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The Thirty Meter Telescope (TMT) project will design and build a 30-m-diameter telescope for research in astronomy in visible and infrared wavelengths. The primary mirror of TMT is made up of 492 hexagonal mirror segments under active control. The highly segmented primary mirror will utilize edge sensors to align and stabilize the relative piston, tip, and tilt degrees of segments. The support system assembly (SSA) of the segmented mirror utilizes a guide flexure to decouple the axial support and lateral support, while its deformation will cause measurement error of the edge sensor. We have analyzed the theoretical relationship between the segment movement and the measurement value of the edge sensor. Further, we have proposed an error correction method with a matrix. The correction process and the simulation results of the edge sensor will be described in this paper.
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http://dx.doi.org/10.1364/AO.57.003401 | DOI Listing |
Light Sci Appl
September 2025
State Key Laboratory of Flexible Electronics, Institute of Advanced Materials (IAM), Nanjing University of Posts & Telecommunications (NUPT), Nanjing, 210023, China.
As the demand for edge platforms in artificial intelligence increases, including mobile devices and security applications, the surge in data influx into edge devices often triggers interference and suboptimal decision-making. There is a pressing need for solutions emphasizing low power consumption and cost-effectiveness. In-sensor computing systems employing memristors face challenges in optimizing energy efficiency and streamlining manufacturing due to the necessity for multiple physical processing components.
View Article and Find Full Text PDFProg Mol Biol Transl Sci
September 2025
Division of Sleep Medicine, Louis Stokes Cleveland VA Medical Center, Cleveland, OH, United States; Division of Pulmonary, Critical Care, and Sleep Medicine, University Hospitals Cleveland Medical Center, Cleveland, OH, United States; Department of Medicine, Case Western Reserve University, Clevelan
Obstructive sleep apnea (OSA) is a pervasive disorder characterized by recurrent airway obstructions during sleep. OSA carries serious health risks, such as cardiovascular and cognitive impairments, and imposes a significant economic burden. This chapter provides a comprehensive overview of various biosensors currently employed for OSA detection, including in-lab polysomnography and flow-based home sleep apnea testing.
View Article and Find Full Text PDFACS Chem Neurosci
September 2025
Chemical and Biomolecular Engineering Dept, University of California, Los Angeles, Los Angeles, California 90095, United States.
Simulations in three dimensions and time provide guidance on implantable, electroenzymatic glutamate sensor design; relative placement in planar sensor arrays; feasibility of sensing synaptic release events; and interpretation of sensor data. Electroenzymatic sensors based on the immobilization of oxidases on microelectrodes have proven valuable for the monitoring of neurotransmitter signaling in deep brain structures; however, the complex extracellular milieu featuring slow diffusive mass transport makes rational sensor design and data interpretation challenging. Simulations show that miniaturization of the disk-shaped device size below a radius of ∼25 μm improves sensitivity, spatial resolution, and the accuracy of glutamate concentration measurements based on calibration factors determined .
View Article and Find Full Text PDFSmall
September 2025
State Key Laboratory of Flexible Electronics (LoFE) & Institute of Flexible Electronics (IFE), Northwestern Polytechnical University, 127 West Youyi Road, Xi'an, 710072, P. R. China.
Flexible strain sensors are pivotal for the advancement of robotics, wearable healthcare, and human-machine interaction in the post-Moore era. However, conventional materials struggle to simultaneously achieve high sensitivity, a broad strain range, and low power consumption for cutting-edge applications. In this work, the issue is addressed through single crystal 1D tellurium nanoribbons (NRs), which are synthesized on SiO/Si substrate by hydrogen-assisted chemical vapor deposition (CVD) method.
View Article and Find Full Text PDFIEEE Trans Med Imaging
September 2025
Photon-counting computed tomography (PCCT) based on photon-counting detectors (PCDs) represents a cutting-edge CT technology, offering higher spatial resolution, reduced radiation dose, and advanced material decomposition capabilities. Accurately modeling complex and nonlinear PCDs under limited calibration data becomes one of the challenges hindering the widespread accessibility of PCCT. This paper introduces a physics-ASIC architecture-driven deep learning detector model for PCDs.
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