Wildlife tracking is nothing new, but it's certainly not without limitations. When pursuing animals, particularly birds, in some places like rough mountains and vast oceans, the traditional method, VHF tracking which uses GPS tags (跟踪器), often ends up with the signal of animals lost.

A newly developed set of UAVs (无人机) with radio tags aims to solve this problem. ''The swift parrot was the original inspiration for the development of the system. The swift parrots are migratory (季节迁徙的) birds. Before reaching their destination, they'll fly across vast areas of land. Besides, during their flying, they tend to choose a random place for temporary food and rest. And they use different areas as their destinations each year depending on where their food is available. So their destinations each year can also be random. The randomnness can make it hard for us to judge in advance where they'll exactly go and more difficult to track them,"explains Saunders.

"So it's necessary to use tags to track them. But GPS tags are not congruent with swift parrots since these creatures are too small, which makes it hard to attach the large GPS tags to them. Besides, GPS signals can be poor in remote and rough areas. Therefore we had to find a new way to search large pieces of land more effectively. We had an idea to attach smaller radio tags to them and use particular UAVs to track those radio tags to study their movements."

These UAVs only need to fly beside the parrots to track their whereabouts while other systems need to fly directly overhead for a visual sighting. Saunders says, "Our system listens for tag signals, and works most effectively at a distance so it can identify where the animals are and help us observe them without influencing their flying routes."

As for the improvement of UAVs, now the scientists want to develop a version that has stronger lifting ability and flies farther without being charged in the midway. And then it can track animals in more remote and rough surroundings that were previously inaccessible, and shed light on species that have been unable to be tracked until now.

Video has become an increasingly popular educational tool. As a storytelling medium, video is in many ways superior to text or lecture-based instruction, but it is not without disadvantages. It can be difficult to search or find already seen content for review. And note-taking is especially laborious (费力的).

Hari Subramonyam, a research professor in the Stanford Graduate School of Education, and two workmates, have used computer vision and natural language processing tools to develop VideoSticker a note-taking application specifically for video-based learning.

VideoSticker combines video, transcripts (文本), and a powerful visual and textual note-taking application. Better yet using AI, VideoSticker can automatically identify and trim (修剪) objects out of the video and place them in the note-taking area. VideoSticker then deals with the transcripts using tools like those behind popular voice recognition and chatbots to pull key text into the note-taking area, combining it with the relevant imagery.

It all adds up to a big head start on manual (手工的) note-taking and allows students to focus on the important content to improve comprehension and recall.

To evaluate the effectiveness of the VideoSticker approach, the researchers conducted a test with 10 undergraduate students. Each completed a 75-to-90-minute note-taking session. They then reported their experiences. All participants noted VideoSticker’s flexibility in note-taking. “Trimming the objects and controlling them in the video viewing panel is cool,” notes one participant.

“Overall, I think VideoSticker is a great example of AI making a good combination with the learning context to balance manual note-taking with the experience of learning that is so important to real comprehension”, Subramonyam says. “As video becomes more commonplace in the classroom, as it is sure to in coming years, a tool like this will be very much needed. Going forward, my team plans to partner with educators to evaluate VideoSticker in real-world learning contexts and make the tool commercially available.”

A living robot has been created out of frog skin cells. Xenobots, named after the frog species Xenopus laevis that the cells come from, were first described last year. Now the team behind the robots has improved their design and demonstrated new capabilities.

To create the xenobots, Michael Levin at Tufts University in Massachusetts and his colleagues obtained tissue from 24-hour-old frog embryos after very small physical operation. Where the previous version relied on the contraction of heart muscle cells to move them forward by pushing off surfaces, these new xenobots swim around faster. They also live between three and seven days longer than their previous generation, which only lasted about seven days, and have the ability to sense their surroundings to some extent, turning red when exposed to blue light.

“The fundamental finding here is that when you free skin cells from their normal context, and you give them a chance to build other things than what they normally build,” says Levin. “To me, one of the most exciting things here is that they are plastic. This idea that even normal cells, not genetically modified, are in fact capable of building something completely different.”

Because they are created from cells, the xenobots eventually break apart and are totally biodegradable, says team member Douglas Blackiston, also at Tufts University. He therefore hopes that they can be used for biomedical and environmental applications.

Previous attempts at creating living robots, such as a wirelessly controlled cockroach, have involved dealing with live animals, raising ethical concerns. Xenobots differ from these because they are made entirely of living cells. “The approach here is maybe ethically the least problematic because everything starts with cells. They have no neurons, so it's not an animal,” says Auke ljspeert at the Swiss Federal Institute of Technology at Lausanne, who wasn't involved in the research. “It's really cells, so I find it maybe the cleanest way."