"This line of research is going to help us start to identify where in the brain we encode memories of pertinent social experiences that we use to guide learning. And we know that there are several neurodevelopmental disorders in people that have really profound effects on this type of learning."
Source: Scientific American
https://www.scientificamerican.com/podcast/episode/implanting-memories-in-birds-reveals-how-learning-happens/
[Rephrase 1, 03:12]
The loss of ‘eternal ice’ threatens Mongolian reindeer herders’ way of life
Carolyn Gramling | November 20, 2019
[Time 2]
Patches of long-frozen snowpack and ice in the Mongolian steppes are rapidly vanishing — with dire consequences for the reindeer and herders who rely on the icy spots.
About 30 families, members of the Tsaatan people, live within a remote part of northern Mongolia called the Ulaan Taiga Special Protected Area. Interviews with some of these families have let researchers create a never-before-recorded history of this frozen resource, and gain new insight into how quickly it is vanishing.
During the summer, the Tsaatan bring their reindeer herds to a treeless, tundra valley region called Mengebulag. There, numerous large patches of snow and ice have historically persisted, regardless of season, for decades, perhaps longer. The people call these patches “eternal ice,” or munkh mus.
The ice is an important source of freshwater for families, and reindeer lie on it to cool themselves and seek respite from biting insects, says William Taylor, an archaeologist at University of Colorado Boulder and the Max Planck Institute for the Science of Human History in Jena, Germany. Without the cooling and insect-suppressing ice, the herders told researchers, the animals are more vulnerable to parasite-borne illnesses, and are also increasingly heat-stressed, which reduces their immunity to disease.
“These folks are immediately experiencing the consequences, because of the way their livelihood is tied to the animals, and tied to the water,” Taylor says. He and his colleagues recount these people’s ethnographic history, increasingly recognized as an important part of documenting ongoing climate change, in a study published online November 20 in PLOS ONE.
[254 words]
[Time 3]
Mongolia is one of the driest countries in the world, but “mountains provide these unique microenvironments, where the seasonal precipitation is banked up in the form of snowpack,” Taylor says. That has allowed people to live and herd animals throughout the country.
But many of the ice patches appeared to be shrinking, or even vanishing, Taylor and his colleagues have noted on repeat visits to the region. To learn more about where and when the ice began to vanish, the researchers interviewed, in Mongolian, members of three families with summer camps in the region and who have visited the ice patches year after year. Loss of eternal ice patches appears to have accelerated in the last decade, the families reported; many long-standing patches melted away completely during the summers of 2016, 2017 and 2018.
“The really troubling stories were the ones where the families took us to where patches used to be, and now they are just barren rock faces,” Taylor says. “The term munkh mus —it’s a term of respect,” he adds. “They don’t use ‘eternal’ lightly in the Mongolian language. And the loss is, in many ways, felt as a tragic one.”
The study doesn’t analyze how the loss of these ice patches is related to warming temperatures in the region. But the team notes that average temperatures in Mongolia as of 2001 were already 1.5 degrees Celsius higher than the 20th century average, according to a United Nations climate change report.
[244 words]
[Time 4]
Using locations given by the families as well as satellite data from 2016 and 2017, the researchers did visit 11 existing ice patches and two sites that were covered in ice in 2016 but are now completely melted. Those surveys, by horseback, yielded wooden artifacts, once buried by the ice, that Taylor says represent clues to the history of reindeer herding in the region. For instance, a long, cylindrical wooden stick may have been a “scaring stick,” an object herders still use to control the behavior of wild reindeer, the herders told researchers. Lines of such sticks, placed upright in the snow, can trigger the animals’ instincts to shy away from a location.
Carbon-14 dating suggests these artifacts were used in the 1960s or 1970s, the team found. Melting ice patches may have previously exposed many other, perhaps older, organic artifacts, once preserved in ice that have already degraded away. “After those are gone, it’s impossible to backtrack and extrapolate what may have been lost,” Taylor says.
Since the early 2000s, similar finds have begun emerging from melting ice in Norway, North America and in the Alps, says Lars Holger Pilø, a glacial archaeologist with the Glacier Archaeology Program in Oppland, Norway. Now, scientists are racing to collect oral histories and vulnerable artifacts at rapidly melting sites in remote areas. “Many of the finds are in organic materials that are not preserved elsewhere, but which have survived hundreds or thousands of years inside the ice like in a time machine,” Pilø says.
Taylor’s group is the first to undertake such glacial archaeology work in Mongolia, Pilø says. “They are doing really important work.” The ethnographic information “adds meat to the bone, so to speak. It makes it easier to understand why finds are made in ice patches and glaciers and how the finds should be interpreted.”
[306 words]
Source: Science News
https://www.sciencenews.org/article/climate-ice-loss-threatens-mongolian-reindeer-herders-way-life
How two gamma-ray bursts created record-breaking high-energy photons
Christopher Crockett | November 20, 2019
[Time 5]
Two eruptions of gamma rays from exploding stars in far-off galaxies have pelted Earth with the highest-energy photons yet detected from one of these explosions. The shower of light particles reveals how so-called long gamma-ray bursts — among the most powerful explosions in the universe — produce such energetic photons.
“This is the Rosetta Stone of gamma-ray bursts,” says Tsvi Piran, an astrophysicist at the Hebrew University of Jerusalem who was not involved with this research.
Long gamma-ray bursts, or GRBs, mark the death of a massive star as it explodes and leaves behind a neutron star or a black hole. (Short GRBs, on the other hand, accompany collisions between neutron stars, such as the smashup picked up by gravitational-wave detectors in 2017. Until now, the most energetic photons radiating from a long GRB typically maxed out at a few million electron volts of energy, or roughly a million times more energetic than the photons our eyes detect.
That record has been smashed. In July 2018 the HESS observatory, about 100 kilometers southwest from the Namibian capital of Windhoek, recorded photons from a GRB with between 100 billion and 440 billion electron volts, 10 hours after the initial burst. Six months later, in January 2019, the twin MAGIC telescopes in the Canary Island of La Palma saw a different burst and captured photons with a whopping 1 trillion electron volts of energy. The previous record holder from a GRB was a single photon with 94 billion electron volts, detected from a gamma-ray burst in 2013. The new findings appear in three papers published November 20 in Nature.
“There were theories predicting that there should be [very-high-energy photons] from GRBs, but things were very uncertain,” says Razmik Mirzoyan, an astrophysicist at the Max Planck Institute for Physics in Munich who led the study of the 2019 burst. These theories offered differing explanations for how magnetic fields, electrons and ambient light interacted within the debris from a GRB explosion to produce gamma rays. To test these ideas, several teams have been hunting for very-high-energy gamma rays for years, says Mirzoyan. “We were trying for 15 years, but never succeeding.”
[355 words]
[Time 6]
Their newfound success reveals a tale of how GRB photons get so much vigor. Shock waves from the explosion accelerate electrons to nearly the speed of light and generate magnetic fields. The electrons whip around the magnetic field lines and emit relatively low-energy photons. These photons, along with other photons passing by from other galaxies, subsequently get a power boost by ricocheting off and stealing energy from these speedy electrons. It’s this last step, known as inverse Compton scattering, that gives some GRB photons their extreme energies.
“This basic theory came out more than 20 years ago, but there was no proof,” Piran says. “It’s so wonderful that they got it.”
The discovery was helped by the relative proximity of the two blasts. The light from the 2018 burst took about 6 billion years to reach Earth; the 2019 explosion needed roughly 4.5 billion years. While that puts both bursts far beyond our galactic neighborhood, they were much closer than typical GRBs.
The extreme photons revealed a couple of tidbits about GRBs. For inverse Compton scattering to work, the low-energy photons need good odds of running into electrons. “This tells you that you have a very dense medium” around the explosion, says Edna Ruiz-Velasco, an astrophysicist at the Max Planck Institute for Nuclear Physics in Heidelberg, Germany, who studied the 2018 burst.
It also appears that astronomers have been underselling just how much oomph a GRB can pack. GRBs emit light across the entire electromagnetic spectrum — from radio waves to gamma rays — and the 2019 burst pumped as much energy into its extreme gamma-ray photons as it did into its more numerous X-rays, Mirzoyan says. That bumps up the overall energy for GRBs — already comparable to the entire energy output of the sun over its lifetime — by about one-third, he says.
[301 words]
Source: Science News
https://www.sciencenews.org/article/how-two-gamma-ray-bursts-created-record-breaking-high-energy-photons
New statistical model improves the predictive power of standardized test scores
Arizona State University | November 19, 2019
[Paraphrase 7]
A standout essay, high grade point average and stellar standardized test scores are sometimes not enough for college admissions.
The ongoing college admission scandal underscores how influential a standardized test score has become. A test administrator is now cooperating with the investigation into other parents who paid to have their children's test scores fixed.
College admissions decisions use standardized test scores as a predictor of how well an applicant will do in college. But what if there were a better way to predict learning -- one that did not rely on a single, high-stakes test?
Researchers from the Arizona State University and the University of Denver have devised a way to predict academic performance that is three times more predictive than a single standardized assessment. The research team developed and validated a statistical model that uses readily available test scores to predict future academic performance. The study will be published in Multivariate Behavioral Research.
"Everyone is affected by testing at some point -- tests are used to make high-stakes decisions about admissions to schools and sometimes even job placement -- and the model we developed captures what is going on in the data and predicts future performance better than existing methods," said Daniel McNeish, assistant professor of psychology at ASU and first author on the paper.
Current ability does not always predict future learning
The stated purpose of many standardized tests is a one-time assessment, not to inform long-term performance. These tests are sometimes used to predict the future performance of anyone who takes the test, but few tests actually do this well, said Denis Dumas, who is an assistant professor at the University of Denver and second author on the paper. The idea that a single test can fail to adequately measure a student's future learning potential is not a new one: The sociologist, historian and civil rights activist W.E.B. DuBois raised it almost a century ago.
"Test scores from a single time point give a good snapshot of what someone knows at the time of testing, but they often are incapable of providing information about the potential to learn," added Dumas. "Test scores are frequently used to indicate how much a person might benefit from future education, like attending college, but this concept is completely different from how much the test taker knows right now."
To develop the model, the research team took inspiration from the work of an Israeli psychologist named Reuven Feuerstein who tested children survivors of the Holocaust for school and grade-level placement. Grade-level assignments based on one test score were often too low, so Feuerstein developed a testing system called dynamic assessment that used several test scores collected over time to measure children's capacity to learn, instead of their current level of knowledge. Dynamic assessment is labor-intensive and is difficult to implement on a large scale. The research team solved that problem by leveraging advances in mathematical models and computing power to create a new method, which they call a dynamic measurement model.
Connecting the dots
The dynamic measurement model uses a series of test scores to predict future learning capacity. The model fits a curve through the test scores over time, which usually looks like a sideways letter "J" and is ofted called a "learning curve." The points on the learning curve represent the amount of current knowledge, and the maximum or ceiling of the curve is the learning potential. Using standardized test scores from kindergarten through eighth grade, the team recently showed the dynamic measurement model could fit the learning curve and predict learning potential.
The research team wanted to know how far out the model could predict learning potential and thus how accurate it actually was. They used three datasets that originated from the Institute of Human Development at the University of California, Berkeley. The datasets include test scores from participants starting when they were 3 years old in the 1920s and 1930s. The participants were studied for decades, until they were in their 50s, 60s, and 70s.
Because most standardized testing happens in school, the research team used the dynamic measurement model to fit the test scores from when the UC Berkeley participants were aged 20 and younger. The team predicted the future learning potential of each participant by having the model finish the curve. Then, they compared the actual test scores at ages 50-70 years to what the model predicted.
"The dynamic measurement model captured three times the variance as other methods, including single time-point test scores. In other words, our model predicted the later scores -- an individual's realized learning potential -- three times better," McNeish said. "Students are tested so frequently now to gauge their progress, but having multiple scores per student can serve a purpose beyond gauging progress. They can be combined into a single learning potential score to improve predictions of where people's skills and abilities are predicted to end up in the future if they maintain the same trajectory."
Harnessing the potential of standardized testing
Using dynamic measurement modeling to predict the future learning potential of students does not require changes in policy or new tests. The test scores needed for the model already exist and are available because of the passage of the No Child Left Behind Act and Every Student Succeeds Act.
"Dynamic measurement modeling does not require a specialized computer to run and does not take much longer than standard statistical models used in this area," McNeish said. "Logistically, all the pieces are there to implement it tomorrow."
The research team is currently working on developing software to disseminate the dynamic measurement model.
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Source: Science Daily
https://www.sciencedaily.com/releases/2019/11/191119161459.htm
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发表于 2019-11-27 09:12:35
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