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To achieve high-precision measurements of target points on long straight tracks, a multi-level measurement method based on length–angle mixed intersection techniques was explored. Firstly, a control network with graded measurement levels was proposed, based on the spatial error characteristics of different measuring devices and the principle of nonlinear least squares, and a method for adjustment calculation based on length–angle mixed intersection was studied. Secondly, numerical simulation was conducted to assess the impact of instrument placement on measurement accuracy, and the results indicated that central positioning within the measurement range can effectively minimize the overall point location errors. Finally, the methodology was validated in a practical setting at a rocket sled test site. Experimental results demonstrated that, within a measurement range of approximately 669 m, when target points were located on one side of the track and distance measurements were used as benchmark values, the measurement control network achieved a distance standard deviation of 0.20 mm. The range of distance deviations was between −0.85 mm and 0.98 mm. This approach offers substantial reference value for high-precision coordinate measurements over extended distances.

Abstract Cutting-edge mid-wavelength infrared (MWIR) sensing technologies leverage infrared photodetectors, memory units, and computing units to enhance machine vision. Real-time processing and decision-making challenges emerge with the increasing number of intelligent pixels. However, current operations are limited to in-sensor computing capabilities for near-infrared technology, and high-performance MWIR detectors for multi-state switching functions are lacking. Here, we demonstrate a non-volatile MoS2/black phosphorus (BP) heterojunction MWIR photovoltaic detector featuring a semi-floating gate structure design, integrating near- to mid-infrared photodetection, memory and computing (PMC) functionalities. The PMC device exhibits the property of being able to store a stable responsivity, which varies linearly with the stored conductance state. Significantly, device weights (stable responsivity) can be programmed with power consumption as low as 1.8 fJ, and the blackbody peak responsivity can reach 1.68 A/W for the MWIR band. In the simulation of Faster Region with convolution neural network (CNN) based on the FLIR dataset, the PMC hardware responsivity weights can reach 89% mean Average Precision index of the feature extraction network software weights. This MWIR photovoltaic detector, with its versatile functionalities, holds significant promise for applications in advanced infrared object detection and recognition systems.

Abstract In-sensor processing has the potential to reduce the energy consumption and hardware complexity of motion detection and recognition. However, the state-of-the-art all-in-one array integration technologies with simultaneous broadband spectrum image capture (sensory), image memory (storage) and image processing (computation) functions are still insufficient. Here, macroscale (2 × 2 mm2) integration of a rippled-assisted optoelectronic array (18 × 18 pixels) for all-day motion detection and recognition. The rippled-assisted optoelectronic array exhibits remarkable uniformity in the memory window, optically stimulated non-volatile positive and negative photoconductance. Importantly, the array achieves an extensive optical storage dynamic range exceeding 106, and exceptionally high room-temperature mobility up to 406.7 cm2 V−1 s−1, four times higher than the International Roadmap for Device and Systems 2028 target. Additionally, the spectral range of each rippled-assisted optoelectronic processor covers visible to near-infrared (405 nm–940 nm), achieving function of motion detection and recognition.

Abstract Inflammation, caused by accumulation of inflammatory cytokines from immunocytes, is prevalent in a variety of diseases. Electro-stimulation emerges as a promising candidate for inflammatory inhibition. Although electroacupuncture is free from surgical injury, it faces the challenges of imprecise pathways/current spikes, and insufficiently defined mechanisms, while non-optimal pathway or spike would require high current amplitude, which makes electro-stimulation usually accompanied by damage and complications. Here, we propose a neuromorphic electro-stimulation based on atomically thin semiconductor floating-gate memory interdigital circuit. Direct stimulation is achieved by wrapping sympathetic chain with flexible electrodes and floating-gate memory are programmable to fire bionic spikes, thus minimizing nerve damage. A substantial decrease (73.5%) in inflammatory cytokine IL-6 occurred, which also enabled better efficacy than commercial stimulator at record-low currents with damage-free to sympathetic neurons. Additionally, using transgenic mice, the anti-inflammation effect is determined by β2 adrenergic signaling from myeloid cell lineage (monocytes/macrophages and granulocytes).