The team has developed the Safety-Assured High-Speed Aerial Robot (SUPER), capable of flying at speeds exceeding 20 meters per second and avoiding obstacles as thin as 2.5 millimeters – such as power lines or twigs – using solely on onboard sensors and computing power. With a compact design featuring a wheelbase of just 280 mm and a takeoff weight of 1.5 kg, SUPER demonstrates exceptional agility, navigating dense forests at night and skillfully avoiding thin wires.

Professor Zhang describes this invention as a game-changer in the field of drone technology, “Picture a ‘Robot Bird’ swiftly maneuvering through the forest, effortlessly dodging branches and obstacles at high speeds. This is a significant step forward in autonomous flight technology. Our system allows MAVs to navigate complex environments at high speeds with a level of safety previously unattainable. It’s like giving the drone the reflexes of a bird, enabling it to dodge obstacles in real-time while racing toward its goal.”

The breakthrough lies in the sophisticated integration of hardware and software. SUPER utilizes a lightweight 3D light detection and ranging (LIDAR) sensor capable of detecting obstacles up to 70 meters away with pinpoint accuracy. This is paired with an advanced planning framework that generates two trajectories during flight: one that optimizing speed by venturing into unknown spaces and another prioritizing safety by remaining within known, obstacle-free zones.

By processing LIDAR data directly as point clouds, the system significantly reduces computation time, enabling rapid decision-making even at high velocities. The technology has been tested in various real-life applications, such as the autonomous exploration of ancient sites, and has demonstrated seamless navigation in both indoor and outdoor environments.

“The ability to avoid thin obstacles and navigate tight spaces opens up new possibilities for applications like search and rescue, where every second counts. SUPER’s robustness in various lighting conditions, including nighttime, makes it a reliable tool for round-the-clock operations.” said Mr Yunfan Ren, the lead author of the research paper.

The research team envisions a wide range of applications for this innovative technology, including autonomous delivery, power line inspection, forest monitoring, autonomous exploration, and mapping. In search and rescue missions, MAVs equipped with SUPER technology could swiftly navigate disaster zones – such as collapsed buildings or dense forests – day and night, locating survivors or assessing hazards more efficiently than current drones. Moreover, in disaster relief scenarios, they could deliver crucial supplies to remote and inaccessible areas.

Men and those who are overweight may be especially vulnerable to the effects of restrictive eating, the findings suggest.

A ‘healthy’ diet rich in minimally processed foods, fresh fruits and vegetables, whole grains, nuts, seeds, lean proteins and fish, is generally associated with a lower risk of depression, while an ‘unhealthy’ diet, dominated by ultra-processed foods, refined carbs, saturated fats, processed meats and sweets, is generally associated with a heightened risk, explain the researchers.

But people follow many different types of diet for health or medical reasons, including those that restrict calories or particular nutrients, and it’s not clear if these other dietary patterns might be associated with a risk of depressive symptoms, they add.

To explore this further, they drew on 28,525 adult respondents (14,329 women and 14,196 men) to the nationally representative US National Health and Nutrition Examination Survey (NHANES) for the years 2007-18, who had completed the Patient Health Questionnaire-9 (PHQ-9) for depressive symptom severity.

In all, 2508 people (just under 8%) reported depressive symptoms, and 7995 participants (29%) had a healthy weight; 9470 (33%) were overweight; and 11060 (38%) were obese.

Participants were asked if they were following any particular diet either to lose weight or for other health reasons, and if so, which of the 9 diet options set out in all 6 cycles of NHANES they were on.

Dietary patterns were categorised into 4 groups: (1) calorie-restrictive; (2) nutrient-restrictive (low in fat/cholesterol, sugar, salt, fibre, or carbs); (3) established dietary patterns (adapted for diabetes, for example); and (4) not on a diet.

Most participants (25,009, 87%) said they weren’t on any specific diet, while 2026 (8%) followed a calorie-restrictive diet, 859 (3%) a nutrient-restrictive diet, and 631 (2%) an established dietary pattern.

When stratified by sex, a greater proportion of men (12,772; 90%) than women (12,237; 85%) said they weren’t on a diet. Calorie restriction was most commonly reported by obese participants (1247;12%) and those who were overweight (594; 8%), while nutrient-restrictive and established dietary patterns were less commonly reported, with the highest proportion of established dietary pattern users among obese participants (359; 3%).

PHQ-9 scores were 0.29 points higher in those on calorie-restrictive diets than in those not on any specific diet.

The scores were higher among those who were overweight and following a calorie-restrictive diet: their PHQ-9 scores were 0.46 points higher, while a nutrient-restrictive diet was associated with a 0.61 point increase in PHQ-9 scores.

Calorie-restrictive diets were also associated with higher cognitive-affective symptom scores (measure of relationship between thoughts and feelings) while nutrient-restrictive diets were associated with higher somatic symptom scores (excessive distress and anxiety about physical symptoms).

These scores also varied by sex: a nutrient-restrictive diet was associated with higher cognitive-affective symptom scores in men than in women not on a diet, while all 3 types of diet were associated with higher somatic symptom scores in men.

And people living with obesity following an established dietary pattern had higher cognitive-affective and somatic symptom scores than those of a healthy weight not on a diet.

This is an observational study, and as such no firm conclusions can be drawn about causality. Respondents may not have accurately classified their diets either, say the researchers.

The findings also contradict those of previously published studies suggesting that low calorie diets improve depressive symptoms. But the researchers explain: “This discrepancy may arise because prior studies were primarily randomised controlled trials (RCTs) where participants adhered to carefully designed diets ensuring balanced nutrient intake.

“In contrast, real-life calorie-restricted diets and obesity often result in nutritional deficiencies (particularly in protein, essential vitamins/minerals) and induce physiological stress, which can exacerbate depressive symptomatology including cognitive-affective symptoms.” Another possible explanation might be a failure to lose weight or weight cycling — losing weight and then putting it back on, they suggest.

By way of an explanation for the observed gender discrepancies, the researchers point out that glucose and the fatty acid omega-3 are critical for brain health. “Diets low in carbohydrates (glucose) or fats (omega-3s) may theoretically worsen brain function and exacerbate cognitive-affective symptoms, especially in men with greater nutritional needs,” they suggest.

Professor Sumantra Ray, Chief Scientist and Executive Director of the NNEdPro Global Institute for Food, Nutrition and Health, which co-owns BMJ Nutrition Prevention & Health with BMJ Group, comments: “This study adds to the emerging evidence linking dietary patterns and mental health, raising important questions about whether restrictive diets which are low in nutrients considered beneficial for cognitive health, such as omega-3 fatty acids and vitamin B12, may precipitate depressive symptoms.

“But the effect sizes are small, with further statistical limitations limiting the generalisability of the findings. Further well designed studies that accurately capture dietary intake and minimise the impact of chance and confounding are needed to continue this important line of inquiry.”

“Our goal was to construct this deep field of space on a physical scale that far exceeded anything that had been done before,” said UC Santa Barbara physics professor Caitlin Casey, who co-leads the COSMOS-Web collaboration alongside Jeyhan Kartaltepe of the Rochester Institute of Technology. “If you had a printout of the Hubble Ultra Deep Field on a standard piece of paper,” she said, referring to the iconic view of nearly 10,000 galaxies released by NASA in 2004, “our image would be slightly larger than a 13-foot by 13-foot-wide mural, at the same depth. So it’s really strikingly large.”

The COSMOS-Web composite image reaches back about 13.5 billion years; according to NASA, the universe is about 13.8 billion years old, give or take one hundred million years. That covers about 98% of all cosmic time. The objective for the researchers was not just to see some of the most interesting galaxies at the beginning of time but also to see the wider view of cosmic environments that existed during the early universe, during the formation of the first stars, galaxies and black holes.

“The cosmos is organized in dense regions and voids,” Casey explained. “And we wanted to go beyond finding the most distant galaxies; we wanted to get that broader context of where they lived.”

A ‘big surprise’

And what a cosmic neighborhood it turned out to be. Before JWST turned on, Casey said, she and fellow astronomers made their best predictions about how many more galaxies the space telescope would be able to see, given its 6.5 meter (21 foot) diameter light-collecting primary mirror, about six times larger than Hubble’s 2.4 meter (7 foot, 10 in) diameter mirror. The best measurements from Hubble suggested that galaxies within the first 500 million years would be incredibly rare, she said.

“It makes sense — the Big Bang happens and things take time to gravitationally collapse and form, and for stars to turn on. There’s a timescale associated with that,” Casey explained. “And the big surprise is that with JWST, we see roughly 10 times more galaxies than expected at these incredible distances. We’re also seeing supermassive black holes that are not even visible with Hubble.” And they’re not just seeing more, they’re seeing different types of galaxies and black holes, she added.

‘Lots of unanswered questions’

While the COSMOS-Web images and catalog answer many questions astronomers have had about the early universe, they also spark more questions.

“Since the telescope turned on we’ve been wondering ‘Are these JWST datasets breaking the cosmological model? Because the universe was producing too much light too early; it had only about 400 million years to form something like a billion solar masses of stars. We just do not know how to make that happen,” Casey said. “So, lots of details to unpack, and lots of unanswered questions.”

In releasing the data to the public, the hope is that other astronomers from all over the world will use it to, among other things, further refine our understanding of how the early universe was populated and how everything evolved to the present day. The dataset may also provide clues to other outstanding mysteries of the cosmos, such as dark matter and physics of the early universe that may be different from what we know today.

“A big part of this project is the democratization of science and making tools and data from the best telescopes accessible to the broader community,” Casey said. The data was made public almost immediately after it was gathered, but only in its raw form, useful only to those with the specialized technical knowledge and the supercomputer access to process and interpret it. The COSMOS collaboration has worked tirelessly for the past two years to convert raw data into broadly usable images and catalogs. In creating these products and releasing them, the researchers hope that even undergraduate astronomers could dig into the material and learn something new.

“Because the best science is really done when everyone thinks about the same data set differently,” Casey said. “It’s not just for one group of people to figure out the mysteries.”

For the COSMOS collaboration, the exploration continues. They’ve headed back to the deep field to further map and study it.

“We have more data collection coming up,” she said. “We think we have identified the earliest galaxies in the image, but we need to verify that.” To do so, they’ll be using spectroscopy, which breaks up light from galaxies into a prism, to confirm the distance of these sources (more distant = older). “As a byproduct,” Casey added, “we’ll get to understand the interstellar chemistry in these systems through tracing nitrogen, carbon and oxygen. There’s a lot left to learn and we’re just beginning to scratch the surface.”

The COSMOS-Web image is available to browse interactively; the accompanying scientific papers have been submitted to the Astrophysical Journal and Astronomy & Astrophysics.