However, nature has shown that vision doesn’t have to be constrained by light’s limitations — many organisms have evolved ways to perceive their environment without relying on light. Bats navigate using the echoes of sound waves, while sharks hunt by sensing electrical fields from their prey’s movements.

Radio waves, whose wavelengths are orders of magnitude longer than light waves, can better penetrate smoke and fog, and can even see through certain materials — all capabilities beyond human vision. Yet robots have traditionally relied on a limited toolbox: they either use cameras and LiDAR, which provide detailed images but fail in challenging conditions, or traditional radar, which can see through walls and other occlusions but produces crude, low-resolution images.

Now, researchers from the University of Pennsylvania School of Engineering and Applied Science (Penn Engineering) have developed PanoRadar, a new tool to give robots superhuman vision by transforming simple radio waves into detailed, 3D views of the environment.

“Our initial question was whether we could combine the best of both sensing modalities,” says Mingmin Zhao, Assistant Professor in Computer and Information Science. “The robustness of radio signals, which is resilient to fog and other challenging conditions, and the high resolution of visual sensors.”

In a paper to be presented at the 2024 International Conference on Mobile Computing and Networking (MobiCom), Zhao and his team from the Wireless, Audio, Vision, and Electronics for Sensing (WAVES) Lab and the Penn Research In Embedded Computing and Integrated Systems Engineering (PRECISE) Center, including doctoral student Haowen Lai, recent master’s graduate Gaoxiang Luo and undergraduate research assistant Yifei (Freddy) Liu, describe how PanoRadar leverages radio waves and artificial intelligence (AI) to let robots navigate even the most challenging environments, like smoke-filled buildings or foggy roads.

PanoRadar is a sensor that operates like a lighthouse that sweeps its beam in a circle to scan the entire horizon. The system consists of a rotating vertical array of antennas that scans its surroundings. As they rotate, these antennas send out radio waves and listen for their reflections from the environment, much like how a lighthouse’s beam reveals the presence of ships and coastal features.

Thanks to the power of AI, PanoRadar goes beyond this simple scanning strategy. Unlike a lighthouse that simply illuminates different areas as it rotates, PanoRadar cleverly combines measurements from all rotation angles to enhance its imaging resolution. While the sensor itself is only a fraction of the cost of typically expensive LiDAR systems, this rotation strategy creates a dense array of virtual measurement points, which allows PanoRadar to achieve imaging resolution comparable to LiDAR. “The key innovation is in how we process these radio wave measurements,” explains Zhao. “Our signal processing and machine learning algorithms are able to extract rich 3D information from the environment.”

One of the biggest challenges Zhao’s team faced was developing algorithms to maintain high-resolution imaging while the robot moves. “To achieve LiDAR-comparable resolution with radio signals, we needed to combine measurements from many different positions with sub-millimeter accuracy,” explains Lai, the lead author of the paper. “This becomes particularly challenging when the robot is moving, as even small motion errors can significantly impact the imaging quality.”

Another challenge the team tackled was teaching their system to understand what it sees. “Indoor environments have consistent patterns and geometries,” says Luo. “We leveraged these patterns to help our AI system interpret the radar signals, similar to how humans learn to make sense of what they see.” During the training process, the machine learning model relied on LiDAR data to check its understanding against reality and was able to continue to improve itself.

“Our field tests across different buildings showed how radio sensing can excel where traditional sensors struggle,” says Liu. “The system maintains precise tracking through smoke and can even map spaces with glass walls.” This is because radio waves aren’t easily blocked by airborne particles, and the system can even “capture” things that LiDAR can’t, like glass surfaces. PanoRadar’s high resolution also means it can accurately detect people, a critical feature for applications like autonomous vehicles and rescue missions in hazardous environments.

Looking ahead, the team plans to explore how PanoRadar could work alongside other sensing technologies like cameras and LiDAR, creating more robust, multi-modal perception systems for robots. The team is also expanding their tests to include various robotic platforms and autonomous vehicles. “For high-stakes tasks, having multiple ways of sensing the environment is crucial,” says Zhao. “Each sensor has its strengths and weaknesses, and by combining them intelligently, we can create robots that are better equipped to handle real-world challenges.”

This study was conducted at the University of Pennsylvania School of Engineering and Applied Science and supported by a faculty startup fund.

Extreme weather events, such as tropical and extratropical cyclones and tornadoes, can cause widespread damage to forests, leading to environmental and financial losses. When trees fall during these storms, ecosystems might be disrupted, increasing forest management costs. As climate change worsens, severe storms are expected to become more frequent, making it crucial to understand how forests respond to wind stress.

Grasping the mechanisms behind tree failure is key to developing strategies for mitigation. While previous studies have explored how trees react to wind, it is unclear whether these responses remain consistent across different forest configurations — characterized by tree spacing and density — and weather conditions.

In this vein, a team of researchers led by Associate Professor Kana Kamimura from the School of Science and Technology at Shinshu University, Japan, investigated tree movements under various forest configurations and weather conditions, including how trees resist winds. The research team included Kazuki Nanko, Asako Matsumoto, and Saneyoshi Ueno from the Forestry and Forest Products Research Institute, Japan, and Barry Gardiner from the University of Freiburg, Germany, and the Institut Européen de la Forêt Cultivée, France. This paper was made available online on August 27, 2024, and was published on November 1, 2024, in Volume 571 of Forest Ecology and Management.

Explaining their motivation behind the study, Prof. Kamimura says, “Several techniques have been developed to predict wind damage. However, they largely depend on empirical data and parameters, and overlook how wind damage occurs. Our research aims to shed light on how winds directly impact trees and how trees reduce the stress from winds to survive.”

To achieve this, researchers set up two experimental plots of Cryptomeria japonica trees, commonly known as the Japanese cedar, in November 2017 in the experimental forests operated by the Forestry and Forest Products Research Institute, Kasumigaura City, Japan. In the first plot, P-100 consisted of 3,000 trees per hectare, creating a dense forest. In the second plot, P-50, half of the trees were removed for this research, leaving 1,500 trees per hectare to mimic thinning practices. Over two years, the team monitored 24 trees in the dense plot and 12 in the thinned plot, using trunk-mounted sensors to track tree sway during various wind conditions. The monitoring period included multiple typhoons, such as Typhoon Trami, in 2018, which caused significant damage to the thinned plot.

The researchers found that cedar trees exhibit two distinct swaying patterns depending on wind speed. In light winds, the trees swayed at around 2 to 2.3 cycles per second, with their branches absorbing much of the wind energy, protecting the trunks and roots from wind stress. However, at higher wind speeds, the trees shifted to a slower swaying pattern of 0.2 to 0.5 cycles per second. In this phase, the whole tree swayed together, transferring force across the trunk and roots, increasing the probability of breakage or uprooting.

Interestingly, the transition between these two swaying modes occurred at different wind speeds, depending on the forest density. In the dense plot, the trees switched patterns at wind speeds between 1.79 and 7.44 meters per second. In contrast, in the thinned plot, the transition occurred at slightly lower wind speeds, ranging from 1.57 to 5.63 meters per second.

Using an uprooted tree as a reference, researchers assessed the resistance to damage in the thinned P-50 over a 10-minute period during Typhoon Trami. They found that the actual resistance was only 48% of the expected resistance estimated through controlled tree-pulling experiments.

Prof. Kamimura elaborates, “The 52% difference between actual and expected resistance values was likely due to the roots weakening because of strong winds, even before the winds became more severe. This root fatigue occurred because the trees moved more due to less support from nearby trees and more wind penetrating the plot.” This also explains why the trees in the dense P-100 were not damaged during Typhoon Trami.

This study offers valuable insights for balancing thinning with wind resistance in forest management to support sustainable forestry practices, and help forests withstand extreme climate changes. While thinning promotes tree growth, it can also make forests more vulnerable to storms, especially soon after thinning. Prof. Kamimura concludes, “With more frequent storms in a changing climate, forest management practices must adapt to maintain resilience.”

Researchers at Aalto University’s Department of Applied Physics found a new way to create tiny hurricanes of light — known to scientists as vortices — that can carry information. The method is based on manipulating metallic nanoparticles that interact with an electric field. The design method, belonging to a class of geometries known as quasicrystals, was thought up by Doctoral Researcher Kristian Arjas and experimentally realised by Doctoral Researcher Jani Taskinen, both from Professor Päivi Törmä’s Quantum Dynamics group. The discovery represents a fundamental step forward in physics and carries the potential for entirely new ways of transmitting information.

Half order and chaos

A vortex is in this case like a hurricane that occurs in a beam of light, where a calm and dark centre is surrounded by a ring of bright light. Just like the eye of a hurricane is calm due to the winds around it blowing in different directions, the eye of the vortex is dark due to the electric field of bright light pointing to different directions on different sides of the beam.

Previous physics research has connected what kind of vortices can appear with how much symmetry there is in the structure that produces them. For example, if particles in the nanoscale are arranged in squares the produced light has a single vortex; hexagons produce a double vortex and so on. More complex vortices require at least octagonal shapes.

Now Arjas, Taskinen and the team unlocked a method for creating geometric shapes that theoretically support any kind of vortex.

“This research is on the relationship between the symmetry and the rotationality of the vortex, i.e. what kinds of vortices can we generate with what kinds of symmetries. Our quasicrystal design is halfway between order and chaos,” Törmä says.

Good vibrations

In their study, the group manipulated 100,000 metallic nanoparticles, each roughly the size of a hundredth of a single strand of human hair, to create their unique design. The key lay in finding where the particles interacted with the desired electric field the least instead of the most.

‘An electrical field has hotspots of high vibration and spots where it is essentially dead. We introduced particles into the dead spots, which shut down everything else and allowed us to select the field with the most interesting properties for applications,’ Taskinen says.

The discovery opens a wealth of future research in the very active field of topological study of light. It also represents the early steps for a powerful way of transmitting information in domains where light is needed to send encoded information, including telecommunications.

‘We could, for example, send these vortices down optic fibre cables and unpack them at the destination. This would allow us to store our information into a much smaller space and transmit much more information at once. An optimistic guess for how much would be 8 to 16 times the information we can now deliver over optic fibre,’ Arjas says.

Practical applications and scalability of the team’s design are likely to take years of engineering. The Quantum Dynamics group at Aalto, however, have their hands full with research into superconductivity and improving organic LEDs.

The group used the OtaNano research infrastructure for nano-, micro- and quantum technologies in their pioneering study.

The research was published early November in Nature Communications.

Described in the open-access journal Zoosystematics and Evolution, Idiopyrgus eowynae and Idiopyrgus meriadoci were named in honour of Éowyn and Meriadoc Brandybuck from J.R.R. Tolkien’s iconic series.

In their research paper, the authors explain the name Idiopyrgus eowynae, stating, “Éowyn exemplifies courage, resilience, and resistance against darkness, both internal and external, standing against Gríma Wormtongue and the Witch-king of Angmar.”

Regarding Idiopyrgus meriadoci, they write, “Besides standing with Éowyn against the Witch-king in the Battle of the Pelennor Fields, Merry is also an example of the fight for nature conservation in Middle-earth, pushing the Ents into action and ultimately ending Saruman’s threat to Fangorn Forest.”

The discovered species are troglobitic and were found in a single limestone cave in the Serra do Ramalho karst area of Bahia state, northeastern Brazil. The gastropods belong to the family Tomichiidae, a group previously known for inhabiting surface freshwater environments but now shown to have adapted to subterranean ecosystems.

Both snails have unique periostracal hairs — thorn-like structures — on their shells, a feature uncommon among Brazilian freshwater snails. Their cave-specific adaptations include reduced pigmentation, fragile shells, and small size.

The Gruna do Pedro Cassiano cave, where the snails were discovered, is a fragile ecosystem threatened by water extraction, deforestation, and climate change. Due to the species’ limited habitat and environmental threats to their subterranean ecosystem, the authors recommend their classification as vulnerable. The findings highlight the importance of protecting Brazil’s subterranean biodiversity and raise concerns about the impact of human activities on these delicate ecosystems.

On his choice of Tolkien-inspired names for the new species, lead author Dr Rodrigo B. Salvador of the Finnish Museum of Natural History said, “I tend to use lots of pop culture references in my species names — from books, comics, Dungeons & Dragons, and video games. If we think about it, there is a long-standing tradition in taxonomy of using names from mythology and literature to name species.

“Granted, in the old days, those names mostly came from Greek and Roman myths and Shakespeare. Today, we have newer mythologies and literature classics, so in a way, we’re just continuing that tradition.”

The university announced on the 7th of November that the research team of Distinguished Professor Sang Yup Lee of the Department of Chemical and Biomolecular Engineering has succeeded in developing a microbial strain that efficiently produces pseudoaromatic polyester monomer to replace polyethylene terephthalate (PET) using systems metabolic engineering.

Pseudoaromatic dicarboxylic acids have better physical properties and higher biodegradability than aromatic polyester (PET) when synthesized as polymers, and are attracting attention as an eco-friendly monomer* that can be synthesized into polymers. The production of pseudoaromatic dicarboxylic acids through chemical methods has the problems of low yield and selectivity, complex reaction conditions, and the generation of hazardous waste.

To solve this problem, Professor Sang Yup Lee’s research team used metabolic engineering to develop a microbial strain that efficiently produces five types of pseudoaromatic dicarboxylic acids, including 2-pyrone-4,6-dicarboxylic acid and four types of pyridine dicarboxylic acids (2,3-, 2,4-, 2,5-, 2,6-pyridine dicarboxylic acids), in Corynebacterium, a bacterium mainly used for amino acid production.

The research team used metabolic engineering techniques to build a platform microbial strain that enhances the metabolic flow of protocatechuic acid, which is used as a precursor for several pseudoaromatic dicarboxylic acids, and prevents the loss of precursors.

Based on this, the genetic manipulation target was discovered through transcriptome analysis, producing 76.17 g/L of 2-pyrone-4,6-dicarboxylic acid, and by newly discovering and constructing three types of pyridine dicarboxylic acid production metabolic pathways, successfully producing 2.79 g/L of 2,3-pyridine dicarboxylic acid, 0.49 g/L of 2,4-pyridine dicarboxylic acid, and 1.42 g/L of 2,5-pyridine dicarboxylic acid.

In addition, the research team confirmed the production of 15.01 g/L through the construction and reinforcement of the 2,6-pyridine dicarboxylic acid biosynthesis pathway, successfully producing a total of five similar aromatic dicarboxylic acids with high efficiency.

In conclusion, the team succeeded in producing 2,4-, 2,5-, and 2,6-pyridine dicarboxylic acids at the world’s highest concentration. In particular, 2,4-, 2,5-pyridine dicarboxylic acid achieved production on the scale of g/L, which was previously produced in extremely small amounts (mg/L).

Based on this study, it is expected that it will be applied to various polyester production industrial processes, and it is also expected that it will be actively utilized in research on the production of similar aromatic polyesters.

Professor Sang Yup Lee, the corresponding author, said, “The significance lies in the fact that we have developed an eco-friendly technology that efficiently produces similar aromatic polyester monomers based on microorganisms,” and “This study will help the microorganism-based bio-monomer industry replace the petrochemical-based chemical industry in the future.”

The results of this study were published in the international academic journal, the Proceedings of the National Academy of Sciences of United States of America (PNAS) on October 30th.

This study was conducted with the support of the Development of Next-generation Biorefinery Platform Technologies for Leading Bio-based Chemicals Industry Project and the Development of Platform Technologies of Microbial Cell Factories for the Next-generation Biorefineries Project (Project leader: Professor Sang Yup Lee) from the National Research Foundation supported by the Ministry of Science and Technology and ICT of Korea.