But if they can be pushed to be faster and more nimble, drones could be put to use in time-critical operations beyond the race course, for instance to search for survivors in a natural disaster.

Now, aerospace engineers at MIT have devised an algorithm that helps drones find the fastest route around obstacles without crashing. The new algorithm combines simulations of a drone flying through a virtual obstacle course with data from experiments of a real drone flying through the same course in a physical space.

The researchers found that a drone trained with their algorithm flew through a simple obstacle course up to 20 percent faster than a drone trained on conventional planning algorithms. Interestingly, the new algorithm didn’t always keep a drone ahead of its competitor throughout the course. In some cases, it chose to slow a drone down to handle a tricky curve, or save its energy in order to speed up and ultimately overtake its rival.

“At high speeds, there are intricate aerodynamics that are hard to simulate, so we use experiments in the real world to fill in those black holes to find, for instance, that it might be better to slow down first to be faster later,” says Ezra Tal, a graduate student in MIT’s Department of Aeronautics and Astronautics. “It’s this holistic approach we use to see how we can make a trajectory overall as fast as possible.”

“These kinds of algorithms are a very valuable step toward enabling future drones that can navigate complex environments very fast,” adds Sertac Karaman, associate professor of aeronautics and astronautics, and director of the Laboratory for Information and Decision Systems at MIT. “We are really hoping to push the limits in a way that they can travel as fast as their physical limits will allow.”

Tal, Karaman, and MIT graduate student Gilhyun Ryou have published their results in the International Journal of Robotics Research.

Fast effects

Training drones to fly around obstacles is relatively straightforward if they are meant to fly slowly. That’s because aerodynamics such as drag don’t generally come into play at low speeds, and they can be left out of any modeling of a drone’s behavior. But at high speeds, such effects are far more pronounced, and how the vehicles will handle is much harder to predict.

“When you’re flying fast, it’s hard to estimate where you are,” Ryou says. “There could be delays in sending a signal to a motor, or a sudden voltage drop which could cause other dynamics problems. These effects can’t be modeled with traditional planning approaches.”

To get an understanding for how high-speed aerodynamics affect drones in flight, researchers have to run many experiments in the lab, setting drones at various speeds and trajectories to see which fly fast without crashing — an expensive, and often crash-inducing training process.

Instead, the MIT team developed a high-speed flight-planning algorithm that combines simulations and experiments, in a way that minimizes the number of experiments required to identify fast and safe flight paths.

The researchers started with a physics-based flight planning model, which they developed to first simulate how a drone is likely to behave while flying through a virtual obstacle course. They simulated thousands of racing scenarios, each with a different flight path and speed pattern. They then charted whether each scenario was feasible (safe), or infeasible (resulting in a crash). From this chart, they could quickly zero in on a handful of the most promising scenarios, or racing trajectories, to try out in the lab.

“We can do this low-fidelity simulation cheaply and quickly, to see interesting trajectories that could be both fast and feasible. Then we fly these trajectories in experiments to see which are actually feasible in the real world,” Tal says. “Ultimately we converge to the optimal trajectory that gives us the lowest feasible time.”

Going slow to go fast

To demonstrate their new approach, the researchers simulated a drone flying through a simple course with five large, square-shaped obstacles arranged in a staggered configuration. They set up this same configuration in a physical training space, and programmed a drone to fly through the course at speeds and trajectories that they previously picked out from their simulations. They also ran the same course with a drone trained on a more conventional algorithm that does not incorporate experiments into its planning.

Overall, the drone trained on the new algorithm “won” every race, completing the course in a shorter time than the conventionally trained drone. In some scenarios, the winning drone finished the course 20 percent faster than its competitor, even though it took a trajectory with a slower start, for instance taking a bit more time to bank around a turn. This kind of subtle adjustment was not taken by the conventionally trained drone, likely because its trajectories, based solely on simulations, could not entirely account for aerodynamic effects that the team’s experiments revealed in the real world.

The researchers plan to fly more experiments, at faster speeds, and through more complex environments, to further improve their algorithm. They also may incorporate flight data from human pilots who race drones remotely, and whose decisions and maneuvers might help zero in on even faster yet still feasible flight plans.

“If a human pilot is slowing down or picking up speed, that could inform what our algorithm does,” Tal says. “We can also use the trajectory of the human pilot as a starting point, and improve from that, to see, what is something humans don’t do, that our algorithm can figure out, to fly faster. Those are some future ideas we’re thinking about.”

This research was supported in part by the Office of Naval Research.

That’s the surprising new finding by University of British Columbia and University of Wisconsin-Madison researchers, detailed today in Proceedings of the National Academy of Sciences.

Triantha — a species of false asphodel — is the first new carnivorous plant to be identified by botanists in 20 years. It is notable for the unusual way it traps prey with sticky hairs on its flowering stem.

“Carnivorous plants have fascinated people since the Victorian era because they turn the usual order of things on its head: this is a plant eating animals,” said co-author Dr. Sean Graham, a professor in the department of botany at UBC. “We’re thrilled to have identified one growing right here in our own backyard on the west coast.”

The plant grows in nutrient-poor, boggy but bright areas on the west coast of North America, from California to Alaska. For the study, the researchers investigated specimens growing on Cypress mountain in North Vancouver, British Columbia.

“What’s particularly unique about this carnivorous plant is that it traps insects near its insect-pollinated flowers,” said lead author Dr. Qianshi Lin, a PhD student at UBC botany at the time of the study. “On the surface, this seems like a conflict between carnivory and pollination because you don’t want to kill the insects that are helping you reproduce.”

“We believe that Triantha is able to balance carnivory with pollination because its glandular hairs are not very sticky and can only trap midges and other small insects, so that the much larger and stronger bees and butterflies that act as its pollinators are not captured,” said co-author Dr. Tom Givnish, a professor in the department of botany at the University of Wisconsin-Madison.

The research builds on previous work in Dr. Graham’s lab, which found that Triantha lacked a particular gene that is often missing in other carnivorous plants.

In order to investigate if the plant was indeed partial to snacking on insects, Dr. Lin attached fruit flies labelled with nitrogen-15 isotopes to its flowering stem. The label acted like a tracking device, allowing Dr. Lin to trace changes in nitrogen uptake by the plant.

He then compared the results with those from similar experiments on other species that grow in the same area, including a recognized carnivorous plant (a sundew) and several non-carnivorous plants as controls.

Isotopic analysis showed significant uptake of nitrogen by Triantha, which obtained more than half its nitrogen from prey -comparable to sundews in the same habitat, and other carnivorous plants elsewhere.

The study also found that the sticky hairs on the Triantha flower stalk produce phosphatase, a digestive enzyme used by many carnivorous plants to obtain phosphorus from prey.

The proximity of Triantha to major urban centres in western Canada and the Pacific coast in the United States suggests that other carnivorous plants — and many other ecological surprises — remain to be discovered, even in well-studied ecosystems.

But if you’re tempted to recreate the film, Little Shop of Horrors, or bring Triantha home to deal with pesky summer fruit flies, the researchers warn the plant doesn’t do well outside of its natural environment and advise admiring its quirks from a distance.

This research was supported by Cypress Provincial Park, the Natural Sciences and Engineering Research Council of Canada (NSERC) and the National Science Foundation (NSF).

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Materials provided by University of British Columbia. Note: Content may be edited for style and length.

In a new study appearing Aug. 9 in the journal Frontiers in Ecology and Evolution, Duke researchers have found evidence for antibiotic resistance in the microbiome of lemurs living close to humans. And the closer the contact, the more antibiotic resistance they found.

The research team, graduate student Sally Bornbusch and Christine Drea, Professor of Evolutionary Anthropology at Duke University, sampled the dung of ring-tailed lemurs and sequenced the genes of all microbes found there, looking for genetic markers of antibiotic resistance.

The study compared 10 lemur populations: seven wild populations in Madagascar, two from research facilities — the Lemur Rescue Center in Madagascar and the Duke Lemur Center in the United States — and finally a group of lemurs kept as pets in Madagascar.

In wild animals, the average proportion of resistance genes in the gut microbiomes was close to zero. But in animals from research facilities, that proportion was more than 25 times greater than in wild lemurs. In pet lemurs, the proportion was almost 35 times greater.

Some of this is likely due to good veterinary care: lemurs living in research facilities are treated for infections when needed, and so have greater direct exposure to antibiotics than their wild cousins.

However, pet lemurs that likely never receive veterinary care harbored the highest abundance of antibiotic resistance genes.

Keeping a lemur as a pet is illegal in Madagascar, so those who keep lemurs are unlikely to take these animals to a veterinarian and risk facing legal consequences. These pet lemurs are therefore acquiring the antibiotic resistant microbes simply by sharing their environment with humans and domestic animals.

Ring-tailed lemurs are omnivores and generalists who will eat dirt, excrement, and whatever they can get hold of. In a domestic household, they are often in constant contact with humans, perched on their owner’s shoulders, or in the arms of tourists willing to pay for a photo (a practice that is harmful to both humans and animals).

Bornbusch said that this physical and social environment is apparently contributing to pet lemurs’ antibiotic resistance.

“Microbes are like an overlaying blanket on everything. They’re not only in our guts, but also on our skin, our furniture, and in our food and water,” Bornbusch said. “They’re everywhere, all the time, and they are easily transmitted between environments.”

Among wild lemurs, antibiotic resistance varied along a gradient of human activity. Animals from areas impacted by cattle grazing, farming, or tourism harbored more antibiotic resistant microbes than those from more pristine environments, but still far less than lemurs living in close proximity to humans.

“Antibiotic treatment is clearly not the only mechanism leading to a higher abundance of resistance genes in these animals,” Bornbusch said.

In fact, even among lemurs housed at research facilities, those with no previous antibiotic treatment harbored similar numbers of antibiotic resistance genes compared to lemurs at the same facility that had been treated many times for infections.

Proximity to humans also determined the type of resistance genes that were acquired. The microbiomes of ring-tailed lemurs from Madagascar showed signs of resistance to antibiotics used to combat outbreaks of plague, while lemurs from the Unites States showed resistance to antibiotics frequently prescribed in North America.

Antibiotic resistance genes are nothing new. Microbes have been mutating and evolving resistance genes for millions of years in an arms race with naturally occurring antibiotics.

In a natural scenario, this process rarely poses problems. But things started to go awry when humans harnessed the power of naturally occurring antibiotics and released human-made antibiotics to the public.

“Humans came along, developed antibiotics, spread them all around us, and propagated these resistance genes into natural environments and into the microbiomes of wildlife,” Bornbusch said. Though grim, these results can have a positive impact on conservation and wildlife management practices.

“Even if these results are slightly scary, they help us use microbiome science to hone veterinary practices and conservation activities,” Bornbusch said. She also said that more research is needed to better understand the impact of these resistance genes on wildlife.

“Right now, we know that these resistance genes are out there, but we don’t know whether they are truly harmful to lemurs,” said Bornbusch. “These results give us a stepping-stone for research on the impact of these resistant microbes on wildlife and their environment.”

Funding for this study came from an NSF Doctoral Dissertation Research Improvement Grant to Bornbusch and Drea (award #1945776), an NSF Behavioral and Cognitive Sciences Grant to Drea (award# 1749465), a Graduate Student Research Grant to Bornbusch from the Triangle Center for Evolutionary Medicine, and a Research fellowship to Bornbusch from The Kenan Institute for Ethics at Duke University.

“There wasn’t an onset of an imbalance until about 1990, which is later than most estimates,” said DeVries, an associate professor in the Department of Geography, and a co-author on a paper that appears in the journal Nature Communications. According to the study, the period from 1950 to1990 saw temperature fluctuations in the water column but no net warming. After 1990, the study continues, the entire water column switched from cooling to warming.

These findings are the result of the addition of a largely underexplored factor in ocean heat content (OHC): deep ocean temperatures.

“Prior studies didn’t consider the deep ocean,” said Bagnell, a graduate scholar in DeVries’ laboratory and the paper’s lead author. Because of the challenges involved in getting temperature measurements in the deep ocean (below 2,000 meters) that region has gone largely unaccounted for, and data has been sparse. “There is some existing data, from research cruises and autonomous floats,” he added.

The researchers used an autoregressive artificial neural network (ARANN) and machine learning methods to connect the dots between data points and “produce a single consistent estimate of the top-to-bottom OHC change for 1946 to 2019.” The result was a trend that delays warming by decades over previous models.

There are two main possibilities for why the effects of global warming took so long to reach the ocean, De Vries said.

“One is that anthropogenic warming might have been weaker than previously thought during the 20th century, perhaps due to the cooling effects of aerosol pollution,” he said. The other is that the deep ocean may still be exhibiting the effects of climate events long past.

“It can take centuries for climate signals to propagate from the surface to the interior,” he said. Thus, the effects of a cooling event such as the Little Ice Age might be deep history to us on the surface, but the echoes of the event may have continued to resonate in the deep ocean into the 20^th century, providing a buffer to the warming Earth.

The delayed cooling effect ended in 1990, after which ocean temperatures, according to the study, have been accelerating upward.

“The lag is catching up and the ocean is warming more strongly now,” Bagnell said. The Atlantic Ocean and Southern Ocean are currently where most of the warming is, with the Pacific Ocean and Indian Ocean not far behind.

Ocean warming is a concern on many levels, as it can cause changes in circulation, reduce its ability to absorb carbon and fuel more intense storms, in addition to causing sea level rise and creating inhospitable environments for undersea life. If the trend continues, the effects might last centuries, thanks to the same lag that kept the oceans cool until the last 30 years.

“The ocean remembers,” DeVries said.

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Materials provided by University of California – Santa Barbara. Original written by Sonia Fernandez. Note: Content may be edited for style and length.