 Your new post is loading...
Despite being larger than the original Starlink satellites, the new "Mini" version is fainter, meeting astronomers' recommendations. SpaceX launched their first batch of second-generation Starlink satellites on February 27th. These spacecraft are called “Mini,” but they are only small in comparison to the full-size satellites that will come later. The 116 square meters of surface area make them more than four times the size of the first-generation spacecraft. The Minis’ large dimensions were an immediate concern for professional and amateur astronomers alike because area usually translates to brightness. However, SpaceX changed their physical design and concept of operations (conops) in order to mitigate their brightness. The company developed a highly reflective dielectric mirror film and a low-reflectivity black paint, which are applied to several parts of the spacecraft body. The mirror-like surface reflects sunlight into space instead of scattering it toward observers on the ground. In addition, the solar panels can be oriented so that observers do not see their sunlit sides. The brightness mitigation plan sounded promising but measurements were needed to determine its effectiveness. So, a group of satellite observers began recording magnitudes. Scott Harrington recorded the first data point visually on March 14th. He has since obtained 125 additional magnitudes from his dark-sky location in Arkansas. Meanwhile, Andreas Hornig developed software to process video observations. He derived 108 magnitude measurements recorded from Macedonia on the night of April 12th alone. In all, we have acquired 506 brightness measurements for our study. SpaceX launched three additional batches of 21 or more Mini satellites in April, May, and June. These spacecraft ascend from low, orbit-insertion heights toward their eventual altitude at 560-km (350 mi). Until May, we were observing Mini satellites at all heights without knowing whether they were operating for brightness mitigation. Then Richard Cole in the UK noticed that some spacecraft had leveled off at 480 km. He reasoned that these satellites might already be in mitigation mode and suggested that we prioritize them. We found that the Minis at that height were several magnitudes fainter than those at other altitudes. SpaceX sent us a message on May 16th confirming that Richard was correct. Now that we could distinguish between mitigated and unmitigated spacecraft, we began to characterize the brightness of each group, prioritizing measurements for those satellites that were already operational. Observed brightness indicates how severely satellites impact celestial observations. The average magnitude for mitigated Mini spacecraft in our database is 7.1, just below the limit set by astronomers’ recommended guidelines. So, most of them are invisible to the unaided eye and do not interfere greatly with research.
Researchers discovered a potential link between "endogenous retroviruses" present in the human genome and the development of neurodegenerative diseases. Summary: Researchers discovered a potential link between “endogenous retroviruses” present in the human genome and the development of neurodegenerative diseases. Their study found that these ancient viral remnants might influence the spread of protein aggregates commonly associated with certain dementias. While these retroviruses don’t trigger neurodegeneration, they may exacerbate the disease process. This discovery offers new potential therapeutic avenues, such as suppressing gene expression or neutralizing viral proteins. Key Facts: - “Endogenous retroviruses”, ancient viral remnants in human DNA, might contribute to neurodegenerative disease progression.
- HERV-W and HERV-K, two such retroviruses, were found to aid in the transport of tau aggregates, protein clumps associated with diseases like Alzheimer’s.
- Potential therapeutic approaches include suppressing the retroviruses or neutralizing their proteins, possibly with antibodies.
Source: DZNE Genetic remnants of viruses that are naturally present in the human genome could affect the development of neurodegenerative diseases. Researchers at DZNE come to this conclusion on the basis of studies on cell cultures. They report on this in the journal Nature Communications. In their view, such “endogenous retroviruses” could contribute to the spread of aberrant protein aggregates – hallmarks of certain dementias – in the brain. Thus, these viral relicts would be potential targets for therapies. It has been suspected for some time that viral infections contribute to the genesis and development of neurodegenerative diseases. Laboratory studies by DZNE scientists now suggest a mechanism that, although related to viruses, does not require infection by external pathogens. According to this study, the culprits would be “endogenous retroviruses” that are naturally present in the human genome. “During evolution, genes from numerous viruses have accumulated in our DNA. Most of these gene sequences are mutated and normally muted,” explained Ina Vorberg, research group leader at DZNE and a professor at the University of Bonn. “However, there is evidence that endogenous retroviruses are activated under certain conditions and contribute to cancer and neurodegenerative diseases. Indeed, proteins or other gene products derived from such retroviruses are found in the blood or tissue of patients.” Experiments with Tau Aggregates Vorberg followed this trail together with colleagues from Bonn and Munich. Using cell cultures, the researchers simulated the situation in which human cells produce certain proteins from the envelope of endogenous retroviruses. Specifically, this involved HERV-W and HERV K – both viruses are present in the human genome but are usually dormant. However, studies indicate that HERV-W is activated in multiple sclerosis and HERV-K in the neurological disease “amyotrophic lateral sclerosis” (ALS) and in frontotemporal dementia (FTD). Now, Vorberg’s team found that the viral proteins facilitate the transport of so-called tau aggregates from cell to cell. “Tau aggregates” are tiny protein clumps that occur in the brains of people affected by certain neurodegenerative diseases – these include Alzheimer’s disease and FTD. “Certainly, conditions in the brain are much more complex than our cellular model system can replicate them. Nevertheless, our experiments show that endogenous retroviruses can influence the spread of tau aggregates between cells,” Vorberg said. “Endogenous retroviruses would thus not be triggers of neurodegeneration, but could fuel the disease process once it is already underway.” Viral Transport Mediators The current research and earlier studies by Vorberg’s team suggest that viral proteins serve as transport mediators for tau aggregates because they insert into the cell membrane and into the membrane of so-called extracellular vesicles: These are small fat bubbles that are naturally secreted by cells. “For the transport of tau aggregates from cell to cell, we see two pathways in particular. Transfer between cells that are in direct contact, and transport within vesicles that act as cargo capsules, so to speak, and pass from one cell to another to eventually merge with it,” Vorberg explained. “In both scenarios, membranes have to fuse. Proteins from the envelope of viruses can promote this process. That’s because many viruses are adapted to fuse with host cells. “This happens by means of special proteins that viruses carry on their surfaces. If precisely these proteins are incorporated into the cell membrane and the membrane of extracellular vesicles, it is understandable that the tau aggregates then spread more easily.” Starting Points for Therapy In the course of the natural aging process, the regulation of genes can change – originally “dormant” endogenous retroviruses could be “awakened” as a result. Indeed, the symptoms of most neurodegenerative diseases do not manifest until older age. This raises two conceivable approaches to therapy. “On the one hand, one could try to specifically suppress gene expression, that is, to inactivate the endogenous retroviruses again. That would get to the root of the problem,” Vorberg said. “But you could also start elsewhere and try to neutralize the viral proteins – for example, with antibodies.” Searching for Antibodies In the opinion of the researchers, it is likely that dementia patients with tau aggregates carry increased amounts of such antibodies. If it were possible to isolate these and reproduce them using biotechnological methods, it might be possible to develop a passive vaccine. Thus, in collaboration with DZNE colleagues in Berlin and Bonn, Vorberg’s team aims to specifically search for such antibodies in patients. In addition, the scientists are considering antiviral drugs. In cell culture, they have already found that such agents can actually stop the spread of protein aggregates. “This is another approach we intend to pursue,” said Vorberg. Research cited published in Nature (Aug. 18, 2023): https://doi.org/10.1038/s41467-023-40632-z
Via Juan Lama
The poisonous birds inhabit one of Earth’s most pristine rainforests, a place as exotic as no other in the world. Hearing the words poisonous and bird coupled will be an eye-opener for most. But poisonous birds actually exist. And now, more species have been discovered in New Guinea’s jungles.
"We managed to identify two new species of poisonous birds on our most recent trip. These birds contain a neurotoxin that they can both tolerate and store in their feathers," says Knud Jønsson of the Natural History Museum of Denmark.
Jønsson and fellow UCPH researcher, Kasun Bodawatta have been on an Indiana Jones-like research trip, risking life and limb to regularly warring tribespeople and ex-cannibals amidst the jaw-dropping biodiversity of New Guinea’s rainforest. Here they captured two new bird species, each of which has developed the ability to consume toxic food and turn that into a poison of their own.
The other new poisonous bird discovered is the The regent whistler (Pachycephala schlegelii). The two birds that the researchers discovered to be poisonous are the regent whistler (Pachycephala schlegelii), a species that belongs to a family of birds with a wide distribution and easily recognizable song well-known from across the Indo-Pacific region, and the rufous-naped bellbird (Aleadryas rufinucha).
"We were really surprised to find these birds to be poisonous as no new poisonous bird species has been discovered in over two decades. Particularly, because these two bird species are so common in this part of the world," says Knud Jønsson.
Neurotoxin causes muscle spasms
Most people are familiar with South and Central America’s iconic poison dart frogs – especially the golden poison frog. These small, brightly colored amphibians can kill a human at the slightest touch. The discovery of the two new poisonous bird species in New Guinea, which carry the same type of toxin in their skin and feathers, demonstrates that the frog toxin is more widespread than once believed.
The name Batrachotoxin comes from the Greek word for frog – Batrachos – and therefore means frog toxin. It earned its name after being discovered in poison dart frogs. It is one of the most powerful known neurotoxins and 250 times more toxic than strychnine.
Batrachotoxin works by forcing sodium channels in skeletal muscles to lock in an open position. This causes muscles to go into extreme spasm and can lead to death.
The new UCPH research demonstrates that animals which adapt to the toxin probably require changes in the voltage-gated sodium (NaV) channels where the toxin binds. The birds have mutations in the same areas as golden poison frog, but the specific changes are different.
The poison in these birds’ bodies and plumage is called Batrachotoxin. It is an incredibly potent neurotoxin that, in higher concentrations, such as those found in the skin of golden poison frogs, leads to muscle cramps and cardiac arrest nearly immediately after contact.
"The bird’s toxin is the same type as that found in frogs, which is a neurotoxin that, by forcing sodium channels in skeletal muscle tissue to remain open, can cause violent convulsions and ultimately death," explains Kasun Bodawatta.
The OncoNPC machine-learning model may help identify sites of origin for cancers whose origins are unknown, which could enable targeted tumor treatments. For a small percentage of cancer patients, doctors are unable to determine where their cancer originated. This makes it much more difficult to choose a treatment for those patients, because many cancer drugs are typically developed for specific cancer types. A new approach developed by researchers at MIT and Dana-Farber Cancer Institute may make it easier to identify the sites of origin for those enigmatic cancers. Using machine learning, the researchers created a computational model that can analyze the sequence of about 400 genes and use that information to predict where a given tumor originated in the body. Using this model, the researchers showed that they could accurately classify at least 40 percent of tumors of unknown origin with high confidence, in a dataset of about 900 patients. This approach enabled a 2.2-fold increase in the number of patients who could have been eligible for a genomically guided, targeted treatment, based on where their cancer originated. “That was the most important finding in our paper, that this model could be potentially used to aid treatment decisions, guiding doctors toward personalized treatments for patients with cancers of unknown primary origin,” says Intae Moon, an MIT graduate student in electrical engineering and computer science who is the lead author of the new study. Alexander Gusev, an associate professor of medicine at Harvard Medical School and Dana-Farber Cancer Institute, is the senior author of the paper, which appears today in Nature Medicine.
Important ocean currents that redistribute heat, cold and precipitation between the tropics and the northernmost parts of the Atlantic region will shut down around the year 2060 if current greenhouse gas emissions persist. This is the conclusion based on new calculations from the University of Copenhagen that contradict the latest report from the IPCC. Contrary to what we may imagine about the impact of climate change in Europe, a colder future may be in store. In a new study, researchers from the University of Copenhagen's Niels Bohr Institute and Department of Mathematical Sciences predict that the system of ocean currents which currently distributes cold and heat between the North Atlantic region and tropics will completely stop if we continue to emit the same levels of greenhouse gases as we do today. Using advanced statistical tools and ocean temperature data from the last 150 years, the researchers calculated that the ocean current, known as the Thermohaline Circulation or the Atlantic Meridional Overturning Circulation (AMOC), will collapse -- with 95 percent certainty -- between 2025 and 2095. This will most likely occur in 34 years, in 2057, and could result in major challenges, particularly warming in the tropics and increased storminess in the North Atlantic region. "Shutting down the AMOC can have very serious consequences for Earth's climate, for example, by changing how heat and precipitation are distributed globally. While a cooling of Europe may seem less severe as the globe as a whole becomes warmer and heat waves occur more frequently, this shutdown will contribute to an increased warming of the tropics, where rising temperatures have already given rise to challenging living conditions," says Professor Peter Ditlevsen from the Niels Bohr Institute. "Our result underscores the importance of reducing global greenhouse gas emissions as soon as possible," says the researcher. The calculations, just published in the scientific journal, Nature Communications, contradict the message of the latest IPCC report, which, based on climate model simulations, considers an abrupt change in the thermohaline circulation very unlikely during this century. Early warning signals already present The researchers' prediction is based on observations of early warning signals that ocean currents exhibit as they become unstable. These Early Warning Signals for the Thermohaline Circulation have been reported previously, but only now has the development of advanced statistical methods made it possible to predict just when a collapse will occur.
The animal is a previously unknown species that may help researchers unlock secrets of surviving harsh environments. A female microscopic roundworm that spent the last 46,000 years in suspended animation deep in the Siberian permafrost was revived and started having babies in a laboratory dish. By sequencing the genome of this Rip Van Winkle roundworm, scientists revealed it to be a new species of nematode, which is described in a study published Thursday in the journal PLOS Genetics. Nematodes today are among the most ubiquitous organisms on Earth, inhabiting the soil, the water and the ocean floor. “The vast majority of nematode species have not been described,” William Crow, a nematologist at the University of Florida who was not involved in the study, wrote in an email. The ancient Siberian worm could be a species that has since gone extinct, he said. “However, it very well could be a commonly occurring nematode that no one got around to describing yet." Published in Plos Genetics (July 27, 2023): https://doi.org/10.1371/journal.pgen.1010798
Via Juan Lama
Google is testing a tool that uses AI to write news stories and has started pitching it to publications, according to a new report from The New York Times. The tech giant has pitched the AI tool to The New York Times, The Washington Post and The Wall Street Journal’s owner, News Corp. The tool, internally codenamed “Genesis,” can take in information and then generate news copy. Google reportedly believes that the tool can serve as a personal assistant for journalists by automating some tasks in order to free up time for others. The tech giant sees the tool as a form of “responsible technology.” The New York Times reports that some executives who were pitched on the tool saw it as “unsettling,” noting that it seemed to disregard the effort that went into producing accurate news stories. “In partnership with news publishers, especially smaller publishers, we’re in the earliest stages of exploring ideas to potentially provide AI-enabled tools to help journalists with their work,” a Google spokesperson said in a statement to TechCrunch. “For instance, AI-enabled tools could assist journalists with options for headlines or different writing styles,” the spokesperson added. “Our goal is to give journalists the choice of using these emerging technologies in a way that enhances their work and productivity, just like we’re making assistive tools available for people in Gmail and in Google Docs. Quite simply these tools are not intended to, and cannot, replace the essential role journalists have in reporting, creating, and fact-checking their articles.” The report comes as several news organizations, including NPR and Insider, have notified employees that they intend to explore how AI could responsibly be used in their newsrooms. Some news organizations, including The Associated Press, have long used AI to generate stories for things like corporate earnings, but these news stories represent a small fraction of the organization’s articles overall, which are written by journalists.
Are we on the brink of an AI apocalypse? According to a recent survey, most U.S. citizens share Elon Musk’s concerns about the potential threat artificial intelligence poses to humanity’s future. What a poll shows: A majority of Americans, 61% to be exact, believe that the fast-paced growth of AI could endanger the future of humanity and over two-thirds expressed concerns about its potential negative impacts, reported Reuters, citing a survey conducted by Ipsos. As per the findings, the proportion of U.S. citizens who anticipate negative consequences from AI is three times higher than those who don’t, with 61% of the 4,415 adults surveyed expressing concerns over the potential hazard of AI and only 22% disagreeing. Rest 17% of the people were uncertain. The aforementioned online survey included 4,415 U.S. adults and has a credible interval with a margin of error of plus or minus two percentage points, the report stated. Why It’s Important: Landon Klein, director of U.S. policy of the Future of Life Institute, which is behind the “open letter” demanding a six-month pause in AI research “more powerful” than OpenAI’s GPT-4, said that the poll’s findings show that “a broad swath of Americans worry about the negative effects of AI,” the report noted. “We view the current moment similar to the beginning of the nuclear era, and we have the benefit of public perception that is consistent with the need to take action.” Musk, who co-founded OpenAI in 2015, along with Apple co-founder Steve Wozniak and over 1000 others, signed an open letter. Although Musk’s intention behind signing the letter has been questioned, considering the tech billionaire’s plans to launch his own chatGPT-rival called “TruthGPT.” Benzinga research has found that the exponential growth of OpenAI’s chatGPT has made AI a ubiquitous part of everyday life, leading to a surge of interest in the field and sparking an AI arms race between tech giants like Microsoft Corporation and Alphabet Inc., eager to showcase their own AI breakthroughs. In May 2023, Geoffrey Hinton, who recently left his job at Google citing the need to talk more freely about the risks posed by AI, stated that risks posed by AI to humanity could be more pressing than those of climate change. However, others like the godfather of virtual reality, Jaron Lanier, Bill Gates and Jürgen Schmidhuber have a different view and disagree with the sentiment.
Recently, researchers have published an important white paper identifying activities in particle physics where burgeoning quantum-computing technologies could be applied. The paper, authored by experts from CERN, DESY, IBM Quantum and over 30 other organisations, is now available on ArXiv. With quantum-computing technologies rapidly improving, the paper sets out where these could be applied within particle physics, in order to help tackle computing challenges related not only to the Large Hadron Collider’s ambitious upgrade program, but also to other colliders and low energy experiments world-wide. The paper was produced by a working group set up at the first-of-its-kind “QT4HEP” conference, held at CERN last November. Over the last eight months, the 46 people in this working group have worked hard to identify areas where quantum-computing technologies could provide a significant boon. The areas identified relate to both theoretical and experimental particle physics. The paper then maps these areas to “problem formulations” in quantum computing. This is an important step in ensuring that the particle physics community is well positioned to benefit from the massive potential of breakthrough new quantum computers when they come online. “Quantum computing is very promising, but not every problem in particle physics is suited to this mode of computing,” says Alberto Di Meglio, head of the CERN Quantum Technology Initiative (CERN QTI). “It’s important to ensure that we are ready and that we can accurately identify the areas where these technologies have the potential to be most useful for our community.” In terms of theoretical particle physics, the authors identify promising areas related to evolution of the quantum states, lattice-gauge theory, neutrino oscillations, and quantum field theories in general as well. The considered applications include quantum dynamics, hybrid quantum/classical algorithms for static problems in lattice gauge theory, optimisation, and classification. The lead authors of the paper CERN QTI’s Alberto Di Meglio, DESY’s Karl Jansen, and IBM Quantum’s Ivano Tavernelli, state that “with quantum computing we address problems in those areas that are very hard – or even impossible to tackle with classical methods. “In this way,” Jansen says, “we can explore the physical systems to which we still do not have access.” On the experimental side, the authors identify areas related to jet and track reconstruction, extraction of rare signals, for-and-beyond Standard Model problems, parton showers, and experiment simulation. These are then mapped to classification, regression, optimisation, and generation problems. Members of the working group behind this paper will now begin a process of selecting specific use cases from the activities listed in the paper to be taken forward through the CERN’s and DESY’s participation in the IBM Quantum Network, and collaboration with IBM Quantum, under its “100x100 Challenge”. IBM Quantum is long-standing collaborator to CERN QTI and the Center for Quantum Technologies and Applications (CQTA) at DESY.
The lunar gene bank - which could also house seed and spore samples - is envisaged as being built under the lunar surface, in a hollow, cooled lava tube. Extinction insurance for planet earth is envisioned by sending sperm and egg samples from 6.7 million species to the moon for safekeeping. How could earth species be destroyed to require a “backup”? - To protect Earth’s species diversity, we presently store genetic material in vaults
- Material including seeds and spores could be used to recover lost species
- But gene banks on Earth are vulnerable to the catastrophes they insure against
- US experts propose to more safely store specimens in lava tubes on the moon
- The deposits would be cryogenically frozen and tended by levitating robots
The lunar gene bank — which could also house seed and spore samples — is envisaged as being built under the lunar surface, in a hollow, cooled lava tube. Specimens deposited in the ark would be kept refrigerated at cryogenic temperatures, with the facility powered by solar panels on the lunar surface. The ark would preserve Earth’s genetic diversity in the event of a global catastrophe, such as might be caused by climate change, a supervolcano or an asteroid impact. Earth is naturally a volatile environment,’ said study author and mechanical engineer Jekan Thanga of the University of Arizona. ‘As humans, we had a close call about 75,000 years ago with the Toba supervolcano eruption, which caused a 1,000-year cooling period and, according to some, aligns with an estimated drop in human diversity,’ he added. ‘Because human civilization has such a large footprint, if it were to collapse, that could have a negative cascading effect on the rest of the planet.’ The idea of creating gene banks to restore lost biodiversity in the future is not new — more than a million seed samples are currently stored in the Svalbard Global Seed Vault on the island of Spitsbergen in the Artic Sea, for example. However, Professor Thanga and colleagues explained that locating such facilities on Earth leaves them also vulnerable to accidental loss. Climate change, for example, has the potential to push many species into terminal decline in the future — and, at the same time, the rising sea levels which will accompany global warming will see the Svalbard vault lost beneath the waves. Removed but still accessible, the moon may present a safer location. Building a genetic storage facility on the moon would be a significant undertaking — but one that Professor Thanga says would be possible. Read full story here…
A scorching hot world where metal clouds rain drops of titanium and other metals has been designated as the most reflective planet ever observed outside of our Solar System by astronomers. Key points: - The side of exoplanet LTT9779b facing its star reaches 2,000 degrees Celsius
- This helps it form metallic clouds that act like a shield and reflects 80 per cent of light
- Scientists say this also prevents its atmosphere from being blown away, defying the odds
This strange world, which is more than 260 light years from Earth, reflects 80 per cent of the light from its host star, according to new observations from Europe's exoplanet-probing Cheops space telescope. That makes it the first exoplanet comparably as shiny as Venus, which is the brightest object in our night sky other than the Moon. First discovered in 2020, the Neptune-sized planet called LTT9779b orbits its host star in just 19 hours. Because it is so close, the side of the planet facing its star is a sizzling 2,000˚C, which is considered far too hot for clouds to form. Yet LTT9779b seems to have plenty of them. "It was really a puzzle," said Vivien Parmentier, a researcher at France's Cote d'Azur Observatory and co-author of a new study in the journal Astronomy and Astrophysics. The researchers then "realized we should think about this cloud formation in the same way as condensation forming in a bathroom after a hot shower," he said in a statement. Like running hot water steams up a bathroom, a scorching stream of metal and silicate — the mineral of which glass is made — oversaturated LTT9779b's atmosphere until metallic clouds formed, he said. These clouds "act like a mirror," reflecting away light, according to the European Space Agency's Cheops project scientist Maximilian Guenther.
Creating new drug candidates is a heroic endeavor, often taking over 10 years to bring a drug to market. New supercomputing-scale large language models (LLMs) that understand biology and chemistry text are helping scientists understand proteins, small molecules, DNA, and biomedical text. These state-of-the-art AI models help generate de novo proteins and molecules and predict the 3D structures of proteins. They can predict the binding structure of a small molecule to a protein and are offering scientists easier ways to engineer new candidate drugs and ultimately bring hope for patients. After Exscientia brought an AI-designed drug candidate to a clinical trial in 2021, several other companies have announced that their candidates are in trials. Within drug companies focused on AI-based discovery, there is publicly available information on about 160 discovery programs, of which 15 products are reportedly in clinical development. At the forefront of AI-based drug discovery are generative AI models for applications such as generating high-quality proteins. These large, powerful models learn from unlabeled data (such as sequencing data) on multi-GPU, multi-node, high-performance computing (HPC) infrastructures. With the novel NVIDIA BioNeMo Service, workflows for generative AI for biology are optimized and turnkey. You can focus on adapting AI models to the right drug candidates instead of dealing with configuration files and setting up supercomputing infrastructure. BioNeMo Service BioNeMo Service is a cloud service for generative AI in early drug discovery, featuring nine state-of-the-art large language and diffusion models in one place. The models in BioNeMo are accessible through a web interface or fully managed APIs and can be further trained and optimized on NVIDIA DGX Cloud. With BioNeMo Service, you can perform any of the following tasks: - Generate large libraries of proteins.
- Build property predictors using embeddings to refine protein libraries.
- Generate small molecules with specific properties.
- Rapidly and accurately predict and visualize the 3D structure for billions of proteins.
- Run large campaigns of ligand-to-small-molecule pose estimations.
- Download proteins, molecules, and predicted 3D structures.
Generative AI models in BioNeMo Service BioNeMo Service features nine AI generative models covering a wide spectrum of applications for developing AI drug discovery pipelines: - AlphaFold 2, ESMFold, and OpenFold for 3D protein structure prediction from a primary amino acid sequence
- ESM-1nv and ESM-2 for protein property predictions
- ProtGPT2 for protein generation
- MegaMolBART and MoFlow for small molecule generation
- DiffDock for predicting the binding structure of a small molecule to a protein
While paper isn’t exactly a smart material, it someday could be if it is covered in a new type of liquid metal. This liquid alloy has the potential to turn paper and other materials into gadgets that can do some things on their own. Liquid metal is already used in smart objects like circuits and wearable sensors—but not as a coating. Inspired by origami, a team of scientists led by Bo Yuan of Tsinghua University in China has figured out a way to formulate liquid metal and apply it with a stamp so it sticks to paper without an adhesive, which has never been possible before. In a study recently published in Cell Reports Physical Science, the scientists showed that paper coated in the metal can be crafted into origami shapes and re-fold itself. The metal coating also conducts heat and electricity. It’s like magic. Almost. A sticky alloy Because the particles in liquid metal tend to stay so close together, it is difficult to get it to adhere to any surface without something that acts as glue. But these adhesives usually have a negative effect on the metal’s properties, such as its conductivity. Yuan and his team wanted a liquid metal that could stick to paper without an adhesive. They used an alloy of bismuth, indium, and tin oxide (BiInSn) and tested how well it performed next to an indium/gallium alloy (eGaIn). BiInSn turned out to be more effective. Unlike eGaIn, it doesn’t oxidize when exposed to air, so how well it sticks to a surface does not depend on the oxide film that forms on the metal. BiInSn is a solid at room temperature and has a higher melting point, so there is no risk of it liquefying at temperatures under 62° Celsius (about 144° Fahrenheit). It is also capable of stronger adhesion. However, getting optimal adhesion out of BiInSn required trial and error. “We needed to ensure the adhesion of liquid metal to be uniform in large scale on different paper, and to maintain the stability of the coating,” Yuan told Ars Technica in an email interview. “To solve these problems, we changed pressure applied on the stamp as well as the rubbing speed used in the experiments and finally found the most suitable parameters, which finally achieved fast, large-scale, and stable adhesion.” The researchers tried stamping it onto paper with different amounts of pressure and found out that not much is needed for it to stay in place. They then created an origami cube out of the metal-coated paper, which required the edges to adhere to each other without any other binding agent. They even saw that when that square was unfolded, the coated paper could fold itself back into its original shape. Because the metal coating was self-adhesive, the edges that had been unfolded attracted each other until the paper became a cube again. Another shape they tried was a spring that could be stretched or compressed and would remain however it was adjusted. It was also possible for the team to build 3D structures out of individual pieces of flat, metal-coated paper. These structures could keep their shape without falling apart, and the coating could just be peeled off afterward without affecting the properties of its paper substrate in any way. The coating, which also lost none of its properties, could be recycled and used repeatedly. The paper just went back to being paper. Next steps Yuan thinks self-adhesion through liquid metal is an advantage, because, if it can be done with paper, it could be done with other thin, lightweight materials to create smart objects and soft robots that can fit into tight spaces. The next thing he wants to accomplish is finding a coating where the metal does not peel off once solidified. He is considering testing bio-friendly paint spray to protect the coating in materials that may eventually be used as packaging (boxes could open and close themselves just like the paper cube in the experiment), on human skin (bandages would come off painlessly without glue), underwater, and even in conditions seen on other planets and moons. This substance could possibly be an asset to soft robots in alien environments. Some soft robots can already explore the deepest reaches of the ocean where the pressure is too high for humans and the cracks and crevices too small for larger machines. Soft robots are being designed with an eye for subsurface tunnels on Mars and other bodies in space. Autonomous soft robots that are thin and flexible would be able to venture into places where larger rovers are unable to fit or navigate safely, and the self-adhesion of the liquid metal coating would allow them to fold and unfold on their own. “Utilizing our method, one can quickly create smart materials with good thermal and electrical conductivity as well as stiffness-tunable ability, which greatly expands material options for soft robots,” Yuan said in the interview. “I think that this method may provide a new route for designing space explorers." Cell Reports Physical Science, 2023. DOI: 10.1016/j.xcrp.2023.101419 (About DOIs).
|
An autonomous drone has competed against human drone-racing champions — and won. The victory can be attributed to savvy engineering and a type of artificial intelligence that learns mostly through trial and error. First-person view (FPV) drone racing is a televised sport in which professional competitors pilot high-speed aircraft through a 3D circuit. Each pilot sees the environment from the perspective of their drone by means of video streamed from an onboard camera. Reaching the level of professional pilots with an autonomous drone is challenging because the robot needs to fly at its physical limits while estimating its speed and location in the circuit exclusively from onboard sensors. Here the authors of this paper introduce Swift, an autonomous system that can race physical vehicles at the level of the human world champions. The system combines deep reinforcement learning (RL) in simulation with data collected in the physical world. Swift competed against three human champions, including the world champions of two international leagues, in real-world head-to-head races. Swift won several races against each of the human champions and demonstrated the fastest recorded race time. This work represents a milestone for mobile robotics and machine intelligence, which may inspire the deployment of hybrid learning-based solutions in other physical systems. An autonomous system is described that combines deep reinforcement learning with onboard sensors collecting data from the physical world, enabling it to fly faster than human world champion drone pilots around a race track.
National Supercomputing Center in Wuxi builds a yet another supercomputer that claims exascale performance. After the U.S. government imposed crippling sanctions against select Chinese high-tech and supercomputer companies through 2019 and 2020, firms like Huawei had to halt chip development; it is impossible to build competitive processors without access to leading-edge nodes. But Jiangnan Computing Lab, which develops Sunway processors, and National Supercomputing Center in Wuxi kept building new supercomputers and recently even submitted results of their latest machine for the Association for Computing Machinery's Gordon Bell prize. The new Sunway supercomputer built by the National Supercomputing Center in Wuxi (an entity blacklisted in the U.S.) employs around feature approximately 19.2 million cores across 49,230 nodes, reports Supercomputing.org. To put the number into context, Frontier, the world's highest-performing supercomputer, uses 9472 nodes and consumes 21 MW of power. Meanwhile, the National Supercomputing Center in Wuxi does not disclose power consumption of its latest system. Interestingly, the new supercomputer seems to be based on the already known 390-core Sunway processor that derive from the Sunway SW26010 CPUs and have been around since 2021. Therefore, the new system increased the number of processors, but not their architectural efficiency, so its power consumption is likely to be gargantuan. Meanwhile, actual performance of the machine is unknown, since scaling out has its limits even in the supercomputer world. The National Supercomputing Center in Wuxi has not disclosed performance numbers of its new supercomputer, and it is hard to make any estimations about its performance at this point. The reason why we called it ‘exascale’ is because its predecessor, the Sunway Oceanlite from 2021, was estimated to offer compute performance of around 1 ExaFLOPS. Meanwhile, engineers revealed the workload that it used the machine for. Apparently, the the group created a new code for large whirlpool simulations to address compressible currents in turbo machinery. They applied it to NASA’s grand challenge problem using an advanced unstructured solver for a high-pressure turbine sequence with 1.69 billion mesh components and 865 billion degrees of freedom (judged by the number of variables). Given how complex the simulation is, it is likely that the machine is indeed quite powerful. Meanwhile, there is no word whether the simulation was conducted with FP64 precision, or precision was sacrificed for the sake of performance.
Moderna's newest vaccine and new shots from Pfizer and Novavax are slated to roll out within weeks, pending potential approvals from the Food and Drug Administration. Moderna’s newest Covid vaccine generated a robust immune response against the now-dominant Eris variant and another rapidly spreading strain of the virus in an early clinical trial, the biotech company recently stated. The updated shot is designed to target omicron subvariant XBB.1.5, but the results suggest that the injection may still be effective against newer variants of the virus that are gaining ground nationwide. That includes Eris and another variant nicknamed Fornax, both of which are also descendants of the omicron virus variant. Moderna’s vaccine and new shots from Pfizer and Novavax are slated to roll out within weeks, pending potential approvals from the U.S. Food and Drug Administration. Meanwhile, Covid-related hospitalizations fueled by Eris and other variants continue to accelerate but remain below the summer peak that strained hospitals this time last year. Eris, also known as EG.5, accounted for 17.3% of all cases as of earlier this month, according to the Centers for Disease Control and Prevention. The World Health Organization designated Eris a “variant of interest,” meaning it will be monitored for mutations that could make it more severe. Fornax, or FL 1.5.1, is also beginning to surge in parts of t he U.S. It accounted for 8.6% of all cases nationwide as of earlier this month, the CDC said. A Pfizer spokesperson on Thursday said the company’s own updated Covid shot effectively neutralized XBB.1.5 and Eris, among other variants, in a recent trial on mice.
Via Juan Lama
Creating brain-like computers with minimal energy requirements would revolutionize nearly every aspect of modern life. Funded by the Department of Energy, Quantum Materials for Energy Efficient Neuromorphic Computing ( Q-MEEN-C) — a nationwide consortium led by the University of California San Diego — has been at the forefront of this research. UC San Diego Assistant Professor of Physics Alex Frañó is co-director of Q-MEEN-C and thinks of the center’s work in phases. In the first phase, he worked closely with President Emeritus of University of California and Professor of Physics Robert Dynes, as well as Rutgers Professor of Engineering Shriram Ramanathan. Together, their teams were successful in finding ways to create or mimic the properties of a single brain element (such as a neuron or synapse) in a quantum material. Now, in phase two, new research from Q-MEEN-C, published in Nano Letters, shows that electrical stimuli passed between neighboring electrodes can also affect non-neighboring electrodes. Known as non-locality, this discovery is a crucial milestone in the journey toward new types of devices that mimic brain functions known as neuromorphic computing. Like many research projects now bearing fruit, the idea to test whether non-locality in quantum materials was possible came about during the pandemic. Physical lab spaces were shuttered, so the team ran calculations on arrays that contained multiple devices to mimic the multiple neurons and synapses in the brain. In running these tests, they found that non-locality was theoretically possible. "In the brain it’s understood that these non-local interactions are nominal — they happen frequently and with minimal exertion,” stated Frañó, one of the paper’s co-authors. “It’s a crucial part of how the brain operates, but similar behaviors replicated in synthetic materials are scarce. When labs reopened, they refined this idea further and enlisted UC San Diego Jacobs School of Engineering Associate Professor Duygu Kuzum, whose work in electrical and computer engineering helped them turn a simulation into an actual device. This involved taking a thin film of nickelate — a “quantum material” ceramic that displays rich electronic properties — inserting hydrogen ions, and then placing a metal conductor on top. A wire is attached to the metal so that an electrical signal can be sent to the nickelate. The signal causes the gel-like hydrogen atoms to move into a certain configuration and when the signal is removed, the new configuration remains.
Maya Bodnick, a student at Harvard University, conducted an experiment to determine if GPT-4, an AI language model, was capable of passing college exams in the humanities and social sciences. Bodnick had GPT-4 write seven essays on topics such as economic concepts, presidentialism in Latin America, and a literary analysis. She then submitted the essays to professors for grading, without revealing whether they were written by herself or GPT-4. The results were impressive, with GPT-4 receiving grades ranging from A to B-. It achieved an average GPA of 3.57, which Bodnick called “respectable.” She noted that GPT-4 wrote all the essays based on the given prompts. Bodnick disclosed that she submitted GPT-4’s answers without any edits, but with two exceptions. First, she combined multiple responses to meet the word count requirement, as GPT-4 could only generate up to 750 words at a time. Second, she asked the evaluators to disregard any missing citations that GPT-4 couldn’t provide, which would normally be essential for academic work. The evaluators praised GPT-4’s essays, commenting on their clarity, well-structured arguments, and detailed analysis. Only one essay received a lower grade, with the evaluator noting a flowery writing style and a lack of consideration for positive aspects of presidentialism and economic factors. Bodnick believes that GPT-4’s performance suggests AI-generated essays could receive favorable grades at most universities, though possibly lower at institutions such as Princeton or UC Berkeley. She suggests that AI technology could revolutionize the teaching and learning methods in the humanities and social sciences. Cheating on essays has become easier, and with advancements in technology, including citation capabilities, it may become even more challenging to detect plagiarism. As for the future, Bodnick questions the effectiveness of text detection systems, as OpenAI’s detector was withdrawn due to accuracy issues. She suggests that exams should involve personal conversations to mitigate concerns about AI writing essays. The fact that GPT-4 passed her exams hints at potential developments in Bodnick’s future field.professional field.
New research from UM and its partners suggests artificial intelligence can match the top 1% of human thinkers on a standard test for creativity. The study was directed by Dr. Erik Guzik, an assistant clinical professor in UM's College of Business. He and his partners used the Torrance Tests of Creative Thinking, a well-known tool used for decades to assess human creativity. The researchers submitted eight responses generated by ChatGPT, the application powered by the GPT-4 artificial intelligence engine. They also submitted answers from a control group of 24 UM students taking Guzik's entrepreneurship and personal finance classes. These scores were compared with 2,700 college students nationally who took the TTCT in 2016. All submissions were scored by Scholastic Testing Service, which didn't know AI was involved. The results placed ChatGPT in elite company for creativity. The AI application was in the top percentile for fluency -- the ability to generate a large volume of ideas -- and for originality -- the ability to come up with new ideas. The AI slipped a bit -- to the 97th percentile -- for flexibility, the ability to generate different types and categories of ideas. "For ChatGPT and GPT-4, we showed for the first time that it performs in the top 1% for originality," Guzik said. "That was new." He was gratified to note that some of his UM students also performed in the top 1%. However, ChatGTP outperformed the vast majority of college students nationally. Guzik tested the AI and his students during spring semester. He was assisted in the work by Christian Gilde of UM Western and Christian Byrge of Vilnius University. The researchers presented their work in May at the Southern Oregon University Creativity Conference. "We were very careful at the conference to not interpret the data very much," Guzik said. "We just presented the results. But we shared strong evidence that AI seems to be developing creative ability on par with or even exceeding human ability." Guzik said he asked ChatGPT what it would indicate if it performed well on the TTCT. The AI gave a strong answer, which they shared at the conference: "ChatGPT told us we may not fully understand human creativity, which I believe is correct," he said. "It also suggested we may need more sophisticated assessment tools that can differentiate between human and AI-generated ideas." He said the TTCT is protected proprietary material, so ChatGPT couldn't "cheat" by accessing information about the test on the internet or in a public database. Guzik has long been interested in creativity. As a seventh grader growing up in the small town of Palmer, Massachusetts, he was in a program for talented-and-gifted students. That experience introduced him to the Future Problem Solving process developed by Ellis Paul Torrance, the pioneering psychologist who also created the TTCT. Guzik said he fell in love with brainstorming at that time and how it taps into human imagination, and he remains active with the Future Problem Solving organization -- even meeting his wife at one of its conferences.
Large language models (LLMs) and Vision-Language Models (VLMs) have been proven to excel at multiple tasks, such as commonsense reasoning. Powerful as these models can be, they are not grounded in the 3D physical world, which involves richer concepts such as spatial relationships, affordances, physics, layout, and so on. In this current work, researchers propose to inject the 3D world into large language models and introduce a whole new family of 3D-LLMs. Specifically, 3D-LLMs can take 3D point clouds and their features as input and perform a diverse set of 3D-related tasks, including captioning, dense captioning, 3D question answering, task decomposition, 3D grounding, 3D-assisted dialog, navigation, and so on. Using three types of prompting mechanisms that they were able to design, enabled them to collect over 300k 3D-language data covering these tasks. To efficiently train 3D-LLMs, they first utilized a 3D feature extractor that obtains 3D features from rendered multi-view images. Then, they used 2D VLMs as backbones to train their 3D-LLMs. By introducing a 3D localization mechanism, 3D-LLMs can better capture 3D spatial information. Experiments on ScanQA showed that this model outperforms state-of-the-art baselines by a large margin (e.g., the BLEU-1 score surpasses state-of-the-art score by 9%). Furthermore, experiments on held-in datasets for 3D captioning, task composition, and 3D-assisted dialogue show that this model outperforms 2D VLMs. Qualitative examples also show that this model could perform more tasks beyond the scope of existing LLMs and VLMs. Project Page: : https://vis-www.cs.umass.edu/3dllm/.
The process of reconstructing experiences from human brain activity offers a unique lens into how the brain interprets and represents the world. Recently, the Google team and international collaborators introduced a method for reconstructing music from brain activity alone, captured using functional magnetic resonance imaging (fMRI). This approach uses either music retrieval or the MusicLM music generation model conditioned on embeddings derived from fMRI data. The generated music resembles the musical stimuli that human subjects experienced, with respect to semantic properties like genre, instrumentation, and mood. The scientists investigate the relationship between different components of MusicLM and brain activity through a voxel-wise encoding modeling analysis. Furthermore, they analyze which brain regions represent information derived from purely textual descriptions of music stimuli.
Signs of life beyond Earth could take forms that are clearly artificial – radio or light signals, or even evidence of large-scale engineering. Our first confirmed proof of life beyond Earth might not involve biology at all. It’s possible that we might intercept communication through electromagnetic waves, like radio, or find telescopic evidence of epic engineering. While the search remains largely focused on non-technological life, NASA scientists also have begun to consider what technological traces of intelligent life – “technosignatures” – might look like. They wouldn’t come from planets in our solar system, but rather far-flung exoplanets that we cannot see up close. Among the possibilities are laser or radio pulses, signs of artificial chemicals in the atmospheres of distant planets, or “Dyson spheres” – massive structures built around stars to collect their energy. And as acceptance in the scientific community slowly grows, a field once derided as a search for “little green men” is showing early signs of blossoming into a mature, serious investigation. “That’s something we’ve worked very hard on: to establish our legitimacy, and distance ourselves from pseudo-science,” said Jill Tarter, an astronomer known for decades as a leader in the search for intelligent life beyond Earth. “If anything, my conviction that this is an important and reasonable thing to do has increased.” Jill Tarter is the co-founder and former director of the Center for SETI (Search for Extraterrestrial Intelligence) Research at the SETI Institute, as well as the inspiration for the main character in Carl Sagan’s 1985 novel “Contact.” She says one of the biggest challenges today is moving the search for signs of technology beyond just radio signals. “We still want to look at all the sky all the time, at all wavelengths,” Tarter said, including pulses of laser light that might be used for communication. Another challenge is short-lived “transient” signals, one-time events that can be bright and energetic. Mixed among the many natural sources for such signals, like gamma-ray bursts or supernovae, might be artificial transients from distant civilizations – an engineered signal lasting less than a few minutes. But teasing them apart likely would require enormous amounts of computer time. "We’re trying to figure out how to do that,” Tarter said. “That is our focus now.” This is the fifth in a series of articles on how NASA is searching for life in the cosmos. Read Part 1 | Part 2 | Part 3 | Part 4
For the 4th time, Anumana has earned the FDA’s breakthrough device designation for another of its artificial intelligence algorithms designed to catch hard-to-spot heart conditions in their earliest stages. This time around, the FDA bestowed the label upon Anumana’s algorithm targeting cardiac amyloidosis, a condition in which abnormal tissues build up in and around the heart, making it more difficult for the heart to pump normally and potentially leading to heart failure or even death. Cardiac amyloidosis can be difficult to properly diagnose because many of its most prevalent symptoms—which include kidney inflammation, liver swelling, heart palpitations and fatigue—may be attributed to other, more common conditions. But Anumana claims to have cracked the code: Its AI tool is designed to pick up on signs of the disease that may otherwise go overlooked by doctors. Anumana developed the algorithm with support from Pfizer. The duo announced their partnership late last year, pledging to spend the next several years working together to bring the cardiac amyloidosis-spotting tech into clinics in the U.S., Europe and Japan. Like Anumana’s other AI tools, it works by scouring standard ECGs, digging into the peaks and valleys of the heart’s electrical signals to detect early indicators of the protein build-up that are typically invisible to human doctors. With the new breakthrough device label, which Anumana recently announced, the process will be somewhat fast-tracked, as the designation opens up a dedicated channel of communication between the startup and the regulator and also ensures that future applications are shuttled to the top of the agency’s pile for review. “The use of AI algorithms to identify subtle signals in ECGs that are imperceptible to humans stands to transform cardiovascular medicine by allowing us to detect disease early, in more easily treated stages, potentially avoiding serious consequences,” Paul Friedman, M.D., chair of Anumana’s Mayo Clinic board of advisors, said in the announcement. “It is encouraging to see an algorithm that can aid in the identification of cardiac amyloidosis receive breakthrough device designation, as it recognizes the importance of having new tools to detect rare cardiac diseases in ways never before possible.”
Claude.ai is pleased to announce Claude 2, their newest model, which can be accessed via API as well as a new public-facing beta website at claude.ai. They have been iterating to improve the underlying safety of Claude 2, so that it is more harmless and harder to prompt to produce offensive or dangerous output. The programmers have an internal red-teaming evaluation that scores our models on a large representative set of harmful prompts, using an automated test while we also regularly check the results manually. In this evaluation, Claude 2 was 2x better at giving harmless responses compared to Claude 1.3. Although no model is immune from jailbreaks, a variety of safety techniques (which you can read about here and here) have been employed, as well as extensive red-teaming, to improve its outputs. Claude 2 is generally available in the US and UK. Claude.ai is working to make Claude more globally available in the coming months. Interested users can now create an account and start talking to Claude in natural language, asking it for help with any tasks. Talking to an AI assistant can take some trial and error, so read up on our tips to get the most out of Claude. Claude.ai is also currently working with thousands of businesses who are using the Claude API. One of the partners is Jasper, a generative AI platform that enables individuals and teams to scale their content strategies. They found that Claude 2 was able to go head to head with other state of the art models for a wide variety of use cases, but has particular strength for long form low latency uses. "We are really happy to be among the first to offer Claude 2 to our customers, bringing enhanced semantics, up-to-date knowledge training, improved reasoning for complex prompts, and the ability to effortlessly remix existing content with a 3X larger context window," said Greg Larson, VP of Engineering at Jasper. "We are proud to help our customers stay ahead of the curve through partnerships like this one with Anthropic." Sourcegraph is a code AI platform that helps customers write, fix, and maintain code. Their coding assistant Cody uses Claude 2’s improved reasoning ability to give even more accurate answers to user queries while also passing along more codebase context with up to 100K context windows. In addition, Claude 2 was trained on more recent data, meaning it has knowledge of newer frameworks and libraries for Cody to pull from. “When it comes to AI coding, devs need fast and reliable access to context about their unique codebase and a powerful LLM with a large context window and strong general reasoning capabilities,” says Quinn Slack, CEO & Co-founder of Sourcegraph. “The slowest and most frustrating parts of the dev workflow are becoming faster and more enjoyable. Thanks to Claude 2, Cody’s helping more devs build more software that pushes the world forward.” The programmers at Claude.ai welcome user feedback as they work to responsibly deploy Claude more broadly. The chat experience is an open beta launch, and users should be aware that Claude – like all current models – can generate inappropriate responses. AI assistants are most useful in everyday situations, like serving to summarize or organize information, and should not be used where physical or mental health and well-being are involved. Please let the people at Claude.ai know if you would like to talk to Claude in a currently unsupported area, or if you are a business who would like to start working with Claude. After working for the past few months with key partners like Notion, Quora, and DuckDuckGo in a closed alpha, Claude.ai has been able to carefully test out our systems in the wild, and are ready to offer Claude more broadly so it can power crucial, cutting-edge use cases at scale. Claude is a next-generation AI assistant based on Anthropic’s research into training helpful, honest, and harmless AI systems. Accessible through chat interface and API in a developer console, Claude is capable of a wide variety of conversational and text processing tasks while maintaining a high degree of reliability and predictability.
Cal Fire, the firefighting agency in California, has embraced the power of AI in its ongoing battle against wildfires. Captain Chris Africa, stationed at the Cal Fire Emergency Command Center in Grass Valley, is at the forefront of this technological revolution. The newly installed wildfire cameras, driven by AI algorithms, generate real-time alerts whenever smoke is detected. Africa explained, "These cameras are all auto-generated and have all moved based off AI indicators." The dispatch monitors now prominently display a red box whenever the cameras identify smoke, which Africa referred to as "signatures." By clicking on the Raw AI option, he can access a comprehensive view of cameras currently detecting these signatures, indicating the potential presence of smoke or other anomalies the camera system perceives. In addition to visual detection, computers equipped with cutting-edge technology are helping predict the trajectory of wildfires by considering various factors such as topography and wind speeds. Cal Fire Battalion Chief David Krussow, based at the Grass Valley Air Attack Base, relies on computer models accessible via his smartphone. This information provides real-time updates on the fire's location and projected path, revolutionizing how firefighting operations are coordinated.
|
