Challenging Einstein's Greatest Theory with Extreme Stars

Researchers have conducted a 16-year long experiment to challenge Einstein’s theory of general relativity. The international team looked to the stars - a pair of extreme stars called pulsars to be precise – through seven radio telescopes across the globe.
Credit: Max Planck Institute for Radio Astronomy

Scientific Frontline: "At a Glance" Summary

• Main Discovery: A 16-year international experiment utilizing a unique double pulsar system confirmed Einstein’s theory of general relativity with unprecedented precision, successfully validating seven distinct predictions including relativistic effects never previously observed.
• Methodology: Researchers employed seven sensitive radio telescopes globally to track the precise radio beams of two pulsars orbiting each other every 147 minutes, utilizing pulsar timing and interferometric measurements to map the system's intense gravitational field and distance (2,400 light-years).
• Key Statistics: The study tested the energy carried by gravitational waves with a precision 25 times greater than the Nobel Prize-winning Hulse-Taylor pulsar results and 1,000 times greater than current gravitational wave detectors, while measuring orbital orientation changes to an accuracy of one part in a million.
• Specific Mechanism: The team successfully detected the Lense-Thirring effect (frame-dragging), where the rotation of the pulsar drags the surrounding spacetime, and observed a specific light deflection angle of 0.04 degrees caused by the strong curvature of space.
• Significance: These findings represent the most rigorous test of gravity in strong-field conditions to date, confirming that general relativity holds firm even at extreme scales and setting a critical benchmark for future attempts to unify gravity with quantum mechanics.

Technique Speeds Up Thermal Actuation for Soft Robotics

Image Credit: Shuang Wu.

Researchers from North Carolina State University have come up with a new design for thermal actuators, which can be used to create rapid movement in soft robotic devices.

“Using thermal actuation is not new for soft robots, but the biggest challenge for soft thermal actuators was that they were relatively slow – and we’ve made them fast,” says Yong Zhu, corresponding author of the paper and the Andrew A. Adams Distinguished Professor of Mechanical and Aerospace Engineering at NC State.

Actuators are the parts of a device – such as a soft robot – that create motion by converting energy into work.

“What makes this new actuator design work is a structure with a bi-stable design,” says Shuang Wu, first author of the paper and a Ph.D. student at NC State. “Think of a snap hair clip. It’s stable until you apply a certain amount of energy (by bending it over), and then it snaps into a different shape – which is also stable.”

In the case of the new thermal actuator, the material is bi-stable, but which shape the material prefers is dictated by temperature.

Here’s how that works. The researchers layer two materials on top of each other, with silver nanowires in the middle. The two materials have different coefficients of thermal expansion, which means they expand at different rates as they heat up. In practical terms, that means the structure bends when you heat it.

How we measure the effects of methane matters for climate policy

How effective is the promotion of low-meat diets at reducing greenhouse gas emissions compared to carbon pricing when the effectiveness of mitigation policies is measured against methane’s long-term behavior? An international team of researchers explored how focusing either on the short- or long-term warming effects of methane can affect climate mitigation policies and dietary transitions in agriculture.

Unlike the other main greenhouse gases (GHG) and particularly carbon dioxide (CO2), methane (CH4) has a short atmospheric life (around 10 years). Its warming effect is significant in the short term but diminishes in the long term. Depending on the time scale considered, methane’s contribution to agricultural emissions and climate change may vary substantially. This has important implications in the design of global climate change mitigation policies for agriculture.

Based on projections from three agricultural economic models, the study just published in the journal Nature Food shows how different valuations of methane, reflecting either a short- or long-term focus, may affect the cost-effectiveness of mitigation policies and the benefits of low-meat diets.

Conventionally, the climate impact of a certain sector is evaluated through its annual greenhouse gas emissions, typically using the Global Warming Potential over a 100 year period metric ̶ GWP100 ̶ which estimates the change in atmospheric energy balance resulting from a particular type of GHG emission. However, as GHG emissions are reported as CO2-equivalents (which is a very stable GHG), GWP100 can fail to capture how the relative impacts of different gases change over time.

The short-lived character of methane emissions has been arguably overlooked in most assessments of emission reductions required from the agricultural sector to achieve climate targets. The authors explored how different valuations of methane affect the ranking of mitigation policies in agriculture and, consequently, the sector’s contribution to global warming.

Farmed seafood supply at risk if we don’t act on climate change

Credit: Bob Brewer/Unsplash

The supply of farmed seafood such as salmon and mussels are projected to drop 16 per cent globally by 2090 if no action is taken to mitigate climate change, according to a new UBC study.

Ocean-farmed seafood or mariculture is often seen as a panacea to the problems of depleted stocks of wild fish and growing human demand, and is expected to grow substantially in the coming years, says lead author Dr. Muhammed Oyinlola (he/him), a postdoctoral research fellow at the Institute for the Oceans and Fisheries (IOF). But the new modeling study highlights the industry is as vulnerable to the effects of climate change as any other. “If we continue to burn fossil fuels at our current rate, the amount of seafood such as fish or mussels able to be farmed sustainably will increase by only eight per cent by 2050, and decline by 16 per cent by 2090.”

By comparison, in a low emissions scenario where the action is taken to mitigate climate change, mariculture is projected to grow by about 17 per cent by the mid-21st century and by about 33 per cent by the end of the century, relative to the 2000s.

The model takes into account many factors, including changing ocean temperatures, suitable mariculture areas in the future, and the supply of fishmeal and fish oil. It examined approximately 70 per cent of the world’s mariculture production as of 2015, focusing on Exclusive Economic Zones, where most of the world’s seafood farming occurs.

Climate change will affect mariculture production differently depending on where farms are in the world, and what they produce, says Dr. Oyinlola. The hardest-hit regions in the high-emissions scenario— Norway, Myanmar, Bangladesh, the Netherlands, and China—could see their mariculture production decline by as much as 40 to 90 per cent.

Artificial intelligence can create better lightning forecasts

Lightning is one of the most destructive forces of nature, as in 2020 when it sparked the massive California Lightning Complex fires, but it remains hard to predict. A new study led by the University of Washington shows that machine learning — computer algorithms that improve themselves without direct programming by humans — can be used to improve lightning forecasts.

Better lightning forecasts could help to prepare for potential wildfires, improve safety warnings for lightning and create more accurate long-range climate models.

“The best subjects for machine learning are things that we don’t fully understand. And what is something in the atmospheric sciences field that remains poorly understood? Lightning,” said Daehyun Kim, a UW associate professor of atmospheric sciences. “To our knowledge, our work is the first to demonstrate that machine learning algorithms can work for lightning.”

The new technique combines weather forecasts with a machine learning equation based on analyses of past lightning events. The hybrid method, presented Dec. 13 at the American Geophysical Union’s fall meeting, can forecast lightning over the southeastern U.S. two days earlier than the leading existing technique.

“This demonstrates that forecasts of severe weather systems, such as thunderstorms, can be improved by using methods based on machine learning,” said Wei-Yi Cheng, who did the work for his UW doctorate in atmospheric sciences. “It encourages the exploration of machine learning methods for other types of severe weather forecasts, such as tornadoes or hailstorms.”

Women Are Facing Greater Interruption Challenges with Remote Work Than Their Male Colleagues

Women employees are facing bigger career challenges than their male colleagues with interruptions to their work-from-home life, according to new research by UConn management professor Nora Madjar.

Madjar’s research, “Working from Home During COVID-19: A study of Interruption Landscape,’’ was published this month by the Journal of Applied Psychology. She co-authored the piece with professors Sophie Leroy of the University of Washington and Aaron Schmidt of the University of Minnesota.

“The gender divide was particularly surprising to us. We had heard anecdotally that it occurred, but now we have empirical evidence that women are interrupted more frequently, both with work-related and personal responsibilities,’’ Madjar says.

“Women have paid an additional price since the onset of the pandemic,’’ she says. “This is more than just an inconvenience. Work interruptions are associated with reduced employee performance and higher levels of emotional exhaustion.’’

The researchers discovered some practical solutions that employers can take to help their employees minimize interruptions, including assistance in establishing a dedicated work space within the employee’s home.

Vaccines shown to induce lower levels of neutralizing antibodies against Omicron coronavirus variant

Vaccines shown to induce lower levels of neutralizing antibodies against Omicron coronavirus variant

Researchers used blood samples collected from Com-COV2 study participants who had received two doses of standard COVID-19 vaccination schedules to perform neutralization assays using Omicron virus isolate

Substantial fall in neutralizing titers suggest that while there is no evidence of increased potential to cause severe disease, or death, increased infections in previously infected, or vaccinated individuals may be likely

Increasing vaccine uptake among unvaccinated, and encouraging third doses, remain priority to reduce transmission levels and potential for severe disease

Researchers from the University of Oxford have analyzed the impact of the Omicron COVID-19 variant of concern on one of the immune responses generated by vaccination.

Using blood samples from individuals who had previously received two doses of the Oxford-AstraZeneca or Pfizer-BioNTech vaccines as part of the Com-COV study, and a live virus isolate, they demonstrate substantial decrease in neutralizing titers – a measure of the level of neutralizing antibodies generated in responses to vaccination against, or infection from, COVID-19.

The results, published on the pre-print server MedRxiv, indicate that the Omicron variant has the potential to drive a further wave of infections, including among those already vaccinated, although the researchers highlight that there is currently no evidence of increased potential to cause severe disease, hospitalizations or deaths in vaccinated populations.

What Is the Ozone Hole?

 

Let’s back up to the basics and understand what caused the Ozone Hole, its effects on the planet, and what scientists predict will happen in future decades.

Video: NASA/GSFC

Final Editing and Conversion: Scientific Frontline

Music Credit: “Glacial Shifts” “Crystallize” “Morning Dew” from Universal Production Music

Video Credits:

Kathleen Gaeta (AIMM): Lead Producer

Paul Newman (NASA/GSFC): Lead Scientist

Susan Strahan (USRA): Scientist

Adriana Manrique Gutierrez (KBRwyle): Animator

Walt Feimer (KBRwyle): Animator

Alexander Bodnar (AIMM): Animator

Kathryn Mersmann (KBRwyle): Technical Support

Artificial Intelligence that can discover hidden physical laws in various data

Diagram explaining the developed artificial intelligence technology
Credit: Yuhan Chen, Kobe University

Researchers at Kobe University and Osaka University have successfully developed artificial intelligence technology that can extract hidden equations of motion from regular observational data and create a model that is faithful to the laws of physics.

This technology could enable us to discover the hidden equations of motion behind phenomena for which the laws were considered unexplainable. For example, it may be possible to use physics-based knowledge and simulations to examine ecosystem sustainability.

The research group consisted of Associate Professor YAGUCHI Takaharu and PhD. student CHEN Yuhan (Graduate School of System Informatics, Kobe University), and Associate Professor MATSUBARA Takashi (Graduate School of Engineering Science, Osaka University).

These research achievements were made public on December 6, 2021, and were presented at the Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS2021), a prestigious meeting on artificial intelligence technologies. This research was among the top 3% selected for the spotlight category.

A longer-lasting COVID vaccine?

 Microscope image showing a human cell (pink)
heavily infected with SARS-CoV-2 virus particles (green and purple).
Credit: NIAID/NIH

Researchers at the Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research at UCLA have identified rare, naturally occurring T cells that are capable of targeting a protein found in SARS-CoV-2 and a range of other coronaviruses.

The findings suggest that a component of this protein, called viral polymerase, could potentially be added to COVID-19 vaccines to create a longer-lasting immune response and increase protection against new variants of the virus.

Background

Most COVID-19 vaccines use part of the spike protein found on the surface of the virus to prompt the immune system to produce antibodies. However, newer variants — such as delta and omicron — carry mutations to the spike protein, which can make them less recognizable to the immune cells and antibodies stimulated by vaccination. Researchers say that a new generation of vaccines will likely be needed to create a more robust and wide-ranging immune response capable of beating back current variants and those that may arise in the future.

One way to accomplish this is by adding a fragment of a different viral protein to vaccines — one that is less prone to mutations than the spike protein and that will activate the immune system’s T cells. T cells are equipped with molecular receptors on their surfaces that recognize foreign protein fragments called antigens. When a T cell encounters an antigen its receptor recognizes, it self-replicates and produces additional immune cells, some of which target and kill infected cells immediately and others which remain in the body for decades to fight that same infection should it ever return.

A bonding experience: Study reveals potential new family of compounds

Thomas E. Albrecht-Schoenzart,
Gregory R. Choppin Professor of Chemistry.

On the Periodic Table of Elements, there are elements that most people remember from school — oxygen, hydrogen, gold and silver. But there are also the ones that you might not immediately recognize, such as berkelium and einsteinium. These exotic elements are typically only used in specialized laboratories to understand how chemistry and physics change at the extremes of the table.

Those heavy elements, particularly radioactive ones, are exceptionally difficult to modify and control for specific purposes. But a Florida State University research team has found that they could design a ligand —a functional group of molecules used to build complex compounds — out of molecules typically used in solar cell technologies and create a completely unexpected effect when bonding them with a radioactive element. When they paired that ligand with the element berkelium, it caused a significant shift in the electron density of the compound.

“You normally wouldn’t think about bonding them to radioactive elements, but the idea was to polarize the electrons around berkelium to gain systematic control of bonding,” said Thomas Albrecht-Schoenzart, the Gregory R. Choppin Professor of Chemistry at Florida State University. “But it had this bigger effect in that it enhanced the bonding ability of anything that was directly across from this highly polarized binding agent, and it pulled the electron density from one side of the molecule to the other.”

The study was published today in Nature Communications.

In addition to berkelium, Albrecht-Schoenzart and his team tested the process on cerium, a silvery white metal that tarnishes when exposed to air and has some properties that are similar to berkelium. The effect was stronger in berkelium than cerium, but still significant.

New biosensors shine a light on CRISPR gene editing

Detecting the activity of CRISPR gene editing tools in organisms with the naked eye and an ultraviolet flashlight is now possible using technology developed at the Department of Energy’s Oak Ridge National Laboratory.

Scientists demonstrated these real-time detection tools in plants and anticipate their use in animals, bacteria and fungi with diverse applications for biotechnology, biosecurity, bioenergy and agriculture. The team described the successful development of the UV system in Horticulture Research and their proof-of-principle demonstration in ACS Synthetic Biology.

CRISPR technologies have quickly become the primary tools of bioengineering, and new versions are continually in development. Identifying whether an organism has been modified by CRISPR technology was previously a complex and time-consuming process.

“Before this, the only way to tell if genome engineering occurred was to do a forensic analysis,” said Paul Abraham, a bioanalytical chemist and head of ORNL’s Secure Ecosystem Engineering and Design Science Focus Area. “To be successful, you would need to know what the genome looked like before it was rewritten. We wanted to design a platform where we could proactively observe CRISPR activity.”

The research team developed an efficient self-detect solution that takes advantage of the way CRISPR works to trigger the technology to reveal itself. Under normal conditions, CRISPR works by connecting with a short RNA sequence, known as the guide RNA, as it leads CRISPR to a matching DNA sequence. When the target DNA is found, CRISPR modifies the DNA by acting like tiny molecular scissors to cut through one or both strands of DNA, depending on the type of CRISPR technology in use.

The tetra-neutron – a miniature neutron star

Dr. Roman Gernhäuser at the target chamber. The tetra-neutron particles were created in the center of this chamber. The reaction was detected using an extremely sensitive magnetic spectrograph.
Image: Uli Benz / Tum

Experiment finds evidence for a long-sought particle comprising four neutrons The tetra-neutron – a miniature neutron star

While all atomic nuclei except hydrogen are composed of protons and neutrons, physicists have been searching for a particle consisting of two, three or four neutrons for over half a century. Experiments by a team of physicists of the Technical University of Munich (TUM) at the accelerator laboratory on the Garching research campus now indicate that a particle comprising four bound neutrons may well exist.

While nuclear physicists agree that there are no systems in the universe made of only protons, they have been searching for particles comprising two, three or four neutrons for more than 50 years.

Should such a particle exist, parts of the theory of the strong interaction would need to be rethought. In addition, studying these particles in more detail could help us better understand the properties of neutron stars.

"The strong interaction is literally the force that holds the world together at its core. Atoms heavier than hydrogen would be unthinkable without it," says Dr. Thomas Faestermann, who directed the

Novel model can aid decisions in electricity generation, stream water quality

A student working in a geosciences class with Susan L. Brantley, Barnes Professor of Geosciences, takes a water sample in central Pennsylvania. Students in the class noticed that some streams near power plants showed improvements in water quality and thought that power plants switching from coal to natural gas may explain the positive results. A Penn State-led research team developed a novel model to detect if power plants shifting from coal to natural gas is affecting stream water quality regionally. Credit: Susan Brantley / Penn State

Switching from coal to natural gas in power plants can reduce how much sulfur dioxide, a gas that smells like a freshly struck match, is emitted into the atmosphere and ultimately how much sulfate pollution enters waterways, according to a Penn State-led research team that has developed a model to detect if the recent switch from coal to gas is affecting streams.

“The number of power plants switching from coal to natural gas is increasing, and sulfur dioxide emissions in Pennsylvania and across the United States are decreasing dramatically,” said Xianzeng Niu, assistant research professor in Penn State’s Earth and Environmental Systems Institute (EESI). “Both technology and the shift of fuels have contributed to this trend. We wanted to look at how this trend has affected water quality.”

Coal- and natural gas-burning power plants emit sulfur dioxide into the atmosphere, but coal has a much higher sulfur content than natural gas and releases more sulfur dioxide when burned. The sulfur particles eventually fall back down to earth and can acidify streams. Too much sulfur, which enters waterways in the form of sulfate, can cause water chemistry to become harmful to ecosystems.

Almost two-thirds of species at deep-sea hydrothermal vents are at risk of extinction

Image of a deep-sea Hydrothermal Vent taken by a Remotely Operate Vehicle (ROV).
Photo credit to Marum Universitat Bremen.

New research from Queen’s University Belfast has led to 184 deep-sea species being added to the global Red List of Threatened Species. With almost two-thirds of the species assessed listed as threatened, it highlights the urgent need to protect them from extinction.

The International Union for Conservation of Nature (IUCN)’s Red List of Threatened Species is the world’s foremost conservation authority, with universally recognized extinction risk categories (e.g. Endangered, Critically Endangered, etc.) used to raise awareness of species’ conservation needs to industry, policy makers, and the general public. More than 140,000 species have been Red Listed but less than 15% are from marine environments and barely any are from the deep sea.

The deep sea is the largest environment on earth with thousands of unique species living in extreme habitats. The remoteness of these seafloor habitats means they are often understudied, making it difficult to understand and communicate their conservation requirements.

Hydrothermal vents are just one of these unique deep-sea ecosystems. Vent habitats host a similar density of life as tropical rainforests and coral reefs. There are approximately 600 of these hotspots known worldwide and most are one-third of a football field in size. Vent communities are also distinctly different from the surrounding seafloor, making these highly insular habitats.