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Astronaut who spent a year in space will keynote TwinFest 2023

Astronaut Scott Kelly spent 340 days aboard the International Space Station, beginning in March 2015, while his identical twin remained on Earth. That dynamic helped elucidate some of the molecular and physiological effects of significant stretches of time beyond the planet’s boundaries and helps illustrate the scientific value of state twin registries.

Kelly is the featured speaker at this year’s Washington State University-sponsored TwinFest, which is set for July 22 in Everett. It’s the first TwinFest gathering in the Evergreen State since the Washington State Twin Registry moved from University of Washington to WSU in 2015.

After collecting troves of samples and data on Kelly during his year in space and comparing them to his then-Earth-bound twin brother, Mark, who is also an astronaut and now a U.S. senator, dozens of researchers from prominent institutions nationwide published a landmark study in the journal Science in 2019.

Their findings related to how long stretches in space affect aging, cognition, and immunology, among numerous other aspects of the human body.

Michael Skinner.

In a recent twin study co-authored by WSU biologist Michael Skinner, the researchers found that consistent exercise has the potential to change molecules within the human body that influence gene behaviors. Twin studies have also examined how environmental exposures such as pollution and area deprivation affect and shape the health of individuals.

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WSU Insider

Ask Dr. Universe: Who Invented the Calendar?

I use a calendar to keep up with my work as a science cat. I also love calendar apps that count down to big events—like my birthday. People have always tracked time for work and holidays.

Nikolaus Overtoom.

I talked about this with my friend Nikolaus Overtoom. He’s a professor of ancient history at Washington State University.

He told me we use the Gregorian calendar today. That’s a revised version of the Julian calendar. The Romans invented the Julian calendar.

But there were calendars before that. Ancient people all over the world had calendars—including a detailed calendar made by the ancient Maya.

“Early people looked to the heavens to understand the movement of planets and stars,” Overtoom said. “They used that information to help structure their societies. They needed to know when to plant crops or move their herds.”

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Ask Dr. Universe

Westneat: Democracy on win streak

The last of the Donald Trump-inspired ‘Big Lie’ cases falls

Remember after the last presidential election, when even here in blue Washington, scores of Republicans sued contending that the election had been stolen?

The lawsuits, filed by a group called Washington Election Integrity Coalition United along with some GOP congressional candidates, contended that “6,000 votes were flipped, over 400,000 votes were added and/or thousands of votes were removed in one or more statewide races.”

No evidence was provided for any of this, so judges across the state started tossing the cases as frivolous. Several times they fined the people involved for wasting everybody’s time.

Cornell Clayton.

Back in early 2022, Cornell Clayton, a Washington State University political science professor who has studied democracy for 35 years, told me that things looked bleak. “All the lights are blinking red” on the American experiment, he said. I asked him this past week to give democracy a follow-up checkup.

“I guess I’d say it’s no longer blinking red quite as urgently,” he said. “Maybe it’s blinking yellow. It’s definitely still saying, ‘Proceed with extreme caution.’ ”

Congress also reformed the Electoral Count Act, making it tougher for any candidate to mess around with congressional certification of the vote.

“These things are extremely important in preventing any further erosion of democratic norms,” Clayton said.

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The Columbian


“This American Land” episode explores threatened Idaho sagebrush steppe environment

When your task is trapping a rabbit, you’ve got to be on the hop. Sometimes that’s easier said than done. In eastern Idaho, the Lemhi Valley is a high-desert valley that runs along the border with Montana. It’s a sagebrush steppe environment, which means it’s a mix of shrub and grasslands, and it is just a gorgeous, gorgeous intact piece of sagebrush landscape.

With support from the National Science Foundation, a team of scientists is trying to understand this critical sagebrush habitat from the perspective of a small but important long-term resident, the pygmy rabbit. They’re trapping and collaring in hopes that their research can contribute to not just an understanding of rabbits but also an understanding of how this system functions so that it can continue to exist in a healthy condition.

Lisa Shipley.

Sheltering from the heat and cold and predators is important, but so is food. Sometimes the rabbits risk a venture into the open to eat. Lisa Shipley is a forging ecologist with Washington State University. “Especially in the winter, it might eat 99% of its diet in sagebrush, ’cause it’s very nutritious,” Shipley said. “It has a lot of protein in it, but it also has a lot of toxic chemicals. It’s the only mammal that can eat sagebrush for a virtually exclusive diet.”

Using tracking data from the collars and imagery from unmanned aerial vehicles, the team generates maps that show where and when the rabbits spend their time, in burrows, under the sagebrush, and out in the open. Maps like these can tell them a lot about how the rabbits use and ultimately shape the landscape around them. They have to make choices all the time. so they can choose to forage in an area that has high-quality forage, but it might be more risky.

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PBS (at 21:45 )

How Math Has Changed the Shape of Gerrymandering

New tools make it possible to detect hidden manipulation of maps.
Until recently, gerrymandered districts tended to stick out, identifiable by their contorted tendrils. This is no longer the case. Without the telltale sign of an obviously misshapen district to go by, mathematicians have been developing increasingly powerful statistical methods for finding gerrymanders. These work by comparing a map to an ensemble of thousands or millions of possible maps. If the map results in noticeably more seats for Democrats or Republicans than would be expected from an average map, this is a sign that something fishy might have taken place.

But making such ensembles is trickier than it sounds, because it isn’t feasible to consider all possible maps — there are simply too many combinations for any supercomputer to count. A number of recent mathematical advances suggest ways to navigate this impossibly large space of possible simulations, giving mathematicians a reliable way to tell fair from unfair.

Daryl DeFord.

One advance came in 2019, when a group of researchers was working on a better way to draw a new district map for the Virginia House of Delegates. The previous year, a federal court had ruled that 11 districts in Virginia’s map were unconstitutional because they concentrated Black residents in a way that diluted their voting strength. Furthermore, Virginia has an unusually strict constraint in its redistricting process: Districts can only deviate in population by 1%. Given that there are 100 state House districts, “that’s a pretty tight bound,” said Daryl DeFord, a mathematician at Washington State University who analyzed the fairness of the Virginia map. It meant that the group couldn’t work at the level of precincts. “Some precincts were basically too big to make a valid plan,” DeFord said. Partitioning the map into smaller census block units didn’t work either. After around 10 million steps, standard flip-based MCMC algorithms “weren’t anywhere close to having representative samples from the whole space,” he said.

So DeFord and his colleagues came up with a way to move through the space more quickly. In order to speedily obtain samples from the entire space of possible maps, they needed to change the district assignment for many precincts at once in a way that preserved the contiguity of the districts. This made each step in the Markov chain more computationally expensive, but it also meant that each step brought them that much closer to the mixing time.

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Quanta Magazine