from the world's big
A new theory explains Jupiter’s perplexing origin
A new computer model solves a pair of Jovian riddles.
- Astronomers have wondered how a gas giant like Jupiter could sit in the middle of our solar system's planets.
- Also unexplained has been the pair of asteroid clusters in front of and behind Jupiter in its orbit.
- Putting the two questions together revealed the answer to both.
Jupiter's long been a puzzler to astronomers. Planet formation theory holds that a gas giant forms far away from its star then moves inward over time until it's in a tight orbit around the sun. Jupiter, though, sits right in the middle of our solar system's planets, between Mars and Saturn. And that's not all that's odd: There's an unexpectedly asymmetrical pair of asteroid clusters — known as the Trojan asteroids — preceding and trailing Jupiter in its orbit. The group in front is 50% larger than the one in back. The most widely accepted idea was that Jupiter formed near the Sun and moved outwards.
That's now been turned on its head by a team of scientists from Lund University who ran a series of models to try to identify a plausible origin story for Jupiter. They discovered that the planet and its clusters would be where they are under only one scenario: Jupiter forming way out near Uranus — as gas giants are supposed to do, after all — and moving slowly toward the Sun, attracting and accreting the asteroids that now form its core, with the leftovers trailing behind. Lead author Simona Pirani says, "This is the first time we have proof that Jupiter was formed a long way from the Sun and then migrated to its current orbit." Including the mystery of the asymmetrical Trojans in the simulations was the key.
Jupiter, right in the middle of everything.
The model that lands Jupiter where it is today, along with its thousand of Trojans, begins four times further away from the Sun than Jupiter currently orbits, just inside of Uranus' orbit. Jupiter first took form about 4.5 billion years back as an icy planetary seedling, an ice asteroid, no bigger than Earth. Somewhere between two and three million years later, the future giant began spiraling slowly inward toward the Sun, pulled by gases circulating throughout the solar system. It took about 700,000 years to get where it is now. Along the way, before it developed its gaseous atmosphere and massive size, Jupiter's gravity pulled the Trojans in — the researchers expect Jupiter's core to be composed of materials similar to the Trojans. They're believed to be rich with dark carbon compounds, and likely rich in water and other volatile materials beneath an outer layer of dust.
Lucy in the sky with Trojans
Trojan clusters held in place by the Sun and Jupiter
(Astronomical Institute of CAS/Petr Scheirich)
In October 2021, NASA plans to launch its Lucy mission to study the Trojans. It's believed that they're very old time capsules from the universe of four billion years ago. The craft will study seven of them: one from the solar system's main asteroid belt, and the remaining six from the clusters leading and following Jupiter in its orbit.
Those two Trojan groups are held in place at stable LaGrange points by the combined gravitation pull of the Sun and Jupiter acting together as a single centrifugal force acting upon them.
NASA has high hopes for the mission as chance to get a closeup look at the type of materials from which our planetary bodies formed.
Meanwhile, Jupiter's seeming a little bit less mysterious now, at least in terms of its origin. It may also be that ice giants Uranus and Neptune, as well as Saturn, have a similar history.
Why are so many objects in space shaped like discs?
What would it be like to experience the 4th dimension?
Physicists have understood at least theoretically, that there may be higher dimensions, besides our normal three. The first clue came in 1905 when Einstein developed his theory of special relativity. Of course, by dimensions we’re talking about length, width, and height. Generally speaking, when we talk about a fourth dimension, it’s considered space-time. But here, physicists mean a spatial dimension beyond the normal three, not a parallel universe, as such dimensions are mistaken for in popular sci-fi shows.
Duke University researchers might have solved a half-century old problem.
- Duke University researchers created a hydrogel that appears to be as strong and flexible as human cartilage.
- The blend of three polymers provides enough flexibility and durability to mimic the knee.
- The next step is to test this hydrogel in sheep; human use can take at least three years.
Duke researchers have developed the first gel-based synthetic cartilage with the strength of the real thing. A quarter-sized disc of the material can withstand the weight of a 100-pound kettlebell without tearing or losing its shape.
Photo: Feichen Yang.<p>That's the word from a team in the Department of Chemistry and Department of Mechanical Engineering and Materials Science at Duke University. Their <a href="https://onlinelibrary.wiley.com/doi/abs/10.1002/adfm.202003451" target="_blank">new paper</a>, published in the journal,<em> Advanced Functional Materials</em>, details this exciting evolution of this frustrating joint.<br></p><p>Researchers have sought materials strong and versatile enough to repair a knee since at least the seventies. This new hydrogel, comprised of three polymers, might be it. When two of the polymers are stretched, a third keeps the entire structure intact. When pulled 100,000 times, the cartilage held up as well as materials used in bone implants. The team also rubbed the hydrogel against natural cartilage a million times and found it to be as wear-resistant as the real thing. </p><p>The hydrogel has the appearance of Jell-O and is comprised of 60 percent water. Co-author, Feichen Yang, <a href="https://today.duke.edu/2020/06/lab-first-cartilage-mimicking-gel-strong-enough-knees" target="_blank">says</a> this network of polymers is particularly durable: "Only this combination of all three components is both flexible and stiff and therefore strong." </p><p> As with any new material, a lot of testing must be conducted. They don't foresee this hydrogel being implanted into human bodies for at least three years. The next step is to test it out in sheep. </p><p>Still, this is an exciting step forward in the rehabilitation of one of our trickiest joints. Given the potential reward, the wait is worth it. </p><p><span></span>--</p><p><em>Stay in touch with Derek on <a href="http://www.twitter.com/derekberes" target="_blank">Twitter</a>, <a href="https://www.facebook.com/DerekBeresdotcom" target="_blank">Facebook</a> and <a href="https://derekberes.substack.com/" target="_blank">Substack</a>. His next book is</em> "<em>Hero's Dose: The Case For Psychedelics in Ritual and Therapy."</em></p>
An algorithm may allow doctors to assess PTSD candidates for early intervention after traumatic ER visits.
- 10-15% of people visiting emergency rooms eventually develop symptoms of long-lasting PTSD.
- Early treatment is available but there's been no way to tell who needs it.
- Using clinical data already being collected, machine learning can identify who's at risk.
The psychological scars a traumatic experience can leave behind may have a more profound effect on a person than the original traumatic experience. Long after an acute emergency is resolved, victims of post-traumatic stress disorder (PTSD) continue to suffer its consequences.
In the U.S. some 30 million patients are annually treated in emergency departments (EDs) for a range of traumatic injuries. Add to that urgent admissions to the ED with the onset of COVID-19 symptoms. Health experts predict that some 10 percent to 15 percent of these people will develop long-lasting PTSD within a year of the initial incident. While there are interventions that can help individuals avoid PTSD, there's been no reliable way to identify those most likely to need it.
That may now have changed. A multi-disciplinary team of researchers has developed a method for predicting who is most likely to develop PTSD after a traumatic emergency-room experience. Their study is published in the journal Nature Medicine.
70 data points and machine learning
Image source: Creators Collective/Unsplash
Study lead author Katharina Schultebraucks of Columbia University's Department Vagelos College of Physicians and Surgeons says:
"For many trauma patients, the ED visit is often their sole contact with the health care system. The time immediately after a traumatic injury is a critical window for identifying people at risk for PTSD and arranging appropriate follow-up treatment. The earlier we can treat those at risk, the better the likely outcomes."
The new PTSD test uses machine learning and 70 clinical data points plus a clinical stress-level assessment to develop a PTSD score for an individual that identifies their risk of acquiring the condition.
Among the 70 data points are stress hormone levels, inflammatory signals, high blood pressure, and an anxiety-level assessment. Says Schultebraucks, "We selected measures that are routinely collected in the ED and logged in the electronic medical record, plus answers to a few short questions about the psychological stress response. The idea was to create a tool that would be universally available and would add little burden to ED personnel."
Researchers used data from adult trauma survivors in Atlanta, Georgia (377 individuals) and New York City (221 individuals) to test their system.
Of this cohort, 90 percent of those predicted to be at high risk developed long-lasting PTSD symptoms within a year of the initial traumatic event — just 5 percent of people who never developed PTSD symptoms had been erroneously identified as being at risk.
On the other side of the coin, 29 percent of individuals were 'false negatives," tagged by the algorithm as not being at risk of PTSD, but then developing symptoms.
Image source: Külli Kittus/Unsplash
Schultebraucks looks forward to more testing as the researchers continue to refine their algorithm and to instill confidence in the approach among ED clinicians: "Because previous models for predicting PTSD risk have not been validated in independent samples like our model, they haven't been adopted in clinical practice." She expects that, "Testing and validation of our model in larger samples will be necessary for the algorithm to be ready-to-use in the general population."
"Currently only 7% of level-1 trauma centers routinely screen for PTSD," notes Schultebraucks. "We hope that the algorithm will provide ED clinicians with a rapid, automatic readout that they could use for discharge planning and the prevention of PTSD." She envisions the algorithm being implemented in the future as a feature of electronic medical records.
The researchers also plan to test their algorithm at predicting PTSD in people whose traumatic experiences come in the form of health events such as heart attacks and strokes, as opposed to visits to the emergency department.