Monday, January 12, 2026

 

How hidden factors beneath Istanbul shape earthquake risk



Underground heat and sediment patterns control how earthquakes behave along one of the most dangerous faults in the eastern Mediterranean



University of Southern California





The fault beneath Istanbul doesn’t behave the way scientists once thought.

New research from USC shows that variations in underground temperature and sediment thickness segment the Main Marmara Fault in ways that control where earthquakes start, how far they spread and where they stop — findings that could reshape risk assessments for one of the world’s most vulnerable megacities.

The study, published in Nature Communications Earth & Environment, focuses on the North Anatolian Fault beneath the Sea of Marmara that hasn’t produced a major earthquake since 1894. Using physics-based simulations that model more than 10,000 years of seismic activity, researchers found that the fault is unlikely to rupture in a single, catastrophic event. Instead, it will likely break in segments, with maximum earthquake magnitudes reaching about 7.3.

“Fault geometry tells us where earthquakes are possible, but rheology — how rocks deform under stress — tells us how they actually unfold,” said Sylvain Barbot, the study’s principal investigator and associate professor of Earth sciences at the USC Dornsife College of Letters, Arts and Sciences. “Variations in temperature and rock type along the Main Marmara Fault act as barriers that can stop ruptures or cause the fault to creep instead of breaking in a large earthquake.”

How scientists simulated thousands of years of earthquakes

The Main Marmara Fault is part of the North Anatolian Fault system, which has produced devastating earthquakes throughout Turkish history. While previous studies mapped the fault’s geometry and slip rates, researchers hadn’t fully understood why earthquakes stop where they do — a critical question for estimating maximum possible magnitudes.

The answer lies beneath the seafloor. In the central Sea of Marmara, thick sedimentary basins sit above the warmer crust, creating what the researchers call a strong rheological barrier. Frictional properties of sedimentary rocks under specific temperature and pressure conditions show that they deform slowly and stably at shallow depths rather than breaking suddenly. Meanwhile, elevated temperatures at greater depths weaken rocks in ways that prevent large ruptures from growing.

“The main takeaway is that temperature and sediment thickness fundamentally change how the fault behaves,” said Sezim E. Guvercin, a postdoctoral researcher at USC Dornsife and first author of the study. “These variations create zones that resist rupture, particularly beneath sedimentary basins in the central Sea of Marmara.”

To test this, the research team built a three-dimensional earthquake-cycle model combining realistic fault geometry, frictional properties of rocks and thermal structure based on regional heat-flow measurements. The simulations used Unicycle, an open-source code that can model thousands of years of seismic cycles.

Different segments, different earthquake patterns

When the model incorporated both sedimentary layers and temperature variations, it reproduced key features of the historical record, including the large 1766 and 1912 earthquakes. Over the simulated period, no earthquake exceeded magnitude 7.3.

Different parts of the fault showed distinct patterns. The western Ganos and Tekirdağ segments, which are cooler and geometrically simpler, produce more regular earthquakes — including magnitude 7.2 events recurring roughly every 150 years. The eastern segments, Kumburgaz and Princes’ Islands, generate smaller, more frequent earthquake doublets, typically between magnitude 6.2 and 6.8 roughly every 100 years and a magnitude 7.0 earthquake roughly every 500 years.

The models also predict shallow creep — slow, continuous slip that releases stress without breaking — in parts of the fault near the Central Basin. That behavior matches geodetic observations and clusters of small, repeating earthquakes recorded over the past two decades.

“Earthquakes tend to nucleate near bends in the fault, where stresses are highest,” Barbot said. “But whether a rupture keeps going or stops is largely controlled by rheology.”

Models that ignored sedimentary basins or thermal structure consistently overestimated earthquake sizes and missed behaviors such as creeping segments. Only by incorporating the physical complexity of underground geology did the simulations match observed patterns.

What this means for Istanbul

The findings don’t reduce Istanbul’s earthquake risk. Moderate to large earthquakes occurring closer to the city, or in rapid succession, could still cause catastrophic damage. Instead, the research provides a more accurate picture of how the fault actually behaves — information essential for building codes, emergency planning and infrastructure decisions.

“Our work shows that what’s underground — heat, rocks and structure — matters enormously for earthquake behavior,” Guvercin said. “Integrating these factors is essential for improving seismic hazard forecasts in regions like Istanbul.”

The locked segments of the Main Marmara Fault on both sides have now gone more than 100 years without a major rupture. If these segments follow the patterns observed in simulations, the region may experience major earthquakes in the coming decades. Understanding exactly how the fault will break when it does could help identify which parts of Istanbul face the greatest risk.

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The study is funded by the National Science Foundation under award number EAR-1848192.

 

New technique puts rendered fabric in the best light




Cornell University
2025 Renderings Loop 

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2025 renderings

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Credit: Cornell University






ITHACA, N.Y. -- Fabric has long been difficult to render digitally because of the myriad ways different yarns can be woven or knitted together. Now, Cornell researchers, in partnership with the technology company NVIDIA, have developed a method for creating digital images of cloth that more accurately captures the texture of textiles.

The team’s new study, presented Dec. 16 at the Association for Computing Machinery’s SIGGRAPH Asia 2025 meeting in Hong Kong, models how light interacts with yarns – both as it passes through and reflects off the fabric. The advance is the latest to emerge from the lab of Steve Marschner, professor of computer science in the Cornell Ann S. Bowers College of Computing and Information Science, who has worked on this problem for more than two decades.

Film industry people always complain about how difficult it is to render fabric, said Marschner, who was on a team that received a 2004 Technical Achievement Award from the Academy of Motion Picture Arts and Sciences for work on rendering translucent materials. “It’s just hard to get it to look right. It always looks fake.” 

At its smallest level, fabric is composed of tiny fibers twisted together to make a strand called a ply. Multiple plies are twisted together to form yarn, which is then woven or knitted to create fabric. Unlike materials such as metal or skin, which have a solid, continuous surface, fabric is “just a bunch of fibers floating in space that happen to be held together by friction,” Marschner said.

The shape of the fibers also varies depending on the material. Cut through a fiber of wool and the end will look almost oval; cotton fibers have a kidney shape and silk looks like three- or four-sided polygons.  

“It makes the structure so interesting but so difficult to model,” said Yunchen Yu, a doctoral student in the field of computer science and the study’s first author. “I think there’s never going to be one fabric model that everyone uses.”

Marschner first began researching methods for rendering fabric when he started as an assistant professor at Cornell in 2002. His first doctoral student, Piti Irawan, Ph.D. ‘08, developed a simple method that modeled how light reflects differently off fibers at different points on the cloth’s surface.

After realizing that the underlying fiber structure dictates a fabric’s appearance, Marschner began modeling fabric in a more comprehensive way. Along with Shuang Zhao, Ph.D. ’14, and Kavita Bala, provost and professor of computer science, he used a microCT scanner to image at the scale of the woven fibers. This level of detail allowed them to render fabric more accurately, but scanning was expensive and time-consuming.

Eventually, they made the process more efficient, so they didn’t need to scan each fabric they rendered. This work turned into a side project with Brooks Hagan, a professor at the Rhode Island School of Design, that enabled interior designers to visualize textiles for the production of custom fabrics.

Meanwhile, Marschner’s lab had been working with Doug James, then an associate professor of computer science at Cornell, now at Stanford, making physical simulations of how yarns and fibers are arranged in woven and knitted materials, and how that impacts their appearance. The team made advances in rendering patterns in knitted cloth, and predicting how a knit pattern will ultimately look when executed with yarn.

In the new study with Andrea Weidlich, a principal researcher at NVIDIA, Yu went further by considering how light interacts with cloth, both as a ray and a wave. She modeled light rays that bounce off the fibers – similar to Irawan’s initial model – and light waves that bend and diffract as they pass through gaps between fibers. This was the first fabric model to take wave optics into account, and built off her recent work rendering iridescent feathers.

At first, she tried to model the fabric’s appearance entirely using wave optics, but the simulation was too computationally intensive. Then, she discovered that using ray optics, which is about 1,000 times faster, works well for generating the average color of the fabric and look of the highlights. She could then save the slower wave-optics simulations to render the light shining through the fabric from behind, and for the subtle glints, sparkles and imperfections that make the images look especially realistic.

With this method, Yu must simulate how light interacts with each new type of fabric she renders. But, ultimately, she hopes to employ artificial intelligence to skip the simulation step, making the model faster and more flexible.

Marschner expects that incorporating generative AI techniques will be the key to more efficient fabric modeling for the gaming and animation industry. This will result in higher quality renderings, not just for high-budget animated films, but also for more widespread use, such as in video games.

“We have come a long way since 2002,” Marschner said. “It’s funny to look back at some of the things that we thought looked really good back then.”

 

Cat disease challenges what scientists thought about coronaviruses



Study finds viruses may hide and persist in immune cells



University of California - Davis

Lychee the cat 

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Lychee, a domestic long-hair cat, had feline infectious peritonitis, a feline coronavirus. He was part of a clinical trial at the UC Davis School of Veterinary Medicine that cured him of the disease.

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Credit: UC Davis





Researchers at the University of California, Davis, have uncovered new details about how a once-deadly coronavirus disease in cats spreads through the immune system. The findings may help scientists better understand long COVID and other long-lasting inflammatory illnesses in people.

The disease, feline infectious peritonitis or FIP, is caused by a form of feline coronavirus that changes inside some cats. If left untreated, it is almost always fatal. While FIP only affects cats, it shares many features with serious coronavirus-related conditions in humans, including severe inflammation that can damage multiple organs, as well as symptoms that can persist or return.

A broader attack on the immune system

For years, the prevailing belief was that the virus behind FIP infected just one type of immune cell. 

“What we found is that it actually infects a much broader range of immune cells, including those that are critical for fighting infection,” said lead author Amir Kol, associate professor with the UC Davis School of Veterinary Medicine.

The study was published in the journal Veterinary Microbiology.

The researchers examined lymph node samples from cats with naturally occurring FIP. Lymph nodes are key immune system hubs where white blood cells gather and coordinate responses to disease. The team found viral material inside several types of immune cells — including B lymphocytes, which produce antibodies, and T lymphocytes, which help the immune system recognize and eliminate infected cells.

They also found evidence that the virus was actively replicating itself inside these immune cells, rather than simply leaving behind harmless fragments. 

Why this matters beyond cats

In people with severe or long-lasting coronavirus illnesses, scientists suspect that the virus may persist in the body or continue to disrupt the immune system. Studying this directly in humans is difficult, because doctors rarely have access to immune tissues such as lymph nodes.

Cats with FIP offer a rare opportunity to study these processes up close.

“This is where cats give us a unique opportunity,” Kol said. “We can directly study infected immune tissues in a naturally occurring coronavirus disease — something that’s very difficult to do in people.”

The researchers also found that traces of the virus could remain in immune cells even after antiviral treatment ended and cats appeared healthy. Because some immune cells can live for years, this lingering infection could help explain long-term immune problems or disease relapse.

A model for long-term coronavirus disease

The findings suggest that FIP may serve as a valuable real-world model for understanding how coronaviruses interact with the immune system over time. Insights gained from cats could help guide future research into chronic inflammation and post-viral syndromes in humans, including long COVID.

By bridging veterinary and human medicine, the study highlights how naturally occurring diseases in animals can help answer critical questions about human health.

Other authors of the study include Aadhavan Balakumar, Patrawin Wanakumjorn, Kazuto Kimura, Ehren McLarty, Katherine Farrell, Terza Brostoff, Jully Pires, Tamar Cohen-Davidyan, Jennifer M. Cassano, Brian Murphy and Krystle Reagan of UC Davis.

Funding for the study was provided by the National Institutes of Health and the Sock-FIP fund at the Center for Companion Animal Health at the UC Davis School of Veterinary Medicine. It was also supported by the Faculty of Veterinary Medicine at Kasetsart University in Thailand.