An agile monopedal hopping quadcopter with synergistic hybrid locomotion.

Nature abounds with examples of superior mobility through the fusion of aerial and ground movement. Drawing inspiration from such multimodal locomotion, we introduce a high-performance hybrid hopping and flying robot. The proposed robot seamlessly integrates a nano quadcopter with a passive telescopic leg, overcoming limitations of previous jumping mechanisms that rely on stance phase leg actuation. Based on the identified dynamics, a thrust-based control method and detachable active aerodynamic surfaces were devised for the robot to perform continuous jumps with and without position feedback. This unique design and actuation strategy enable tuning of jump height and reduced stance phase duration, leading to agile hopping locomotion. The robot recorded an average vertical hopping speed of 2.38 meters per second at a jump height of 1.63 meters. By harnessing multimodal locomotion, the robot is capable of intermittent midflight jumps that result in substantial instantaneous accelerations and rapid changes in flight direction, offering enhanced agility and versatility in complex environments. The passive leg design holds potential for direct integration with conventional rotorcraft, unlocking seamless hybrid hopping and flying locomotion.

A novel method for feature selection based on molecular interactive effect network.

Analyzing the biological data by considering the molecule interactions may induce a more accurate identification of disease-related biomarkers. In this study, a novel feature selection method based on molecule (feature) interactive effect network is proposed, denoted as Distance Correlation Gain-Network (DCG-Net). In DCG-Net, DCG is defined to measure the interactive effects between pairwise features with respect to the process of physiological and pathological changes and infer the molecule interactive effect network. DCG index is suitable for discrete random variables and continuous random variables. Then a greedy searching strategy is developed to search the informational modules of the interactive features with high statistical dependence on disease outcome. To evaluate the performance of DCG-Net, it was compared with eight representative feature selection techniques including t-test, ReliefF, SVM-RFE, mRMR, IG-RFE, INDEED, MN-PCC and Dcor-SFS on ten public datasets. The experiment results showed the superior performance of DCG-Net in classification accuracy rate, sensitivity, and specificity for three different classifiers. Subsequently, DCG-Net was employed to analyze a lung adenocarcinoma metabolomics dataset, and the metabolites selected involved in the important pathway and had a better discrimination ability. The experiments demonstrate that DCG can effectively detect the molecular interactions, and incorporation of the molecule interactions is helpful to identify informational biomarkers reflecting the occurrence and development of complex diseases.

A bioinspired revolving-wing drone with passive attitude stability and efficient hovering flight.

Among small rotorcraft, the use of multiple compact rotors in a mechanically simple design leads to impressive agility and maneuverability but inevitably results in high energetic demand and acutely restricted endurance. Small spinning propellers used in these vehicles contrast with large lifting surfaces of winged seeds, which spontaneously gyrate into stable autorotation upon falling. The pronounced aerodynamic surfaces and delayed stalls are believed key to efficient unpowered flight. Here, the bioinspired principles are adopted to notably reduce the power consumption of small aerial vehicles by means of a samara-inspired robot. We report a dual-wing 35.1-gram aircraft capable of hovering flight via powered gyration. Equipped with two rotors, the underactuated robot with oversized revolving wings, designed to leverage unsteady aerodynamics, was optimized for boosted flight efficiency. Through the analysis of flight dynamics and stability, the vehicle was designed for passive attitude stability, eliminating the need for fast feedback to stay upright. To this end, the drone demonstrates flight with a twofold decrease in power consumption when compared with benchmark multirotor robots. Exhibiting the power loading of 8.0 grams per watt, the vehicle recorded a flight time of 14.9 minutes and up to 24.5 minutes when equipped with a larger battery. Taking advantage of the fast revolving motion to overcome the severe underactuation, we also realized position-controlled flight and illustrated examples of mapping and surveillance applications with a 21.5-gram payload.

Dual-foci fast-scanning photoacoustic microscopy with 3.2-MHz A-line rate.

We report fiber-based dual-foci fast-scanning OR-PAM that can double the scanning rate without compromising the imaging resolution, the field of view, and the detection sensitivity. To achieve fast scanning speed, the OR-PAM system uses a single-axis water-immersible resonant scanning mirror that can confocally scan the optical and acoustic beams at 1018 Hz with a 3-mm range. Pulse energies of 45∼100-nJ are sufficient for acquiring vascular and oxygen-saturation images. The dual-foci method can double the B-scan rate to 2036 Hz. Using two lasers and stimulated Raman scattering, we achieve dual-wavelength excitation on both foci, and the total A-line rate is 3.2-MHz. In in vivo experiments, we inject epinephrine and monitor the hemodynamic and oxygen saturation response in the peripheral vessels at 1.7 Hz over 2.5 × 6.7 mm2. Dual-foci OR-PAM offers a new imaging tool for the study of fast physiological and pathological changes.