Robo-pigeons, a novel class of hybrid robotic systems developed using brain–computer interface technology, hold marked promise for search and rescue missions due to their superior load-bearing capacity and sustained flight performance. However, current research remains largely confined to laboratory environments, and precise control of their flight behavior, especially flight altitude regulation, in a large-scale spatial range outdoors continues to pose a challenge. Herein, we focus on overcoming this limitation by using electrical stimulation of the locus coeruleus (LoC) nucleus to regulate outdoor flight altitude. We investigated the effects of varying stimulation parameters, including stimulation frequency (SF), interstimulus interval (ISI), and stimulation cycles (SC), on the flight altitude of robo-pigeons. The findings indicate that SF functions as a pivotal switch controlling the ascending and descending flight modes of the robo-pigeons. Specifically, 60 Hz stimulation effectively induced an average ascending flight of 12.241 m with an 87.72% success rate, while 80 Hz resulted in an average descending flight of 15.655 m with a 90.52% success rate. SF below 40 Hz did not affect flight altitude change, whereas over 100 Hz caused unstable flights. The number of SC was directly correlated with the magnitude of altitude change, enabling quantitative control of flight behavior. Importantly, electrical stimulation of the LoC nucleus had no significant effects on flight direction. This study is the first to establish that targeted variation of electrical stimulation parameters within the LoC nucleus can achieve precise altitude control in robo-pigeons, providing new insights for advancing the control of flight animal–robot systems in real-world applications.

Mechanical metamaterials, by introducing porous structures into the materials, can achieve complex nonlinear responses through the large deformation of structures, which support a new generation of impact energy absorption and vibration damping systems, wearable electronics, and tactile simulation devices. However, arbitrarily customizable stress–strain curves have yet to be achieved by existing mechanical metamaterials, which are inherently multi-degree-of-freedom (multi-DOF) deformable systems, and their deformation sequence is influenced by the minimum energy gradient principle. Multi-DOF metamaterials behave like underactuated systems, where the number of degrees of freedom exceeds the number of actuators. As a result, their deformation is controlled by the material's elastic forces, inertial forces, and boundary constraints. Here, we propose a novel composition of elastic components integrated with one-degree-of-freedom (1-DOF) kinematic bases, forming a fully actuated system in which the number of actuators equals the number of degrees of freedom. The deformation of each elastic component is governed by its designed 1-DOF kinematic path. Consequently, the stress–strain profile can be arbitrarily prescribed, for instance, controlled multistage strain softening curve is achievable, as the principle of minimum energy gradient does not affect the deformation sequence dictated by the 1-DOF kinematic base. Furthermore, a class of shape memory alloys (SMAs) is introduced as active components to enable rapid in situ property change, providing versatility in switching between different target responses. The analytical inverse design method, numerical analysis, parametric study of different target responses, and experimental validation are carried out. Lastly, preliminary demonstrations of designable anisotropic nonlinear responses are presented.

Ultrasound localization microscopy (ULM) is a novel imaging technique that overcomes the diffraction limit to achieve super-resolution imaging at the 10-μm scale. Despite its remarkable progress, challenges persist in enhancing the precision of microbubble tracking and fulfilling the requirements for high frame rates in practical circumstances, especially in moving organs. To address these issues, an enhanced ULM approach (shorten as vc-Kalman) integrating rapid motion compensation was developed to achieve excellent image quality. Unlike traditional methods relying on observed bubble positions, the proposed algorithm combined statistical information derived from historical data with Kalman-filter-predicted positions to enable more accurate bubble localization. Meanwhile, microbubble brightness in adjacent frames was incorporated as multidimensional feature to further improve the matching efficacy. Furthermore, velocity constraint was applied to minimize possible erroneous traces and enhance the contrast-to-noise ratio of ULM images, while ensuring the continuity of vascular reconstruction and the accuracy of the blood flow analysis to generate a reduced normalized root mean square error in velocity estimation, even at a relatively low frame rate of 146 Hz. More important, to effectively suppress the impact of physiological movements in moving organs like kidneys, this algorithm fulfilled subpixel displacement vector identification through parabolic fitting and expedited motion compensation via dynamic programming-based cross-correlation search. The results indicated that this advanced vc-Kalman method substantially boosted both the robustness and accuracy of ULM imaging, thereby opening more opportunities for clinical applications of super-resolution ULM technology.

After years of research and development, flexible sensors are gradually evolving from the traditional “electronic” paradigm to the “ionic” dimension. Smart flexible sensors derived from the concept of ion transport are gradually emerging in the flexible electronics. In particular, ionic hydrogels have increasingly become the focus of research on flexible sensors as a result of their tunable conductivity, flexibility, biocompatibility, and self-healable capabilities. Nevertheless, the majority of existing sensors based on ionic hydrogels still mainly rely on external power sources, which greatly restrict the dexterity and convenience of their applications. Advances in energy harvesting technologies offer substantial potential toward engineering self-powered sensors. This article reviews in detail the self-powered mechanisms of ionic hydrogel self-powered sensors (IHSSs), including piezoelectric, triboelectric, ionic diode, moist-electric, thermoelectric, potentiometric transduction, and hybrid modes. At the same time, structural engineering related to device and material characteristics is discussed. Additionally, the relevant applications of IHSS toward wearable electronics, human–machine interaction, environmental monitoring, and medical diagnostics are further reviewed. Lastly, the challenges and prospective advancement of IHSS are outlined.

Micro-electro-mechanical systems (MEMS) light detection and ranging (LiDAR) systems are widely employed in diverse applications for their precise ranging and high-resolution imaging capabilities. However, conventional Lissajous scanning patterns, despite their design flexibility, are increasingly limited in meeting the growing demands for image quality. In this study, we propose a novel programmable scanning method that enhances angular resolution within defined regions of interest (ROIs). By applying parameter modulation techniques, we establish a direct, analytical link between the scanning trajectory and ROI placement, enabling precise resolution control. The proposed method increases point cloud density by 2 to 6 times across any ROI within a Lissajous scan, achieving localized improvements of up to 650%, independent of frequency constraints. Moreover, it reduces the design complexity of MEMS scanning mirrors by half, while maintaining comparable high-resolution performance. Incorporating a gaze-inspired trajectory modulation strategy and random modulation continuous wave ranging, we develop a MEMS LiDAR prototype that greatly enhances point cloud fidelity and enables accurate 3-dimensional imaging within ROIs—achieving a ranging accuracy of 2.4 cm (3σ). This approach not only improves angular resolution in targeted regions but also extends the practical applicability of MEMS LiDAR to multitarget tracking and recognition scenarios. Furthermore, the study establishes a robust theoretical framework for ROI-based trajectory control, contributing to the advancement of next-generation high-resolution imaging systems.

Psoriasis, a chronic inflammatory skin disorder, remains challenging to treat due to poor skin barrier penetration, limited efficacy, and adverse effects of current therapies. Natural plant-derived extracellular vesicle-like particles (EVPs) have emerged as biocompatible carriers for bioactive molecules. Among various medicinal plants screened, Perilla frutescens leaf-derived EVPs (PLEVPs) exhibited strong anti-inflammatory and antioxidant effects. By incorporating PLEVPs into a hydrogel formulation, we enhanced their stability, retention at psoriatic lesions, and transdermal delivery efficiency. In vivo studies demonstrated that the PLEVPs markedly alleviated psoriasis symptoms in both preventive and therapeutic mouse models, outperforming conventional treatments. This effect was attributed to reduced oxidative stress, modulation of Treg cells, and promotion of keratinocyte apoptosis. Transcriptomic analysis revealed enrichment of the interleukin-17 (IL-17) signaling pathway, a major driver of psoriasis, while small RNA sequencing identified pab-miR396a-5p, an endogenous microRNA (miRNA) within PLEVPs, as a key regulator. Mechanistic studies showed that pab-miR396a-5p targets the 3′-untranslated region of plant heat shock protein 83a, a homolog of mammalian heat shock protein 90, leading to the suppression of nuclear factor-kappa B and Janus kinase/signal transducers and activators of transcription signaling, inhibiting the IL-17 signaling pathway. Validation using lipid nanoparticles encapsulating pab-miR396a-5p mimics confirmed comparable therapeutic effects. This study highlights the potential of plant-derived EVPs as carriers of endogenous miRNAs, enabling interkingdom communication and offering a scalable platform for psoriasis therapy.

Microrobots enhance contact with pollutants through their movement and flow-induced mixing, substantially improving wastewater treatment efficiency beyond traditional diffusion-limited methods. g-C₃N₄ is an affordable and environmentally friendly photocatalyst that has been extensively researched in various fields such as biomedicine and environmental remediation. However, compared to other photocatalytic materials like TiO₂ and ZnO, which are widely used in the fabrication of micro- and nanorobots, research on g-C₃N₄ for these applications is still in its early stages. This work presents microrobots entirely based on g-C₃N₄ microtubes, which can initiate autonomous movement when exposed to ultraviolet and visible light. We observed distinct motion behaviors of the microrobots under light irradiation of different wavelengths. Specifically, under ultraviolet light, the microrobots exhibit negative photogravitaxis, while under visible light, they demonstrate a combination of 3-dimensional motion and 2-dimensional motion. Therefore, the wavelength of the light can be used for programming the motion style of the microrobots and subsequently their application. We show that the microrobots can effectively degrade the antibiotic tetracycline, displaying their potential for antibiotic removal. This exploration of autonomous motion behaviors under different wavelength conditions helps to expand research on g-C₃N₄-based microrobots and their potential for environmental remediation.