This paper introduces a novel compliant mechanism combining lightweight and energy dissipation for aerial physical interaction. Weighting 400~g at take-off, the mechanism is actuated in the forward body direction, enabling precise position control for force interaction and various other aerial manipulation tasks. The robotic arm, structured as a closed-loop kinematic chain, employs two deported servomotors. Each joint is actuated with a single tendon for active motion control in compression of the arm at the end-effector. Its elasto-mechanical design reduces weight and provides flexibility, allowing passive-compliant interactions without impacting the motors' integrity. Notably, the arm's damping can be adjusted based on the proposed inner frictional bulges. Experimental applications showcase the aerial system performance in both free-flight and physical interaction. The presented work may open safer applications for \ac{MAV} in real environments subject to perturbations during interaction.

Famously, the Battle of the Bulge in the winter of 1944/45 was one of the largest and bloodiest armed conflict of the Second World War. Taking place in densely forested Ardennes region between Belgium and Luxembourg, it was the last major German offensive campaign on the Western Front during World War II. Researchers have used drone-mounted LiDAR – which emits pulses of light to create 3D models and maps – to'see through' the thick forest canopy. They found nearly 1,000 features within the landscape, including dugouts, bomb craters and even artillery emplacements where troops positioned their guns. Pictured are LiDAR images from the study.

We present a machine-learning framework to accurately characterize morphologies of Active Galactic Nucleus (AGN) host galaxies within $z<1$. We first use PSFGAN to decouple host galaxy light from the central point source, then we invoke the Galaxy Morphology Network (GaMorNet) to estimate whether the host galaxy is disk-dominated, bulge-dominated, or indeterminate. Using optical images from five bands of the HSC Wide Survey, we build models independently in three redshift bins: low $(0

Two combinatorial mechanical metamaterials designed in such a way that the letters M and L bulge out in the front when being squeezed between two plates (top and bottom). Designing novel metamaterials such as this can be aided by machine learning. Given a 3D piece of origami, can you flatten it without damaging it? Just by looking at the design, the answer is hard to predict, because each and every fold in the design has to be compatible with flattening. This is an example of a combinatorial problem.

Nearly a decade ago scientists got pretty excited over a glow coming out of the center of our galaxy. They believed it to be gamma ray emissions resulting from self-destructing dark matter. Unfortunately, it turns out, the Milky Way's glowing "bulge" wasn't related to suicidal dark matter. It was probably just gas. A team of researchers from the University of Amsterdam and the University of Grenoble Alpes today published work indicating the glow is actually just a profile of the stars the bulge surrounds.

Scientists in the UK and Netherlands have developed the first-ever device that can "walk" along like a caterpillar using a single, constant light source for power. The concept is clever: A polymer material is installed in a frame shorter than itself to create a bulge. By shining a concentrated, violet LED on the front of the bulge, it contracts, exposing the next part of the strip to the light. That creates a continuous, relatively powerful movement that could be used to "transport small items in hard-to-reach places or to keep the surfaces of solar cells clean," the team says. The trick relies on a light-sensitive liquid-crystal material that changes shape very quickly in the presence of light.

The suckers of an octopus have inspired the creation of a new adhesive patch that can stick to wet and dry surfaces. After studying the anatomy of an octopus' tentacle, the scientists made a patch created from flexible sheets of rubber covered in artificial suction cups. The sticky patches could one day be used to create wound dressings that can easily be taken on and off and may even inspire a generation of Spiderman-style robots that can scale walls, according to researchers. After studying the anatomy of an octopus' tentacle, the scientists made a patch created from flexible sheets of rubber covered in tiny holes. To create the adhesive, the scientists concentrated on recreating a dome-shaped bulge found at the bottom of the octopus' suction patch.

This paper presents a knowledge-based approach to the task of learning and identifying galaxies from their images. To this effect, we propose a crowd-sourced pipeline approach that employs two systems - case based and rule based systems. First, the approach extracts morphological features i.e. features describing the structure of the galaxy such as its shape, central characteristics e.g., has a bar or bulge at its center)etc., using computer vision techniques. Then it employs a case based reasoning system and a rule based system to perform the classification task. Our initial results show that this pipeline is effective in learning reasonably accurate models on this complex task.