."
A new study highlights both the promise and the limitations of gene editing, as a highly lethal form of avian influenza continues to spread around the world.
Scientists have used the gene-editing technology known as CRISPR to create chickens that have some resistance to avian influenza, according to a new study that was published in the journal Nature Communications on Tuesday. The study suggests that genetic engineering could potentially be one tool for reducing the toll of bird flu, a group of viruses that pose grave dangers to both animals and humans. But the study also highlights the limitations and potential risks of the approach, scientists said. Some breakthrough infections still occurred, especially when gene-edited chickens were exposed to very high doses of the virus, the researchers found. And when the scientists edited just one chicken gene, the virus quickly adapted.
The findings suggest that creating flu-resistant chickens will require editing multiple genes and that scientists will need to proceed carefully to avoid driving further evolution of the virus, the study’s authors said. The research is “proof of concept that we can move toward making chickens resistant to the virus,” Wendy Barclay, a virologist at Imperial College London and an author of the study, said at a news briefing. “But we’re not there yet.” Some scientists who were not involved in the research had a different takeaway. “It’s an excellent study,” said Dr. Carol Cardona, an expert on bird flu and avian health at the University of Minnesota. But to Dr. Cardona, the results illustrate how difficult it will be to engineer a chicken that can stay a step ahead of the flu, a virus known for its ability to evolve swiftly. “There’s no such thing as an easy button for influenza,” Dr. Cardona said. “It replicates quickly, and it adapts quickly.”
What to Know About Avian Flu
The spread of H5N1. A new variant of this strain of the avian flu has spread widely through bird populations in recent years. It has taken an unusually heavy toll on wild birds and repeatedly spilled over into mammals, including minks, foxes and bears.
Here’s what to know about the virus:
What is avian influenza? Better known as the bird flu, avian influenza is a group of flu viruses that is well adapted to birds. Some strains, like the version of H5N1 that is currently spreading, are frequently fatal to chickens and turkeys. It spreads via nasal secretions, saliva and fecal droppings, which experts say makes it difficult to contain.
Should humans be worried about being infected? Although the danger to the public is currently low, people who are in close contact with sick birds can and have been infected. The virus is primarily a threat to birds, but infections in mammals increase the odds that the virus could mutate in ways that make it more of a risk to humans, experts say.
How can we stop the spread? The U.S. Department of Agriculture has urged poultry growers to tighten their farms’ biosecurity measures, but experts say the virus is so contagious that there is little choice but to cull infected flocks. The Biden administration has been contemplating a mass vaccination campaign for poultry.
Is it safe to eat poultry and eggs? The Agriculture Department has said that properly prepared and cooked poultry and eggs should not pose a risk to consumers. The chance of infected poultry entering the food chain is “extremely low,” according to the agency.
Can I expect to pay more for poultry products? Egg prices soared when an outbreak ravaged the United States in 2014 and 2015.
The current outbreak of the virus — paired with inflation and other factors — has contributed to an egg supply shortage and record-high prices in some parts of the country. Avian influenza refers to a group of flu viruses that are adapted to spread in birds. Over the last several years, a highly lethal version of a bird flu virus known as H5N1 has spread rapidly around the globe, killing countless farmed and wild birds. It has also repeatedly infected wild mammals and been detected in a small number of people. Although the virus remains adapted to birds, scientists worry that it could acquire mutations that help it spread more easily among humans, potentially setting off a pandemic. Many nations have tried to stamp out the virus by increasing biosecurity on farms, quarantining infected premises and culling infected flocks. But the virus has become so widespread in wild birds that it has proved impossible to contain, and some nations have begun vaccinating poultry, although that endeavor presents some logistic and economic challenges.
If scientists could engineer resistance into chickens, farmers would not need to routinely vaccinate new batches of birds. Gene editing “promises a new way to make permanent changes in the disease resistance of an animal,” Mike McGrew, an embryologist at the University of Edinburgh’s Roslin Institute and an author of the new study, said at the briefing. “This can be passed down through all the gene-edited animals, to all the offspring.” CRISPR, the gene-editing technology used in the study, is a molecular toolthat allows scientists to make targeted edits in DNA, changing the genetic code at a precise point in the genome. In the new study, the researchers used this approach to tweak a chicken gene that codes for a protein known as ANP32A, which the flu virus hijacks to copy itself. The tweaks were designed to prevent the virus from binding to the protein — and therefore keep it from replicating inside chickens. The edits did not appear to have negative health consequences for the chickens, the researchers said. “We observed that they were healthy, and that the gene-edited hens also laid eggs normally,” said Dr. Alewo Idoko-Akoh, who conducted the research as a postdoctoral researcher at the University of Edinburgh.
The researchers then sprayed a dose of flu virus into the nasal cavities of 10 chickens that had not been genetically edited, to serve as the control. (The researchers used a mild version of the virus different from the one that has been causing major outbreaks in recent years.) All of the control chickens were infected with the virus, which they then transmitted to other control chickens they were housed with. When the researchers administered flu virus directly into the nasal cavities of 10 gene-edited chickens, just one of the birds became infected. It had low levels of the virus and did not pass the virus on to other gene-edited birds. “But having seen that, we felt that it would be the responsible thing to be more rigorous, to stress test this and ask, ‘Are these chickens truly resistant?’” Dr. Barclay said. “‘What if they were to somehow encounter a much, much higher dose?’” When the scientists gave the gene-edited chickens a flu dose that was 1,000 times higher, half of the birds became infected. The researchers found, however, that they generally shed lower levels of the virus than control chickens exposed to the same high dose.
The researchers then studied samples of the virus from the gene-edited birds that had been infected. These samples had several notable mutations, which appeared to allow the virus to use the edited ANP32A protein to replicate, they found. Some of these mutations also helped the virus replicate better in human cells, although the researchers noted that those mutations in isolation would not be enough to create a virus that was well adapted to humans. Seeing those mutations is “not ideal,” said Richard Webby, who is a bird flu expert at St. Jude Children’s Research Hospital and was not involved in the research. “But when you get to the weeds of these particular changes, then it doesn’t concern me quite so much.” The mutated flu virus was also able to replicate even in the complete absence of the ANP32A protein by using two other proteins in the same family, the researchers found. When they created chicken cells that lacked all three of these proteins, the virus was not able to replicate. Those chicken cells were also resistant to the highly lethal version of H5N1 that has been spreading around the world the last several years. The researchers are now working to create chickens with edits in all three of the genes for the protein family. The big question, Dr. Webby said, was whether chickens with edits in all three genes would still develop normally and grow as fast as poultry producers needed. But the idea of gene editing chickens had enormous promise, he said. “Absolutely, we’re going to get to a point where we can manipulate the host genome to make them less susceptible to flu,” he said. “That’ll be a win for public health.”
Research cited published in Nature Comm. (Oct. 10, 2023):
Some asteroids have measured densities higher than those of any elements known to exist on Earth. This suggests that they are at least partly composed of unknown types of "ultradense" matter that cannot be studied by conventional physics. Jan Rafelski and his team at the Department of Physics, The University of Arizona, Tucson, U.S., suggest that this could consist of superheavy elements with atomic number (Z) higher than the limit of the current periodic table. They modeled the properties of such elements using the Thomas-Fermi model of atomic structure, concentrating particularly on a proposed "island of nuclear stability" at and around Z=164 and extending their method further to include more exotic types of ultra-dense material. This work has now been published in The European Physical Journal Plus.
Superheavy elements are defined as those with a very high number of protons (high atomic number), generally considered to be those with Z>104. They can be divided into two groups. Those with atomic numbers between 105 and 118 have been made experimentally but are radioactive and unstable with very short half-lives and, therefore, are only of academic and research interest. Elements with Z>118 have not yet been observed, but properties have been predicted for some of them. In particular, an "island of nuclear stability" is predicted at about Z=164. And as, in general, the density of elements tends to rise with their atomic mass, these superheavy elements can be expected to be extremely dense.
The densest stable element is the rare platinoid metal osmium (Z=76); its density of 22.59 g/cm3 is about twice that of lead. Objects—typically, astronomical bodies—with densities higher than that are considered "compact ultradense objects" or CUDOs. The most extreme example known is the asteroid named 33 Polyhymnia, which is located in the main belt between Mars and Jupiter; its density has been calculated as about 75 g/cm3. Rafelski proposes that Polyhymnia and similar objects may be composed of elements above Z=118, possibly with other types of ultradense matter.
Rafelski and his two student co-workers, Evan LaForge and Will Price set out to calculate the microscopic atomic structure and properties of ultraheavy elements using the relativistic Thomas-Fermi model of the atom. "We chose this model, despite its relative imprecision, because it allows the systematic exploration of atomic behavior as a function of atomic number beyond the known periodic table," Rafelski explains. "A further consideration is that it also enabled us to explore many atoms in the short time available to Evan [LaForge], our brilliant undergraduate student."
The researchers' calculations confirmed the prediction that atoms with around 164 protons in their nuclei were likely to be stable, and, furthermore, suggested that a stable element with Z=164 would have a density between 36.0 and 68.4 g/cm3: a range that approaches the expected value for asteroid Polyhymnia.
As their model used the charge distribution in the atomic nucleus as one of its inputs, it could be extended to simulate still more exotic substances including alpha matter: a condensate composed entirely of isolated helium nuclei (alpha particles).
The idea that some asteroids may be composed of materials unknown on Earth is further motivating potential "space miners" who are planning to exploit the precious metals, including gold, that are expected to lie close to the surface of others.
"All super-heavy elements—those that are highly unstable as well as those that are simply unobserved—have been lumped together as 'unobtainium,'" concludes Rafelski. "The idea that some of these might be stable enough to be obtained from within our solar system is an exciting one."
A virtual cell modeling system, powered by AI, will lead to breakthroughs in our understanding of diseases, argue the cofounders of the Chan Zuckerberg Initiative.
As the smallest living units, cells are key to understanding disease—and yet so much about them remains unknown. We do not know, for example, how billions of biomolecules—like DNA, proteins, and lipids—come together to act as one cell. Nor do we know how our many types of cells interact within our bodies. We have limited understanding of how cells, tissues, and organs become diseased and what it takes for them to be healthy.
AI can help us answer these questions and apply that knowledge to improve health and well-being worldwide—if researchers can access and harness these powerful new technologies. Imagine if we had a way to represent every cell state and cell type using AI models. A “virtual cell” could simulate the appearance and known characteristics of any cell type in our body—from the rods and cones that detect light in our retinas to the cardiomyocytes that keep our hearts beating.
Scientists could use such a simulator to predict how cells might respond to specific conditions and stimuli: how an immune cell responds to an infection, what happens at the cellular level when a child is born with a rare disease, or even how a patient’s body will respond to a new medication. Scientific discovery, patient diagnosis, and treatment decisions would all become faster, safer, and more efficient. At the Chan Zuckerberg Initiative, we’re helping to generate the scientific data and build out the computing infrastructure to make this a reality—and give scientists the tools they need to take advantage of new advances in AI to help end disease.
Advances in AI coupled with large volumes of scientific data have already predicted the structure of nearly all known proteins. DeepMind trained AlphaFold on 50 years’ worth of carefully collected data, and in just five years, they solved the mystery of protein structure. ESM, another AI system which was developed at Meta, is a protein language model trained not on words but on over 60 million protein sequences. It is used for a wide range of applications, like predicting protein structures and the effects of mutations from single sequences.
A virtual cell modeling system will also require large amounts of data. Since 2016, CZI has supported researchers globally in efforts to generate and annotate data about cells and their components, built tools to integrate these large data sets, and made them widely available for researchers to learn from and build upon. A global consortium of researchers has been building a reference map of every cell type in the body, and our San Francisco Biohub is creating whole-organism cell atlases. Together, these data sets are yielding the first draft of the open-source Human Cell Atlas, which will chart cell types in the body from development to adulthood. Our SF Biohub and the Chan Zuckerberg Imaging Institute are partnering on OpenCell, which maps the locations of different proteins in our cells.
Eric Schmidt: This is how AI will transform the way science gets done Science is about to become much more exciting—and that will affect us all, argues Google's former CEO.
Researchers are also using machine-learning models like Geneformer and scGPT to explore large amounts of data about genes and cells—including data generated from CELLxGENE, the open-source software platform that CZI’s science and technology teams created to speed up single-cell research. Similarly, with a new prototype data portal for cryo-electron tomography, our Imaging Institute and our science and technology teams are engaging machine-learning experts to develop automated annotations of microscopy data. This will speed up data processing time from months or even years to just weeks.
We are making the data as representative as possible to make sure scientific breakthroughs benefit everyone. This includes incorporating pediatric data into the Human Cell Atlas, filling gaps in our knowledge about the cellular mechanisms of diseases that arise in childhood. With our Ancestry Networks grants, we are also supporting researchers generating reference data about cells based on tissue samples from Black, Latino, Southeast Asian, and Indigenous people, among others from understudied racial, ethnic, and ancestral backgrounds.
Already, research teams have made discoveries using these well-curated data sets. One discovered that the broken gene linked to cystic fibrosis is expressed by a type of cell scientists had never come across before, while another identified the respiratory cells that are most vulnerable to SARS-CoV-2. Others are using the data to discover new options for splicing genes to potentially correct disease-causing mutations in specific cells. These discoveries are the first step in developing treatments for diseases—and we believe that AI can significantly speed up researchers’ rate of discoveries going forward.
How to compute a virtual cell?
To create a virtual cell, we’re building a high-performance computing cluster with 1000+ H100 GPUs that will enable us to develop new AI models trained on various large data sets about cells and biomolecules—including those generated by our scientific institutes. Over time, we hope, this will enable scientists to simulate every cell type in both healthy and diseased states, and query those simulations to see how elusive biological phenomena likely play out—including how cells come into being, how they interact across the body, and how exactly disease-causing changes affect them. The computing cluster won’t be as large as those used in the private sector for commercial products, but once it’s up and running, it will be one of the world’s largest AI clusters for nonprofit scientific research. This will be an important resource for academic teams that are ready to use data sets in new ways but are held back by the prohibitive cost of accessing the latest AI technology. Like our other tools, these digital cell models, and their associated data and applications, will be openly accessible to researchers worldwide.
A new report lays out a modern way to search for E.T., calling for better use of big data and machine learning techniques.
Humanity has wondered whether we are alone for millennia. The discovery of life elsewhere in the Universe, particularly intelligent life, would have profound effects, comparable to those of recognizing that the Earth is not the center of the Universe and that humans evolved from previous species.
There has been rapid growth in the fields of extrasolar planets and data-driven astronomy. In a relatively short interval, we have seen a change from knowing of no extrasolar planets to now knowing more potentially habitable extrasolar planets than there are planets in our Solar System. In approximately the same interval, astronomy has transitioned to a field in which sky surveys can generate 1 PB or more of informative data.
The Data-Driven Approaches to Searches for the Technosignatures of Advanced Civilizations is now ongoing. Data-driven searches, being able to process volumes of data much greater than a human could, and in a reproducible manner, can identify *anomalies* that could be clues to the presence of technosignatures. Experts agree that technosignature searches should be conducted in a manner consistent with Freeman Dyson's "First Law of SETI Investigations," namely "every search for alien civilizations should be planned to give interesting results even when no aliens are discovered." This approach to technosignatures is commensurate with NASA's approach to biosignatures in that no single observation or measurement can be taken as providing full certainty for the detection of life. Areas of particular promise identified during one of the recent workshop were (*) Data Mining of Large Sky Surveys, (*) All-Sky Survey at Far-Infrared Wavelengths, (*) Surveys with Radio Astronomical Interferometers, and (*) Artifacts in the Solar System.
SORTING SHAPES - Applying machine learning to find the properties of atomic pieces of geometry shows how AI has the power to accelerate discoveries in maths.
Mathematicians from Imperial College London and the University of Nottingham have, for the first time, used machine learning to expand and accelerate work identifying 'atomic shapes' that form the basic pieces of geometry in higher dimensions. Their findings have been published in Nature Communications. The way they used artificial intelligence, in the form of machine learning, could transform how maths is done, say the authors. Dr Alexander Kasprzyk from the University of Nottingham said: "For mathematicians, the key step is working out what the pattern is in a given problem. This can be very difficult, and some mathematical theories can take years to discover."
Prof.Tom Coates, from the Department of Mathematics at Imperial, added: "We have shown that machine learning can help uncover patterns within mathematical data, giving us both new insights and hints of how they can be proved." PhD student Sara Veneziale, from the Department of Mathematics at Imperial, said: "This could be very broadly applicable, such that it could rapidly accelerate the pace at which maths discoveries are made. It's like when computers were first used in maths research, or even calculators: it's a step-change in the way we do maths."
Defining shapes
Mathematicians describe shapes using equations, and by analysing these equations can break the shape down into fundamental pieces. These are the building blocks of shapes, the equivalent of atoms, and are called Fano varieties. The Imperial and Nottingham team began building a 'periodic table' of these Fano varieties several years ago, but finding ways of classifying them into groups with common properties has been challenging. Now, they have used machine learning to reveal unexpected patterns in the Fano varieties. One aspect of a Fano variety is its quantum period -- a sequence of numbers that acts like a barcode or fingerprint. It has been suggested that the quantum period defines the dimension of the Fano variety, but there has been no theoretical proposal for how this works, so no way to test it on the huge set of known Fano varieties.
Machine learning, however, is built to find patterns in large datasets. By training a machine learning model with some example data, the team were able to show the resulting model could predict the dimensions of Fano varieties from quantum periods with 99% accuracy.
A new study tests elephants’ abilities to innovate and circumvent barriers to food sources.
Individual innovation is considered one sign of intelligence within species, and elephants are among the animals that researchers have long taken an interest in because of their sophisticated approach to problem solving. A newly published study in the journal Animal Behaviour details findings from a six-month-long study documenting the abilities of individual wild Asian elephants to access food by solving puzzles that unlocked storage boxes.
"This is the first research study to show that individual wild elephants have different willingness and abilities to problem solve in order to get food," said the study's lead author Sarah Jacobson, a psychology doctoral candidate studying animal cognition at the CUNY Graduate Center and Hunter College. "This is important knowledge, because how animals think and innovate may influence their ability to survive in environments that are rapidly changing due to human presence."
Conducted at the Salakpra Wildlife Sanctuary in Kanchanaburi, Thailand, the study used motion-activated cameras to observe 77 wild Asian elephants who approached and decided whether to attempt opening puzzle boxes with three differently configured compartments that contained highly aromatic jackfruit. Depending on the compartment with which the elephant interacted, the jackfruit could be accessed by pulling on a chain so the door opened toward the elephant, pushing the door so that it swung open into the box, or sliding the door open to the right. The elephants had to independently interact with the puzzle boxes to discover how the compartments could be opened.
Over time, 44 of the elephants who approached the puzzle boxes interacted with them, but there were individual differences in how innovative the elephants were. The researchers found that elephants who interacted with the puzzle boxes more frequently and with greater persistence were more successful in retrieving food from all three differently configured compartments. Overall, 11 elephants solved one compartment type and eight solved two compartment types. Five elephants solved all three types, and therefore were the most innovative.
"Conflict involving humans and elephants is increasing due to loss of natural habitat and agricultural encroachment into what is left of it," said the study's principal investigator Dr. Joshua Plotnik, a psychology professor with the CUNY Graduate Center and Hunter College, and Sarah Jacobson's dissertation advisor. "Investigating innovation and problem solving in elephants can inform our understanding of wild elephant cognitive flexibility and its potential impact on conservation management and human-elephant conflict mitigation."
In addition to sweet, salty, sour, bitter and umami, the tongue might also detect ammonium chloride as a basic taste, say USC Dornsife neuroscientists
Japanese scientist Kikunae Ikeda first proposed umami as a basic taste -- in addition to sweet, sour, salty and bitter -- in the early 1900s. About eight decades later, the scientific community officially agreed with him.
Now, scientists led by researchers at the USC Dornsife College of Letters, Arts and Sciences have evidence of a sixth basic taste. In a research study published Oct. 10, 2023 in Nature Communications, USC Dornsife neuroscientist Emily Liman and her team found that the tongue responds to ammonium chloride through the same protein receptor that signals sour taste.
"If you live in a Scandinavian country, you will be familiar with and may like this taste," says Liman, professor of biological sciences. In some northern European countries, salt licorice has been a popular candy at least since the early 20th century. The treat counts among its ingredients salmiak salt, or ammonium chloride.
Scientists have for decades recognized that the tongue responds strongly to ammonium chloride. However, despite extensive research, the specific tongue receptors that react to it remained elusive. Liman and the research team thought they might have an answer.
In recent years, they uncovered the protein responsible for detecting sour taste. That protein, called OTOP1, sits within cell membranes and forms a channel for hydrogen ions moving into the cell.
Hydrogen ions are the key component of acids, and as foodies everywhere know, the tongue senses acid as sour. That's why lemonade (rich in citric and ascorbic acids), vinegar (acetic acid) and other acidic foods impart a zing of tartness when they hit the tongue. Hydrogen ions from these acidic substances move into taste receptor cells through the OTOP1 channel.
Because ammonium chloride can affect the concentration of acid -- that is, hydrogen ions -- within a cell, the team wondered if it could somehow trigger OTOP1.
To answer this question, they introduced the Otop1 gene into lab-grown human cells so the cells produce the OTOP1 receptor protein. They then exposed the cells to acid or to ammonium chloride and measured the responses. "We saw that ammonium chloride is a really strong activator of the OTOP1 channel," Liman said. "It activates as well or better than acids."
Ammonium chloride gives off small amounts of ammonia, which moves inside the cell and raises the pH, making it more alkaline, which means fewer hydrogen ions. "This pH difference drives a proton influx through the OTOP1 channel," explained Ziyu Liang, a PhD student in Liman's lab and first author on the study.
Diagnostic tools for timely, accurate and inexpensive early cancer detection that can assess risk or monitor response to treatment could help patients get the care they need faster and improve existing care strategies. But current cancer assessment methods have limited specificity and sensitivity and can be prohibitively expensive.
In a new study led by investigators from Mass General Brigham, the Wyss Institute for Biologically Inspired Engineering at Harvard University and Dana-Farber Cancer Institute, in collaboration with researchers from across the country and beyond the U.S., researchers developed a low-cost, ultrasensitive blood test to detect minute levels of a cancer biomarker that is highly specific to multiple common cancers. Each test can be performed with merely half a drop of blood (25 microliters). The tool showed promise for early cancer detection and disease monitoring, and could potentially be used in conjunction with other tools for detection, risk stratification and treatment. Results are published in Cancer Discovery.
“Cancer biomarker detection is a burgeoning area of research and is still a young field,” said co-corresponding author David Walt, Ph.D., of the Department of Pathology at Brigham and Women’s Hospital, a founding member of Mass General Brigham. Walt is also a core faculty member at the Wyss Institute. “Our results show that we can detect levels of this pan-cancer biomarker in the blood of patients with many types of cancers.”
The new study leverages a single-molecule-based detection technology known as SIMOA that was developed by the Walt lab. The test is designed to detect the open reading frame 1 protein (ORF1p), a transposable element protein that’s known to occur in many cancers but not in corresponding normal tissue, and that can indicate high risk of cancer lethality. Researchers have long sought a sensitive, accurate test to detect ORF1p. The authors describe their first investigation of the test as a pilot experiment that wound up working better than they had imagined, which was followed by a series of engineering improvements and iterations in patient samples.
“We were shocked by how well this test worked in detecting the biomarker’s expression across cancer types,” said lead author Martin Taylor, M.D., Ph.D., of the Department of Pathology at Massachusetts General Hospital, the other founding member of Mass General Brigham. “It’s created more questions for us to explore and sparked interest among collaborators across many institutions.”
Teaming up with investigators across Mass General Brigham, Dana-Farber, Beth Israel Deaconess, and MIT in Boston and from Rockefeller University, University of Pennsylvania, University of Washington (Seattle), Johns Hopkins, Groningen (Netherlands), and Canon Medical, the researchers tested blood samples from patients with different types of cancers, including ovarian and colorectal cancer. The ultrasensitive assessment tool successfully quantified ORF1p in cancer patient blood samples, but only in very rare ‘healthy’ patients, supporting the specificity for cancer detection. Studies in tissue samples from ~200 colon cancer and 75 esophageal biopsies, obtained from patients at different disease stages, showed that ORF1p tissue expression was prevalent in carcinomas and high-risk precursor lesions.
“Our results bolster the emerging idea that ORF1p expression is a ‘hallmark of cancer’ expressed starting early in the disease process. Pervasive expression of ORF1p in carcinomas and the lack of expression in normal tissues makes ORF1p unlike other protein biomarkers, which have normal expression levels. This unique biology makes it highly specific,” said Taylor.
The gyroid was discovered in 1970 by NASA scientist Alan Schoen. He calculated the angle of association and gave a convincing demonstration of pictures of intricate plastic models, but did not provide a proof of embeddedness. Schoen noted that the gyroid contains neither straight lines nor planar symmetries. Karcher gave a different, more contemporary treatment of the surface in 1989 using conjugate surface construction. In 1996 Große-Brauckmann and Wohlgemuth proved that it is embedded, and in 1997 Große-Brauckmann provided CMC (constant mean curvature) variants of the gyroid and made further numerical investigations about the volume fractions of the minimal and CMC gyroids.
The gyroid separates space into two oppositely congruent labyrinths of passages. The gyroid has space groupI4132 (no. 214). Channels run through the gyroid labyrinths in the (100) and (111) directions; passages emerge at 70.5 degree angles to any given channel as it is traversed, the direction at which they do so gyrating down the channel, giving rise to the name "gyroid". One way to visualize the surface is to picture the "square catenoids" of the P surface (formed by two squares in parallel planes, with a nearly circular waist); rotation about the edges of the square generate the P surface. In the associate family, these square catenoids "open up" (similar to the way the catenoid "opens up" to a helicoid) to form gyrating ribbons, then finally become the Schwarz D surface. For one value of the associate family parameter the gyrating ribbons lie in precisely the locations required to have an embedded surface.
EVEscape uses evolutionary and biological information to predict how a virus could change to escape the immune system.
The COVID-19 pandemic seemed like a never-ending parade of SARS-CoV-2 variants, each equipped with new ways to evade the immune system, leaving the world bracing for what would come next. But what if there were a way to make predictions about new viral variants before they actually emerge?
A new artificial intelligence tool named EVEscape, developed by researchers at Harvard Medical School and the University of Oxford, can do just that. The tool has two elements: A model of evolutionary sequences that predicts changes that can occur to a virus, and detailed biological and structural information about the virus. Together, they allow EVEscape to make predictions about the variants most likely to occur as the virus evolves.
In a recent study published in Nature, the researchers show that had it been deployed at the start of the COVID-19 pandemic, EVEscape would have predicted the most frequent mutations and identified the most concerning variants for SARS-CoV-2. The tool also made accurate predictions about other viruses, including HIV and influenza. The researchers are now using EVEscape to look ahead at SARS-CoV-2 and predict future variants of concern; every two weeks, they release a ranking of new variants. Eventually, this information could help scientists develop more effective vaccines and therapies. The team is also broadening the work to include more viruses.
“We wanted to know if we can anticipate the variation in viruses and forecast new variants — because if we can, that’s going to be extremely important for designing vaccines and therapies,” said senior author Debora Marks, professor of systems biology in the Blavatnik Institute at HMS.
From EVE to EVEscape
The researchers first developed EVE, short for evolutionary model of variant effect, in a different context: gene mutations that cause human diseases. The core of EVE is a generative model that learns to predict the functionality of proteins based on large-scale evolutionary data across species.
“Viruses are flexible — it’s almost like they’ve evolved to evolve.”
explains Debora Marks, Blavatnik Institute at Harvard Medical School. “You can use these generative models to learn amazing things from evolutionary information — the data have hidden secrets that you can reveal,” Marks said.
As the COVID-19 pandemic hit and progressed, the world was caught off guard by SARS-CoV-2’s impressive ability to evolve. The virus kept morphing, changing its structure in ways subtle and substantial to slip past vaccines and therapies designed to defeat it. “We underestimate the ability of things to mutate when they’re under pressure and have a large population in which to do so,” Marks said. “Viruses are flexible — it’s almost like they’ve evolved to evolve.”
Watching the pandemic unfold, Marks and her team saw an opportunity to help: They rebuilt EVE into a new tool called EVEscape for the purpose of predicting viral variants. They took the generative model from EVE — which can predict mutations in viral proteins that won’t interfere with the virus’s function — and added biological and structural details about the virus, including information about regions most easily targeted by the immune system.
“We’re taking biological information about how the immune system works and layering it on our learnings from the broader evolutionary history of the virus,” explained co-lead author Nicole Thadani, a former research fellow in the Marks lab.
Artificial intelligence takes a lot of compute power, and Microsoft is putting together a road map for powering that computation with small nuclear reactors. That’s according to a job description Microsoft posted Thursday seeking a nuclear technology expert to lead the company’s technical assessment for integrating small modular nuclear reactors and microreactors “to power the datacenters that the Microsoft Cloud and AI reside on,” the job posting reads.
Specifically, Microsoft is looking to hire a “principal program manager for nuclear technology” and that person “will be responsible for maturing and implementing a global Small Modular Reactor (SMR) and microreactor energy strategy,” the job posting reads. Microsoft is looking to generate energy with nuclear fission, which is when an atom splits and releases energy as a result of that splitting.
News of this job description was first reported on DCD, a website about data centers. In January 2023, Microsoft announced a multiyear, multibillion-dollar investment in OpenAI, maker of viral AI chatbot ChatGPT. Bill Gates, Microsoft’s co-founder, is also the chairman of the board of TerraPower, a nuclear innovation company in the process of developing and scaling small modular reactor designs. TerraPower “does not currently have any agreements to sell reactors to Microsoft,” a spokesperson told CNBC. However, Microsoft has publicly committed to pursuing nuclear energy from an innovator in the fusion space.
In May, Microsoft announced it signed a power purchase agreement with Helion, a nuclear fusion startup, to buy electricity from it in 2028. Sam Altman, CEO of OpenAI, is an early and significant investor in Helion. Nuclear fusion occurs when two smaller atomic nuclei smash together to form a heavier atom and release tremendous quantities of energy in the process. It is the way in which the sun makes power. Fusion has not yet been recreated at scale here on earth, but many venture-backed startups are working to make it a reality due to the potential promise of virtually unlimited clean energy.
Interest in nuclear energy has increased alongside concerns about climate change in recent years, as nuclear reactors generate electricity without releasing virtually any carbon dioxide emissions.
The existing fleet of nuclear reactors in the U.S. was largely built between 1970 and 1990, and currently generates about 18% of the total electricity in the U.S., according to the U.S. Energy Information Administration. Nuclear energy also makes up 47% of America’s carbon-free electricity in 2022, according to the U.S. Department of Energy.
Much of the hope for the next generation of nuclear reactor technology in the U.S. is pinned on smaller nuclear reactors, which Microsoft’s job posting indicates the company is interested in using to power its data centers.
Germinal centers (GCs) are distinct microanatomical structures that form in the secondary lymphoid organs of endothermic vertebrates (i.e., mammals and some birds). Within GCs, B cells undergo a Darwinian selection process to identify clones which can respond to pathogen insult as well as affinity mature the B cell repertoire. The GC response ultimately generates memory B cells and bone marrow plasma cells which facilitate humoral immunological memory, the basis for successful vaccination programs.
GCs have not been observed in the secondary lymphoid organs of ectothermic jawed vertebrates (i.e., fishes, reptiles, and amphibians). However, abundant research over the past decades has indicated these organisms can produce antigen specific B cell responses and some degree of affinity maturation.
This current review examines data demonstrating that the fundamentals of B cell selection may be more conserved across vertebrate phylogeny than previously anticipated. Further, research in both conventional mammalian model systems and comparative models raises the question of what evolutionary benefit GCs provide endotherms if they are seemingly unnecessary for generating the basic functional components of jawed vertebrate humoral adaptive immune responses.
Using the full capabilities of the Quantinuum H1-1 quantum computer, researchers from the Department of Energy's Oak Ridge National Laboratory not only demonstrated best practices for scientific computing on current quantum systems but also produced an intriguing scientific result. By modeling singletfission—in which absorption of a single photon of light by a molecule produces two excited states—the team confirmed that the linear H4 molecule's energetic levels match the fission process's requirements. The linear H4 molecule is, simply, a molecule made of four hydrogen atoms arranged in a linear fashion.
A molecule's energetic levels are the energies of each quantum state involved in a phenomenon, such as singlet fission, and how they relate and compare with one another. The fact that the linear molecule's energetic levels are conducive to singlet fission could prove to be useful knowledge in the overall effort to develop more efficient solar panels.
"This is one of the leading motivating factors behind singlet fission—conventional solar cells have a theoretical maximum efficiency of about 33%, but it has been postulated that materials that exhibit singlet fission can break that limit and can be more efficient," said Daniel Claudino, a research scientist in ORNL's Quantum Computational Science group and the project's principal investigator. "The downside is that to understand fundamentally whether a certain material exhibits singlet fission is very hard. There is a specific energetic requirement, and it's difficult to find materials that fulfill it."
With its high accuracy for a manageable computational cost, the ORNL team's approach to using a quantum computer provides an effective simulation method to identify molecules that demonstrate singlet fission properties while bypassing approximations commonly found in techniques used for classical computers. The results of its work were published in The Journal of Physical Chemistry Letters.
Singlet fission is a multistate phenomenon, so the ORNL team needed a computational method that could describe all the process's quantum states on an equal footing to calculate accurate energetics numbers. They turned to PDS, which is a quantum solver based on the Peeters-Devreese-Soldatov approach and developed at Pacific Northwest National Laboratory.
Previous research has indicated that when flying at night, birds (and many other animals) use Earth's magnetic field for navigation. Because solar events disrupt the magnetic field — as well as produce auroras — birds have more difficulty navigating during them. The new study analyzed images taken from 37 NEXRAD Doppler weather radar stations, which can detect groups of migrating birds, as well as data from ground-based magnetometers, to study 23 years of bird migration across the U.S. Great Plains. The 1,000-mile (1,600-kilometer) span from North Dakota to Texas is considered a major migratory corridor for birds.
"The biggest challenge was trying to distill such a large dataset — years and years of ground magnetic field observations — into a geomagnetic disturbance index for each radar site," Daniel Welling, University of Michigan space scientist said in a statement. "There was a lot of heavy lifting in terms of assessing data quality and validating our final data product to ensure that it was appropriate for this study."
The work paid off. The researchers discovered that the number of migrating birds in this region decreases by 9 to 17 percent during severe space weather events. They also noticed increased rates of birds becoming lost during migration, a phenomenon known as migratory bird vagrancy.
The researchers posit four stages of Earth's past and possible future to illustrate how planetary intelligence might play a role in humanity's long-term future. They also show how these stages of evolution driven by planetary intelligence may be a feature of any planet in the galaxy that evolves life and a sustainable technological civilization.
Stage 1—Immature biosphere: Characteristic of very early Earth, billions of years ago and before a technological species, when microbes were present but vegetation had not yet come about. There were few global feedbacks because life couldn't exert forces on Earth's atmosphere, hydrosphere, and other planetary systems.
Stage 2—Mature biosphere: Characteristic of Earth, also before a technological species, from about 2.5 billion to 540 million years ago. Stable continents formed, vegetation and photosynthesis developed, oxygen built up in the atmosphere, and the ozone layer emerged. The biosphere exerted a strong influence on the Earth, perhaps helping to maintain Earth's habitability.
Stage 3—Immature technosphere: Characteristic of Earth now, with interlinked systems of communication, transportation, technology, electricity, and computers. The technosphere is still immature, however, because it is not integrated into other Earth systems, such as the atmosphere. Instead, it draws matter and energy from Earth's systems in ways that will drive the whole into a new state that likely doesn't include the technosphere itself. Our current technosphere is, in the long run, working against itself.
Stage 4—Mature technosphere: Where Earth should aim to be in the future, Frank says, with technological systems in place that benefit the entire planet, including globally harvesting energy in forms like solar that do not harm the biosphere. The mature technosphere is one that has co-evolved with the biosphere into a form that allows both the technosphere and the biosphere to thrive.
"Planets evolve through immature and mature stages, and planetary intelligence is indicative of when you get to a mature planet," Frank says. "The million-dollar question is figuring out what planetary intelligence looks like and means for us in practice because we don't know how to move to a mature technosphere yet."
The complex system of planetary intelligence Although we don't yet know specifically how planetary intelligence might manifest itself, the researchers note that a mature technosphere involves integrating technological systems with Earth through a network of feedback loops that make up a complex system.
Put simply, a complex system is anything built from smaller parts that interact in such a fashion that the overall behavior of the system is entirely dependent on the interaction. That is, the sum is more than the whole of its parts. Examples of complex systems include forests, the Internet, financial markets, and the human brain.
By its very nature, a complex system has entirely new properties that emerge when individual pieces are interacting. It is difficult to discern the personality of a human being, for instance, solely by examining the neurons in her brain.
That means it is difficult to predict exactly what properties might emerge when individuals form a planetary intelligence. However, a complex system like planetary intelligence will, according to the researchers, have two defining characteristics: It will have emergent behavior and will need to be self-maintaining.
"The biosphere figured out how to host life by itself billions of years ago by creating systems for moving around nitrogen and transporting carbon," Frank says. "Now we have to figure out how to have the same kind of self-maintaining characteristics with the technosphere."
If new particles are out there, the Large Hadron Collider (LHC) is the ideal place to search for them.
The theory of supersymmetry suggests that a whole new family of partner particles exists for each of the known fundamental particles. While this might seem extravagant, these partner particles could address various shortcomings in current scientific knowledge, such as the source of the mysterious dark matter in the Universe, the “unnaturally” small mass of the Higgs boson, the anomalous way that the muon spins and even the relationship between the various forces of nature. But if these supersymmetric particles exist, where might they be hiding?
This is what physicists at the LHC have been trying to find out, and in a recent study of proton–proton collision data from Run 2 of the LHC (2015–2018), the ATLAS collaboration provides the most comprehensive overview yet of its searches for some of the most elusive types of supersymmetric particles – those that would only rarely be produced through the “weak” nuclear force or the electromagnetic force. The lightest of these weakly interacting supersymmetric particles could be the source of dark matter.
The increased collision energy and the higher collision rate provided by Run 2, as well as new search algorithms and machine-learning techniques, have allowed for deeper exploration into this difficult-to-reach territory of supersymmetry.
ATLAS physicists have pulled together results from eight searches, each seeking evidence for supersymmetric particles in a different way. The combined power and sensitivity of the different search strategies has allowed ATLAS researchers to study tens of thousands of supersymmetry models, each with different predictions about the masses of supersymmetric particles.
These ATLAS searches have unprecedented sensitivity and explore a wide range of supersymmetric-particle masses. The ATLAS physicists looked for evidence of “lab-made” dark matter – that is, dark matter created in LHC collisions. Their searches have proved complementary to other experiments seeking natural, “relic” dark matter left over from the Big Bang. Unlike collider searches, which don’t need to see the dark matter to infer its presence, the latter experiments rely on the sufficiently large probability of dark matter particles hitting normal materials and therefore being detected.
One of the most significant findings of this combination of searches is that some regions for supersymmetric-particle masses that were previously viewed favourably, where the dark matter particle has about half the mass of the Z boson or the Higgs boson, have now been almost totally ruled out.
Another benefit of such a comprehensive study is an understanding of which supersymmetry models have not yet been probed. ATLAS has presented examples of such surviving models, which can be used to optimise future searches. Though possible hiding places for supersymmetric particles are being systematically reduced, many models remain stubbornly evasive.
Improving the sensitivity of ATLAS searches to these models will require more collision data and further clever developments in search strategy.
Grass may transfer genes from their neighbors in the same way genetically modified crops are made, a new study has revealed.
Research, led by the University of Sheffield, is the first to show the frequency at which grasses incorporate DNA from other species into their genomes through a process known as lateral gene transfer. The stolen genetic secrets give them an evolutionary advantage by allowing them to grow faster, bigger or stronger and adapt to new environments quicker.
Understanding the rate is important to know the potential impact it can have on a plant's evolution and how it adapts to the environment. Grasses are the most ecologically and economically important group of plants, covering 30% of the earth's terrestrial surface and producing a majority of our food.
The Sheffield team sequenced multiple genomes of a species of tropical grass and determined at different time points in its evolution how many genes were acquired -- giving a rate of accumulation. It is now thought these transfers are likely to occur in the same way that some genetically modified crops are made.
These findings, published in the journal New Phytologist could inform future work to harness the process to improve crop productivity and make more resilient crops, and have implications on how we view and use controversial GM crops. Dr. Luke Dunning, Research Fellow from the University of Sheffield's School of Biosciences, and senior author of the research, said: "There are many methods to make GM crops, some which require substantial human intervention and some that don't. Some of these methods that require minimal human intervention could occur naturally and facilitate the transfers we have observed in wild grasses. These methods work by contaminating the reproductive process with DNA from a third individual. Our current working hypothesis, and something we plan to test in the near future, is that these same methods are responsible for the gene transfers we document in wild grasses."
If global temperatures increase by 1 degree Celsius (˚C) or more than current levels, each year billions of people will be exposed to heat and humidity so extreme they will be unable to naturally cool themselves, according to interdisciplinary research from the Penn State College of Health and Human Development, Purdue University College of Sciences and Purdue Institute for a Sustainable Future.
Results from a new article published today (Oct. 9, 2023) in Proceedings of the National Academy of Sciences (PNAS) indicated that warming of the planet beyond 1.5˚C above preindustrial levels will be increasingly devastating for human health across the planet. Humans can only withstand certain combinations of heat and humidity before their bodies begin to experience heat-related health problems, such as heat stroke or heart attack. As climate change pushes temperatures higher around the world, billions of people could be pushed beyond these limits.
Since the start of the industrial revolution, when humans began to burn fossil fuels in machines and factories, temperatures around the world have increased by about 1˚C, or 1.8 degrees Fahrenheit (˚F). In 2015, 196 nations signed the Paris Agreement which aims to limit worldwide temperature increases to 1.5˚C above pre-industrial levels.
The researcher team modeled global temperature increases ranging between 1.5˚C and 4˚C -- considered the worst-case scenario where warming would begin to accelerate -- to identify areas of the planet where warming would lead to heat and humidity levels that exceed human limits.
"To understand how complex, real-world problems like climate change will affect human health, you need expertise both about the planet and the human body," said co-author W. Larry Kenney, professor of physiology and kinesiology, the Marie Underhill Noll Chair in Human Performance at Penn State and co-author of the new study. "I am not a climate scientist, and my collaborators are not physiologists. Collaboration is the only way to understand the complex ways that the environment will affect people's lives and begin to develop solutions to the problems that we all must face together."
A threat to billions
The ambient wet-bulb temperature limit for young, healthy people is about 31˚C, which is equal to 87.8˚F at 100% humidity, according to work published last year by Penn State researchers. However, in addition to temperature and humidity, the specific threshold for any individual at a specific moment also depends on their exertion level and other environmental factors, including wind speed and solar radiation. In human history, temperatures and humidity that exceed human limits have been recorded only a limited number of times -- and only for a few hours at a time -- in the Middle East and Southeast Asia, according to the researchers.
WHOI scientists document changes in the Gulf Stream using two decades of measurements from Argo floats and Spray underwater gliders.
The Gulf Stream is intrinsic to the global climate system, bringing warm waters from the Caribbean up the East Coast of the United States. As it flows along the coast and then across the Atlantic Ocean, this powerful ocean current influences weather patterns and storms, and it carries heat from the tropics to higher latitudes as part of the Atlantic Meridional Overturning Circulation.
A new study published today in Nature Climate Change now documents that over the past 20 years, the Gulf Stream has warmed faster than the global ocean as a whole and has shifted towards the coast. The study, led by Robert Todd, a physical oceanographer at the Woods Hole Oceanographic Institution (WHOI), relies on over 25,000 temperature and salinity profiles collected between 2001 and 2023.
"The warming we see near the Gulf Stream is due to two combined effects. One is that the ocean is absorbing excess heat from the atmosphere as the climate warms," said Todd. "The second is that the Gulf Stream itself is gradually shifting towards the coast."
He and study co-author Alice Ren, also a physical oceanographer at WHOI, found that the near-surface layer of the Gulf Stream has changed most prominently. According to their data, it has warmed on average by about 1°C (2 °F) over the past two decades, becoming increasingly lighter than the waters below. The team also found the Gulf Stream to be shifting closer to the shore by about 5 kilometers (3.1 miles) per decade on average, meaning that the Gulf Stream is moving gradually closer to the Northeastern United States continental shelf.
"One of the triumphs of this paper is that it provides observational confirmation of something that numerical simulations have predicted in a warming climate," Todd said. They identified these trends using observational data from Spray autonomous underwater gliders and from the Argo Program, which is an array of about 4,000 autonomous profiling floats that drift with ocean currents and move up and down between the surface and about 2,000 meters (6,560 feet) in depth, collecting data as they rise. Argo is an international program that has been operating since 1999. WHOI is one of the original Argo institutions and maintains about 10% of the array.
To better resolve the Gulf Stream, Todd and Ren have launched Spray gliders off the coast of Florida every two months. Like Argo floats, the gliders move up and down, but they have the additional ability to fly through the water and crisscross the Gulf Stream as it carries them northward. By providing measurements below the surface of the Gulf Stream, the gliders and floats complement satellites that routinely measure water temperature at the ocean surface.
The black curtain goes up: As if on a stage, below us lies a cleanroom, about the size of a school gymnasium. It is almost entirely filled with a laser system. Here, powerful laser beams zip through the air, containing a stream of femtosecond light pulses lasting just a few millionths of a billionth of a second. The system is so sensitive that we can only admire it through an observation window. The complex assembly of optical instruments before us forms the first section of a speedway where the world’s shortest flashes of light cross the finish line. But this is no racetrack: we’re in the department of Ferenc Krausz at the Max Planck Institute of Quantum Optics in Garching.
The femtosecond laser pulses – which are already very short – travel through a vacuum tube to a lab one floor down. We’re allowed to enter this lab. This is where attosecond flashes are created, which are a thousand times shorter than femtopulses. In the lab stands a large barrel to which doctoral students Martin Schäffer and Johann Riemensberger are making some adjustments. The barrel is vaguely reminiscent of an enormous washing machine drum crossed with an old diving helmet. In reality, it’s a vacuum chamber made of solid stainless steel. Its armored-glass windows permit a glimpse of the probe that marks the target of the attosecond flashes of light.
Schäffer and Riemensberger belong to the Garching-based team of Reinhard Kienberger, who is also a physics professor at Technische Universität München (TUM). More than a hundred scientists conduct their research in Ferenc Krausz’s department. The pioneer of attosecond technology attracts young scientists from all over the world who want to observe some of nature’s extremely fast processes.
Krausz is therefore the perfect person to convey a sense of how fast an attosecond is. Purely mathematically, an attosecond is a billionth of a billionth of a second. Even as a physicist, Krausz finds this numbers game lacking in clarity. So he searches for suitable comparisons. “The fastest thing we know is light,” he explains, “which can circle the earth approximately eight times in one second.” But even though light is so fast, within one attosecond, it could only travel from one end of a single water molecule to the other!” With a diameter of only 0.3 nanometres (a nanometre is one millionth of a millimetre), a water molecule is unimaginably tiny. “Nano” is derived from the Ancient Greek word for dwarf, nanos, and that is precisely what attosecond physics is about: extremely dwarfish quantum objects that move incredibly quickly.
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