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New Discoveries on Uranus and Neptune
Heidi B. Hammel joined The Planetary Society's Board of Directors in 2005. A Senior Research Scientist with the Space Science Institute in Boulder, Colorado, Hammel herself lives in Ridgefield, Connecticut.
She received her undergraduate degree from the Massachusetts Institute of Technology in 1982 and her Ph.D. in physics and astronomy from the University of Hawaii in 1988. After a post-doctoral position at the Jet Propulsion Laboratory (Pasadena, California), Hammel returned to MIT, where she spent nearly nine years as a Principal Research Scientist in the Department of Earth, Atmospheric, and Planetary Sciences.
Hammel primarily studies outer planets and their satellites, with a focus on observational techniques. Hammel received the 2002 American Astronomical Society's Division for Planetary Sciences (AAS/DPS) Sagan Medal for outstanding communication by an active planetary scientist to the general public .
Topic: New Discoveries on Uranus and Neptune
Heidi Hammel: Right now Uranus has been a huge focus of my professional career, and that’s because we’ve had a really amazing opportunity. Just last year, in the end of 2007, the planet Uranus was sideways to us. And this doesn’t happen very often, because Uranus is that sturdy planet that’s tipped over in its orbit. It basically rotates sideways, laying on its side. And most of the time, you know, when it’s going around the sun. Well, it takes 84 years for Uranus to go around the sun, so 20 some years ago was when the Voyager spacecraft flew over Uranus. And at that time, its pole, its south pole was pointing at the sun. And so no matter now much that planet spun, the south pole was in total sunlight, and the north pole was in complete blackness. I mean, it didn’t. I mean, and it’s 90 degrees over, so it was like totally half sunlit and half darkness. And when Voyager flew over Uranus, it saw cloud tops, but they were really blank. I mean, there were no swirling storms, or dark bands and light bands, and stuff that you’d see on Jupiter or Saturn. And so people thought, well, it must be because the planet’s turned over on its side, and whatever made it turn over, like a cosmic collision, kind of stirred up the atmosphere and kind of left it dead. And that was peoples’ understanding of Uranus, that it was a dead atmosphere. Well, that was 20 years ago. And in the intervening 20 years, the planet has moved a quarter of the way around in its orbit, ‘til now it’s sideways to the sun. So as it spins, the entire planet is in sunlight, and amazingly, the atmosphere is turning on. There are clouds popping up where no clouds had been seen before. And there’s bands that we can see. There’s a dark spot had developed. Neptune had a dark spot, but Uranus had no dark spot. Well, now, Uranus has a dark spot. So it’s becoming like Neptune as its sunlight is illuminating the whole planet. And that was totally not predicted. People said, well, you know, if it does respond to the sunlight changing, it’s going to be really slow to respond, so maybe 10 years after it goes through what we call equinox, this point where it’s illuminated, maybe 10 years later the atmosphere will turn on. But that is not what’s happening. It is turning on in real time. And that means that our theories, our physical understanding, of what’s just making this atmosphere go, are missing some critical pieces. What are those pieces? Well, I don’t know. I mean, that’s my research. That’s what we’re trying to find out. But I’m in the state right now, we’re taking the data. And because this is a real time event, I mean, it happens and then Uranus moves on, and you have to watch it while it’s happening, right now we’re really, really busy just getting all the information. And then in the next couple of years, when Uranus starts to go back over to its other configuration with one pole lit and one pole dark, we’ll have some breathing space to try to figure out what it all means. So it’s keeping me very busy as a scientist to try to just take the data right now. Another thing that we’re doing with Uranus is we’re looking at its ring system, because the rings orbit in the plane of the equator, you know, sort of like Saturn’s rings do, except the rings are sideways. Well, the last time we had this sideways configuration, it was 42 years ago, because remember it takes Uranus 84 to go around the sun. So 42 years ago was 1965. The rings weren’t even discovered until 1977. So they didn’t even know they existed at the last equinox. So at this equinox was our first time to look at the rings sideways. And what happens is when these rings are closing up as you’re going from sort of a sideways view to the edge on view, you can see different kinds of scattering of sunlight off the rings and through the rings. And we even got this really cool picture where, you know, the sun was illuminating the rings from one side, but the earth was off to another angle, and we could see through the rings. So we were looking at the dark side of the rings of Uranus that were like not lit up by the sun, because the sun was shining on the other side. And you can only do that once ever 42 years. We get this
teeny tiny little two-week window, and we were lucky enough to actually get some good images. We had to fight hurricanes, earthquakes, power failures, but we did it. It was a very exciting and challenging time. And what we’re finding, the surprising science we’re finding, is that the ring system now seems to be quite different than the ring system 20 years ago, when Voyager flew by. And that, again, was not predicted. We thought the rings are, you know, pretty much stable over the period of a 100, a million years, 10,000 years they’ll change. But over 20 years? We’re finding like the major dots where Voyager saw the dots, has shifted like thousands kilometers. So the rings are changing. In real time it’s a very dynamic system, which was not expected. And so, again, what does that mean? Well, that means that our physical understanding in how these rings form has some work left to do, and that will keep us busy. Keeps me off the streets at night, you know, trying to figure these things out.
There's a whole dynamism in these planets that Heidi Hammel did not expect.
If machines develop consciousness, or if we manage to give it to them, the human-robot dynamic will forever be different.
- Does AI—and, more specifically, conscious AI—deserve moral rights? In this thought exploration, evolutionary biologist Richard Dawkins, ethics and tech professor Joanna Bryson, philosopher and cognitive scientist Susan Schneider, physicist Max Tegmark, philosopher Peter Singer, and bioethicist Glenn Cohen all weigh in on the question of AI rights.
- Given the grave tragedy of slavery throughout human history, philosophers and technologists must answer this question ahead of technological development to avoid humanity creating a slave class of conscious beings.
- One potential safeguard against that? Regulation. Once we define the context in which AI requires rights, the simplest solution may be to not build that thing.
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>
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.
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.