EPA Seeks To Revoke Scientific Basis For Greenhouse Gas Rules

IRA FLATOW: This is Science Friday. I’m Ira Flatow. This week, the Trump administration indicated that they’ll seek to roll back a key EPA finding that allows the agency to regulate greenhouse gas emissions from things like cars and power plants. Here with the details and other stories from the week in science is Sophie Bushwick, senior news editor at New Scientist in New York. Welcome back, Sophie.

SOPHIE BUSHWICK: Thank you.

IRA FLATOW: You’re welcome. OK, what is this rule? How does it interact with how the EPA regulates things?

SOPHIE BUSHWICK: Well, the finding itself, it’s called the endangerment finding, is basically the basis of the EPA regulating power plants and vehicles. Like you said, without it, there would be a major deregulatory effort. Our reporter, James Dinneen, spoke with a lot of climate scientists who described this report in less than glowing terms.

They described it as flimsy. Someone called it nutty. One researcher, whose work was cited in the report, has called it a farce. And so there’s overwhelming scientific evidence that supports the endangerment finding, and already the EPA is going to face a lot of pushback legally. And they’re open to public comment as well if they want to try to move forward with this.

IRA FLATOW: What exactly is the aim here, to take away all the basis for regulation?

SOPHIE BUSHWICK: Yes. The claim is that it’s bad for the economy to limit the emissions that power plants and vehicles are allowed to do and that, by repealing the endangerment finding and removing those regulations, it would be stimulating to the economy.

IRA FLATOW: Well, we seem like we’re turning the clock back.

SOPHIE BUSHWICK: It does seem like an attempt to do that, yes.

IRA FLATOW: So is this a done deal? Or is this just a possible outcome?

SOPHIE BUSHWICK: This is just a possible outcome. And already there is organizations lining up, lawsuits to try to prevent this. The EPA is opening a public comment period, so people will be able to comment on this and to voice their disagreement if that’s what they choose to do. So this is just the beginning of a process.

IRA FLATOW: All right. Let’s switch gears to another kind of emission. Tell us about the news this week, re– the search for life outside our solar system and an exoplanet.

SOPHIE BUSHWICK: That’s right. So earlier this year, the exoplanet K2-18B became one of the leading candidates for life because researchers were able to detect what they said was a signature of these molecules, dimethyl sulfide and dimethyl disulfide. And these two molecules on Earth are only produced by life. So that would really suggest some exciting news.

The problem is, when you’re talking about something as far away as this planet, it’s 124 light years away. And the way that we figure out what’s in the atmosphere is basically researchers look at the light from the star that this planet relies on. And as that light passes through the planet’s atmosphere, it can tell us what molecules are there.

But you have to do some statistical analysis. There’s different ways of interpreting the data. And so that’s made this a controversial finding.

So first there was pushback from other researchers who reassessed the data and found no evidence. Then the original researchers looked at the data again and did their own reanalysis and said it supported their finding. And now researchers have looked at new data, and one of the researchers on the original study says this supports the finding. But other researchers said it shows this isn’t a sign of life at all.

IRA FLATOW: Wow. (SARCASTICALLY) Controversy in scientists? Scientists disagree with one another? Wow.

SOPHIE BUSHWICK: Wild, right?

IRA FLATOW: Wow. Wild. Let’s get back here on Earth for a bit. The conflict between Russia and Ukraine stretches on, and there’s unfortunately an innovation in warfare technology. Tell us about that.

SOPHIE BUSHWICK: Well, from the beginning of this conflict, cheap, small drones have played a role. And recently people have spotted these drones that are equipped with solar panels. So they don’t come with solar panels. They’ve been fitted with them.

And the idea is that this could keep a drone charged and allow it to lay in wait to ambush someone. So almost like the drone has become a new kind of land mine, it can just lurk indefinitely until a target comes near.

IRA FLATOW: Is this a Ukrainian or a Russian drone?

SOPHIE BUSHWICK: This seems to be coming from Russian forces. But the fact is that if Russian forces are able to modify drones in this way, Ukrainian forces could do the same thing. And so this might become a much more widespread thing.

IRA FLATOW: Yeah, because the Ukrainians are pretty good at drones, aren’t they?

SOPHIE BUSHWICK: That’s right. One of the really interesting things about this conflict is the use of tools like hobbyist drones that maybe weren’t intended for warfare originally, but people are innovating and turning them into military tools. I mean, whether we think that’s a good thing or a bad thing, it depends on your perspective. But this adding solar panels to it is now the latest twist in the saga.

IRA FLATOW: So it could lurk around for as long as the solar panels.

SOPHIE BUSHWICK: That’s right. It seems to be– the panels right now that they’re using are a little heavy. And again, these drones weren’t designed with that type of modification in mind, so that might limit the amount of power it’s allowed to get out of it.

It might be something like the power wouldn’t be used to keep the drone flying, but it could allow the drone’s sensors to recharge. So if the drone parks itself in some location and then it uses these chargers to keep its sensors alive, it could just not move and keep a digital eye out for anyone coming near. And then once it senses a target, that’s when it kicks into gear and flies there to attack.

IRA FLATOW: There’s another tech that’s a bit more hopeful, and we’re talking here about batteries based on rust. Wow, they should see my old car. They could make–

SOPHIE BUSHWICK: [LAUGHS] I think this is such a cool idea. And I mean, this is based on the idea that when you’ve got renewable power, it ebbs and flows. Solar panels are great when the sun is shining, but you need some sort of battery to store that power for the times when the energy is not so abundant. And so a lot of times that means plugging a battery into the grid that is manufactured in China made out of lithium iron phosphate.

And the problem is those batteries, they don’t hold charge for as long as you would like, just about four to six hours. And they can be quite expensive. So now researchers have developed a battery made from some of the cheapest materials you can find, air and iron. And the claim is that these can hold their charge for 100 hours or longer.

IRA FLATOW: Sophie, I find this rust battery thing something I have to know more about. Give me some more details on this.

SOPHIE BUSHWICK: Right. So the way this works is it charges by– it takes electricity, feed it into the system, and it uses that to convert iron oxides into– iron oxides are a form of rust, and it transforms this rust back into iron. And then when it’s time for the battery to discharge, it can release this energy by reacting with oxygen in the air to turn back into rust.

IRA FLATOW: Wow. And so this is– because rust is everywhere, this is really cheap, right?

SOPHIE BUSHWICK: Right.

IRA FLATOW: You don’t need special minerals, hard to dig up out of the ground, to do this.

SOPHIE BUSHWICK: Exactly. That’s one of the really cool things about this. It’s just taking iron and turning it into rust and then turning it back into iron. And that’s how the battery works, which means what you need is air, which we have a lot of, and iron, which is pretty easy for most places to source.

IRA FLATOW: Wow. Let’s move on from rust to diamonds. I already think of diamonds as super strong, the strongest materials on Earth. But there’s now a new champion, a new, stronger diamond in town?

SOPHIE BUSHWICK: Yes, diamonds can be made even stronger by growing them in a hexagonal shape. So the way that diamonds are is they are molecules ordered in a cubic crystalline structure. And researchers have seen hints that you could have hexagonal diamond, but it’s only been found in small amounts. And that’s when it’s mixed in with cubic diamonds.

And researchers have tried to grow it before, but until now, they haven’t succeeded. And now they’ve grown a relatively large sample of hexagonal diamond. And it’s mostly 100% hexagonal without any cubic diamond mixed in.

IRA FLATOW: Wow. Wow. I’m not getting that any time soon in my jewelry store, I don’t think.

SOPHIE BUSHWICK: Maybe not. It’s still going to take some work to grow it in larger amounts. So far they’ve grown a piece that’s about 1 millimeter wide, so very, very small. But if they could scale this up, the hexagonal diamond is about 60% harder than your regular diamond.

IRA FLATOW: Really?

SOPHIE BUSHWICK: Which means it could be used for things like drilling and making much more resilient tools.

IRA FLATOW: Love it. All right. You know I love weird quantum stuff, and you have a story about how quantum entanglement might not just be a one-time thing? Tell me about that.

SOPHIE BUSHWICK: This is super cool. So when two particles are quantum entangled, it means they’re linked together in such a way that they can do things like spooky action at a distance. They have all these weird shared behaviors.

And you’re used to thinking about quantum entanglement like a link. But what if you could think about it as a bank, something you could tap into? Researchers found out that if you have a pair of hypothetical experimenters and they’ve got these entangled particles, they can share that entanglement with another pair of experimenters. And then it can be shared again and again. In fact, they can keep on doing this indefinitely, as if our little bank of entanglement is an almost infinite one.

IRA FLATOW: Wow. Why would they want to do that? Why do we care?

SOPHIE BUSHWICK: Well, if you want to have something entangled, which entanglement is required for things like quantum computing or quantum communication, you can create entanglement from scratch. But the idea is sharing it might be an easier way to get more entanglement out there.

IRA FLATOW: Sure, I get that. I get it. Finally, something sweet to end on, a super old sample of honey. Really?

SOPHIE BUSHWICK: That’s right. So near Pompeii, there’s this ancient shrine. And in it, researchers, in 1954, they found these pots with a sticky residue. And they thought at the time that it was animal or vegetable fat, but they noticed it was contaminated with pollen and insect parts.

And then now researchers have used more advanced techniques to analyze the residue of this substance. They’ve used things like gas chromatography and mass spectrometry. And they found a lot of sugars and some complex acids and some proteins that are found in royal jelly. They even found some protein fragments from a mite that we know feeds on honeybees. So we’re pretty sure that this pot used to hold ancient honey.

IRA FLATOW: Anybody stick their finger and taste it to see if it was?

SOPHIE BUSHWICK: [LAUGHS] Unfortunately, these were corked, and the seals have since degraded. And so I don’t think you would really enjoy tasting whatever is left of this honey. Bacteria has gotten into it. It’s not going to be a yummy taste, but we know it once was. Maybe Winnie the Pooh can try it.

IRA FLATOW: [LAUGHS] All right, Sophie. Always great to have you come and talk with us. Thanks for taking time to be with us today.

SOPHIE BUSHWICK: Thanks for having me.

IRA FLATOW: Sophie Bushwick, senior news editor at New Scientist here in New York.

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We have to take a break. And when we come back, scientists have successfully trained a robot to perform surgery without the help of a surgeon.

AXEL KRIEGER: We didn’t expect that we would get to a point where we didn’t need any human intervention, so this was really even better than we anticipated.

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IRA FLATOW: You’ve had surgery recently, your surgeon might have been a robot. Yeah, almost a quarter of all surgeries in the US use robots. But don’t be alarmed because every one of the robot’s movements in the operating room is actually controlled by a surgeon.

But there is change in the wind because, for the first time, researchers at Johns Hopkins University have trained a robot to do surgery on its own, a portion of a gallbladder surgery, on a test pig cadaver. The encouraging results were published last month in the journal Science Robotics.

Joining me now to dissect how he trained the robot to accomplish this feat and what it means for the future of robotic surgery is my guest, Doctor Axel Krieger, associate professor in mechanical engineering at Johns Hopkins University, based in Baltimore, Maryland. Welcome to Science Friday.

AXEL KRIEGER: Thank you so much for having me.

IRA FLATOW: You’re quite welcome. Can you walk me through what part of the surgery the robot was able to perform all by itself?

AXEL KRIEGER: Yes. There are about three large portions of gallbladder surgery. The first one is a dissecting the gallbladder from the liver bed. The second part– that’s what we really focused on– is the precision clipping and cutting of the artery and the bile duct.

So this is going in with small little clippers and identifying where the artery is, placing three plastic clips in it, and then identifying where the bile duct is, then placing three plastic clips in that, and then dissecting between the clips so that the gallbladder then in the third procedural step can be effectively removed.

And so that’s a very complex, lengthy step and really requires a lot of precision. And there’s a lot of deformation of the tissue and anatomical variations even between healthy pigs.

IRA FLATOW: Right. So how do you train a robot to do this?

AXEL KRIEGER: We used a technique called imitation learning. We can effectively now watch expert surgeons perform these steps and then repeat these steps over and over and then train a network to learn to then reproduce those steps. So we can tie what the robot sees to what the robot should do, so it’s a hierarchical framework that first predicts the right phase of the surgery and then predicts what the robot should do, given the certain video image that the robot sees currently.

IRA FLATOW: What happens if the robot makes a mistake? I mean, is it able to correct itself before it does something really bad?

AXEL KRIEGER: Yeah. The really nice thing that we demonstrated in our study is that our robot is capable to adapt to small little misplacements. So imagine if the clipper doesn’t catch the artery perfectly on the first try. The system automatically recognizes that and then self-corrects.

That’s one way, so self-correction by the robotic systems. And then also the surgeon would then be the supervisor and could always stop and take over and complete the procedure manual if necessary. In our study, in eight consecutive pick surgeries, we didn’t need any interventions. But if something unforeseen happens, the surgeon can always intervene and take over.

IRA FLATOW: Were you surprised yourself just how well the robot performed here?

AXEL KRIEGER: Yeah, super exciting result. When we set out on this project, we didn’t expect that we would get to a point where we didn’t need any human intervention. So this was really even better than we anticipated.

IRA FLATOW: Let’s talk about getting to that point. How do you get to that point? How big a jump in technology is this new robot from other older ones?

AXEL KRIEGER: It’s a major step forward. In older systems, we were able to automate maybe one small task, one little step. And now tying these steps effectively together and recognizing small mistakes and then consecutively performing these sub steps to do a big chunk of a surgical procedure, that’s a huge step forward.

IRA FLATOW: Yeah, because you’ve been designing robots to do this itself for a few years now, right?

AXEL KRIEGER: Absolutely. We published a study in 2022 where we did a step called the anastomosis, so that’s suturing of tubular structures. And so we were able to perform that suturing step. But what’s really exciting now is that we can boost up the success rate. And we have this framework that is more general, so we can train it for all different types of procedures, not just one step. But by adding more data, we can just learn more procedures and really get closer to clinical viability of this technology.

IRA FLATOW: I watched a video you put online of the robot actually doing this work, and I was surprised how well it did it. I mean, how does the robot’s work compare to a human surgeon?

AXEL KRIEGER: In our study, we really wanted to demonstrate the feasibility of this technology, so we didn’t do a very thorough evaluation comparing to expert surgeons. We did a small little comparison to one surgeon and showed that our robot is a bit slower. We ran it quite slow so we can intervene if something happens. But the movement was more smooth compared to the expert surgeon, so really some early indication that we are getting on par with even an expert surgeon there.

IRA FLATOW: And what about other kinds of surgeries? Now that you’ve had success with this, do you see you’re able to expand to others besides just gallbladder surgery?

AXEL KRIEGER: Yeah. For us, this is a fantastic starting point. Gallbladder surgery was the first surgery that was performed minimally invasively, so has this lighthouse character of a new technique for surgery. So that’s why it’s such a good target.

But we are excited to use this technology now for other applications, for other surgeries. A big one that we are working on right now is precision tumor resection, where it’s so difficult to delineate where the tumor is from the healthy tissue and cutting that out. That is so difficult for surgeons, and we really want to use this technology to improve surgical techniques.

IRA FLATOW: Yeah. Yeah, I was going to ask you about the benefit of a robot that can do surgery without human intervention. But you’re saying here that in some cases it can do better than the surgeon.

AXEL KRIEGER: Yeah, that’s what we are working on. So integrating preoperative scans effectively, so seeing where the tumor is on other imaging and then combining it effectively with surgical videos, that’s the next big goal that we’re working on. And that is very hard for human surgeons to map these things together in their head, and so doing this with a robot we might be able to even boost expert surgical performance.

IRA FLATOW: Are you saying a robot independent of a surgeon guiding it or with surgeon supervision?

AXEL KRIEGER: Always surgeon supervision. Our goal is not to replace surgeons. We want to just make the surgery easier and help surgeons work with this rising caseload.

We have an aging society, more surgeries needed. And so the individual caseload is doubling in the next 10 years. So how can we help surgeons with that? How can we do an effective surgery later in the day when the surgeon might get tired? By helping the surgeon, not having to do every part and every little step of every surgery but then, for portions of it, just watch the robot do it and then intervene if necessary. That can really improve the effectiveness and the efficiency of surgeries.

IRA FLATOW: A lot of surgeries are done today through lap surgery, laparoscopy, right? Can the robot do that also?

AXEL KRIEGER: Yeah, absolutely. So the big improvement of using surgical robots is making it easier to do laparoscopic surgery, minimally invasive surgery. So traditionally, surgeons had to perform large incisions and work with the organs directly, with the hands, guidance directly with the eyes. Now we use cameras and small ports, and we use surgical tools in ports. And the surgical robot that we are working with is a minimally invasive keyhole surgery robot, and so we can do this procedure minimally, yes.

IRA FLATOW: All right. Now, we have listeners who are listening to this, and they’re going to ask, how do I get in on this? How soon might patients see autonomous robots, perhaps this gallbladder surgery, in the operating room?

AXEL KRIEGER: We are super excited to take the next steps and go to do a preclinical study. So demonstrating this in live pig surgeries, that’s our next steps that we are very, very hardworking on right now. I also see that, similarly to modern cars where we have some autonomous functions, like brake assist, park assist, those autonomous functions, we see those coming in surgical robotic systems for the next few years.

So for example, the FDA approved recently a camera system that can follow the surgery autonomously. So the camera is moving autonomously, not the surgical tools. And now we can see maybe suction, maybe holding tissue, those things to be coming over the next few years. It’s going to take a while before procedures like gallbladders are implemented clinically and commercially, but we can definitely see the path forward for those.

IRA FLATOW: So what’s your next work here? You were studying this on a pig cadaver. Do you ever get to the living, breathing pig section?

AXEL KRIEGER: That’s exactly the next step. So we demonstrated this on pig cadavers, and now we are working very hard to see if we can do this in a living pig. That would be the next step. And then if we demonstrate that this is safe and effective, then we can really design a first-in-human study and work on the regulatory approval for that.

IRA FLATOW: What’s the most challenging part about creating and training these robots?

AXEL KRIEGER: The most challenging part is getting the right training data. So we acquired about 30 different cadavers from butchers and then tested on all different anatomy and variations in the lab to acquire our testing data. And we also needed to predict how our robot might make small little mistakes and then add them manually to the training data, so start some procedures with maybe the clipper or the cutter being a little bit misaligned from the target so that we can self-correct then during the procedure.

So you become a bit of a robot whisperer. You anticipate mistakes, how could I fail? and then add that to the training data. So that’s probably the most complex part of our work.

IRA FLATOW: We have run out of time. I didn’t get to ask you about how a robot scrubs up for surgery, but that’s for the next time. We can talk about that.

AXEL KRIEGER: Thank you so much. That was fantastic questions.

IRA FLATOW: You’re quite welcome, and come on back when you’re working in a little more in vivo in live pigs.

AXEL KRIEGER: Absolutely. Would love to come back. Thank you so much for your interest and this fantastic interview. Really enjoyed it.

IRA FLATOW: You’re welcome. Doctor Alex Krieger, associate professor in mechanical engineering at Johns Hopkins University in Baltimore, Maryland.

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Thanks for listening. And don’t forget to rate and review the podcast, but only if you like the show. This episode was produced by Charles Bergquist and Shoshannah Buxbaum. See you next time. I’m Ira Flatow.

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