Martian Meteorite Upsets Planet Formation Theory

When our solar system formed, Mars formed earlier than Earth, and its composition gives clues about early steps in planet formation. A new UC Davis study overturns previous ideas about how rocky planets form.
Credit: NASA

A new study of an old meteorite contradicts current thinking about how rocky planets like the Earth and Mars acquire volatile elements such as hydrogen, carbon, oxygen, nitrogen and noble gases as they form. The work is published June 16 in Science.

A basic assumption about planet formation is that planets first collect these volatiles from the nebula around a young star, said Sandrine Péron, a postdoctoral scholar working with Professor Sujoy Mukhopadhyay in the Department of Earth and Planetary Sciences, University of California, Davis.

Because the planet is a ball of molten rock at this point, these elements initially dissolve into the magma ocean and then degas back into the atmosphere. Later on, chondritic meteorites crashing into the young planet deliver more volatile materials.

So, scientists expect that the volatile elements in the interior of the planet should reflect the composition of the solar nebula, or a mixture of solar and meteoritic volatiles, while the volatiles in the atmosphere would come mostly from meteorites. These two sources — solar vs. meteoritic — can be distinguished by the ratios of isotopes of noble gases, in particular krypton.

Mars is of special interest because it formed relatively quickly — solidifying in about 4 million years after the birth of the solar system, while the Earth took 50 to 100 million years to form.

“We can reconstruct the history of volatile delivery in the first few million years of the solar system,” Péron said.

Can computers understand complex words and concepts?

 A depiction of semantic projection, which can determine the similarity between two words in a specific context. This grid shows how similar certain animals are based on their size.
Credit: Idan Blank/UCLA 

In “Through the Looking Glass,” Humpty Dumpty says scornfully, “When I use a word, it means just what I choose it to mean — neither more nor less.” Alice replies, “The question is whether you can make words mean so many different things.”

The study of what words really mean is ages old. The human mind must parse a web of detailed, flexible information and use sophisticated common sense to perceive their meaning.

Now, a newer problem related to the meaning of words has emerged: Scientists are studying whether artificial intelligence can mimic the human mind to understand words the way people do. A new study by researchers at UCLA, MIT and the National Institutes of Health addresses that question.

The paper, published in the journal Nature Human Behavior, reports that artificial intelligence systems can indeed learn very complicated word meanings, and the scientists discovered a simple trick to extract that complex knowledge. They found that the AI system they studied represents the meanings of words in a way that strongly correlates with human judgment.

The AI system the authors investigated has been frequently used in the past decade to study word meaning. It learns to figure out word meanings by “reading” astronomical amounts of content on the internet, encompassing tens of billions of words.

Scientists fail to locate once-common CA bumble bees

The Western bumble bee, a once-common bee in California, was not found in the recent UCR-led survey.
resized using AI by SFLORG
Credit: Rich Hatfield/Xerces Society

Several species of California bumble bees have gone missing in the first statewide census of the fuzzy pollinators in 40 years. If they can be found, a recent court ruling could help save them.

Smaller-scale studies have documented significant declines in bumble bee populations around the world due to climate change, development of wild habitat, and the use of bee-killing pesticides.

Led by UC Riverside, this study was an effort to document changes in bumble bee populations across large geographic areas in California since the last such study was done in the 1980s.

It is important to have data that substantiates the bees’ health. Bumble bees can fly in cooler temperatures and lower light levels than many other bees, and help pollinate crops worth $3 billion annually in the U.S. They perform a type of pollination required for plants including tomatoes, peppers and cranberries.

For the updated data, UCR entomologist Hollis Woodard’s research group collected bees from 17 total sites representing six different ecosystems previously known to host a large variety of bumble bees.

Molecular 3D-maps unlock new ways of studying human reproduction

The study also provides a crucial reference for fetal tissue generation in the lab - such tissue is in short supply but is needed for drug screening and studies into stem cell-based treatments to regenerate body tissues in diseases like Parkinson’s, for example.

Embryos develop from a clump of cells into highly organized structures. However, until now the signals orchestrating this transformation have remained hidden from observation inside the womb.

Measuring gene activity in three dimensions, researchers have generated molecular maps of the second week of gestation as it has never been seen before. Their work is published today in the journal Nature.

“This work will provide a definitive laboratory reference for future studies of early embryo development, and the embryonic origins of disease,” said Dr Thorsten Boroviak in the University of Cambridge’s Department of Physiology, Development and Neuroscience and senior author of the study.

The second week of gestation is one of the most mysterious, yet critical, stages of embryo development. Failure of development during this time is one of the major causes of early pregnancy loss and birth defects.

In previous work, Boroviak showed that the first week of development in marmoset monkeys is remarkably similar to that in humans. But with existing methods he could not explore week two of development, after the embryo implants into the womb.

Glimpses of Quantum Computing Phase Changes Show Researchers the Tipping Point

Tuning a quantum computer’s measurement rate provides hints of quantum phase transition

Researchers at Duke University and the University of Maryland have used the frequency of measurements on a quantum computer to get a glimpse into the quantum phenomena of phase changes – something analogous to water turning to steam.

By measuring the number of operations that can be implemented on a quantum computing system without triggering the collapse of its quantum state, the researchers gained insight into how other systems — both natural and computational — meet their tipping points between phases. The results also provide guidance for computer scientists working to implement quantum error correction that will eventually enable quantum computers to achieve their full potential.

The results appeared online in the journal Nature Physics.

When heating water to a boil, the movement of molecules evolves as the temperature changes until it hits a critical point when it starts to turn to steam. In a similar fashion, a quantum computing system can be increasingly manipulated in discrete time steps until its quantum state collapses into a single solution.

“There are deep connections between phases of matter and quantum theory, which is what’s so fascinating about it,” said Crystal Noel, assistant professor of electrical and computer engineering and physics at Duke. “The quantum computing system is behaving in the same way as quantum systems found in nature — like liquid changing to steam — even though it’s digital.”

Parasitic worms reveal new insights into the evolution of sex and sex chromosomes

Schematic picture designed by the authors: During evolution, different chromosome elements represented by the Lego bricks (NA, NB, NX..etc. in the figure) were added onto the ancestral sex chromosomes in different species, forming the great diversity of nematode sex chromosomes. These "Lego" combinations of chromosome elements are shown as corresponding colors for each ‘clade’ of nematode species.
Credit: Quzijian

Studying two highly divergent phyla of worms that contain numerous parasites that cause human and livestock diseases, the research group of Qi Zhou from the University of Vienna and Zhejiang University, sheds light on how sexual reproduction and subsequent great diversity of sex chromosomes might have evolved.

Animals or plants with separate sexes are widespread in nature, and result from independent transitions from their hermaphroditic ancestor. The actual mechanism involved in the transitions between asexual and sexual reproductive modes, in other words, how is sex originated, remains an important and unanswered question. Excluding insects, about one third of the animal species, such as earthworms, snails, and some teleosts, are hermaphroditic. A comparison with their relatives who have evolved separate sexes, might reveal, how this particular trait originated and evolved in animals.

A new paper in Nature Communications, published by Qi Zhou of Department of Neuroscience and Developmental Biology in University of Vienna and Zhejiang University in China, provides clues into how separate sexes originated and characterizes how sex chromosomes evolved in flatworms or roundworms.

NASA's Chandra Catches Pulsar in X-ray Speed Trap

G292.0+1.8: NASA's Chandra Catches Pulsar in X-ray Speed Trap
Credit: X-ray: NASA/CXC/SAO/L. Xi et al.; Optical: Palomar DSS2
Hi-Res Zoomable Image

A young pulsar is blazing through the Milky Way at a speed of over a million miles per hour. This stellar speedster, witnessed by NASA's Chandra X-ray Observatory, is one of the fastest objects of its kind ever seen. This result teaches astronomers more about how some of the bigger stars end their lives.

Pulsars are rapidly spinning neutron stars that are formed when some massive stars run out of fuel, collapse, and explode. This pulsar is racing through the remains of the supernova explosion that created it, called G292.0+1.8, located about 20,000 light-years from Earth.

"We directly saw motion of the pulsar in X-rays, something we could only do with Chandra's very sharp vision," said Xi Long of the Center for Astrophysics | Harvard & Smithsonian (CfA), who led the study. "Because it is so distant, we had to measure the equivalent of the width of a quarter about 15 miles away to see this motion."

To make this discovery, the researchers compared Chandra images of G292.0+1.8 taken in 2006 and 2016. From the change in position of the pulsar over the 10-year span, they calculated it is moving at least 1.4 million miles per hour from the center of the supernova remnant to the lower left. This speed is about 30% higher than a previous estimate of the pulsar's speed that was based on an indirect method, by measuring how far the pulsar is from the center of the explosion.

River Belt Discovery Helps Scientists Understand Ancient Rivers

A relative elevation map of the Susitna River in Alaska,
one of the 30 rivers that were mapped as part of the study.
Credit: Tian Dong.

Long after a river has dried up, its channel belt lives on.

Made up of swaths of sediment surrounding the river, channel belts, once hardened into rock, preserve the paths of rivers that once were. However, reconstructing details about an ancient river from channel belt deposits is a notoriously difficult task.

New research from scientists at The University of Texas at Austin is making progress on that front. Lead author Tian Dong, a postdoctoral researcher at the UT Jackson School of Geosciences, said that by analyzing modern rivers they have been able to come up with a rule that connects channel belts to river patterns, finding that, in general, the more channels a river has, the narrower its channel belt.

Since the physics of shaping rivers is the same over time and place, the rule should hold for ancient rivers and rivers on other planets, too, according to co-author Timothy Goudge, an assistant professor at the Jackson School.

“We can look at a river deposit from 100 million years ago on Earth or from 3.5 billion years ago on Mars and we can say something about what the actual river looked like,” he said.

The results were published in the journal Geology.

Researchers Model Accelerator Magnets' History Using Machine Learning Approach

A magnet on a test stand inside SLAC National Accelerator Laboratory. Researchers have created a machine-learning model that will help predict how magnets will perform during beam experiments, among other applications.
Credit: Scott Anderson, SLAC National Accelerator Laboratory

Knowing a magnet’s past will allow scientists to customize particle beams more precisely in the future. As accelerators stretch for higher levels of performance, understanding subtle effects, such as those introduced by magnetic history, is becoming more critical.

After a long day of work, you might feel tired or exhilarated. Either way, you are affected by what happened to you in the past.

Accelerator magnets are no different. What they went through – or what went through them, like an electric current – affects how they will perform in the future.

Without understanding a magnet’s past, researchers might need to fully reset them before starting a new experiment, a process that can take 10 or 15 minutes. Some accelerators have hundreds of magnets, and the process can quickly become time-consuming and costly.

Now a team of researchers from the Department of Energy’s SLAC National Accelerator Laboratory and other institutions have developed a powerful mathematical technique that uses concepts from machine learning to model a magnet’s previous states and make predictions about future states. This new approach eliminates the need to reset the magnets and results in improvements in accelerator performance immediately.

Bringing back native predators to tackle invasive species crisis

Source: Queen's University Belfast

Invasive species are one of the greatest threats to biodiversity globally and are the main cause for the extinction of vertebrates in the last century, with an estimated cost of at least $162 billion (USD) a year.

Native predator populations have been depleted globally, despite being essential for the functioning of the ecosystem and biodiversity. The absence of native predators facilitates the spread of invasive species leading to the extinction of native species throughout the world.

The research, published today in Global Change Biology, found that restoring native predators could provide a solution to a variety of the most damaging invasive species globally. According to the study, the evolutionary naivety of invasive species to native predators, coupled with a lack of spatial refuges from predation could underpin the abilities of native predators to provide effective control of certain established invasive species.

The research team have previously shown how the recovery of the native pine marten in the UK and Ireland has resulted in landscape-scale declines of the invasive grey squirrel. Building on this research, the team have now evaluated native predator reintroduction and restoration as a viable nature-based solution to the invasive species crisis.