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1. Optimal Speed-based Cost of Resilience in Electrified High-speed Railway Systems

   Pan, W.; Shittu, E. (January 2022, Proceedings of the IISE Annual Conference & Expo 2022 K. Ellis, W. Ferrell, J. Knapp, eds.)

   Ellis, K.; Ferrell, W.; Knapp, J. (Ed.)

   There is no doubt that there is an increase in the penetration of electrical energy into the operation of high-speed railway systems (HSR). This is even more pronounced with the increasing trends in smart electric multiple units (EMU). The operational speed serves as a metric for punctuality and safety, as well as a critical element to maintain the balance between energy supply and consumption. The speed-based regenerative energy from EMU’s braking mode could be utilized in the restoration of system operation in the aftermath of a failure. This paper optimizes the system resiliency with respect to the operational speed for the purpose of restoration by minimizing the total cost of implementing recovery measures. By simultaneously valuating the dual-impact of any given fault on the speed deterioration level from the railway operation systems (ROS) side and the power supply and demand unbalance level from the railway power systems (RPS) side, this process develops an adaptive two-dimension risk assessment scheme for prioritizing the handling of different operational zones that are cascaded in the system. With the aid of an integrated speed-based resilience cost model, we determine the optimal resilience time, speed modification plan, and energy allocation strategy. The outcome from implementing this routine in a real-world HSR offers a pioneering decision-making strategy and perspective on optimizing the resilience of an integrated system. 

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2. Large-range high-speed dynamic-mode atomic force microscope imaging: adaptive tapping towards minimal force

   https://doi.org/10.1088/1361-6528/acd700  

   Chen, Jiarong; Zou, Qingze (May 2023, Nanotechnology)

   Abstract This paper presents a software-hardware integrated approach to high-speed large-range dynamic mode imaging of atomic force microscope (AFM). High speed AFM imaging is needed to interrogate dynamic processes at nanoscale such as cellular interactions and polymer crystallization process. High-speed dynamic-modes such as tapping-mode AFM imaging is challenging as the probe tapping motion is sensitive to the highly nonlinear probe-sample interaction during the imaging process. The existing hardware-based approach via bandwidth enlargement, however, results in a substantially reduction of imaging area that can be covered. Contrarily, control (algorithm)-based approach, for example, the recently developed adaptive multiloop mode (AMLM) technique, has demonstrated its efficacy in increasing the tapping-mode imaging speed without loss of imaging size. Further improvement, however, has been limited by the hardware bandwidth and online signal processing speed and computation complexity.Thus, in this paper, the AMLM technique is further enhanced to optimize the probe tapping regulation and integrated with a field programmable gate array (FPGA) platform to further increase the imaging speed without loss of imaging quality and range. Experimental implementation of the proposed approach demonstrates that the high-quality imaging can be achieved at a high-speed scanning rate of 100 Hz and higher, and over a large imaging area of over 20 µm. 

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3. DeepInMiniscope: Deep learning–powered physics-informed integrated miniscope

   https://doi.org/10.1126/sciadv.adr6687  

   Tian, Feng; Mattison, Ben; Yang, Weijian (September 2025, Science Advances)

   Mask-based integrated fluorescence microscopy is a compact imaging technique for biomedical research. It can perform snapshot 3D imaging through a thin optical mask with a scalable field of view (FOV). Integrated microscopy uses computational algorithms for object reconstruction, but efficient reconstruction algorithms for large-scale data have been lacking. Here, we developed DeepInMiniscope, a miniaturized integrated microscope featuring a custom-designed optical mask and an efficient physics-informed deep learning model that markedly reduces computational demand. Parts of the 3D object can be individually reconstructed and combined. Our deep learning algorithm can reconstruct object volumes over 4 millimeters by 6 millimeters by 0.6 millimeters. We demonstrated substantial improvement in both reconstruction quality and speed compared to traditional methods for large-scale data. Notably, we imaged neuronal activity with near-cellular resolution in awake mouse cortex, representing a substantial leap over existing integrated microscopes. DeepInMiniscope holds great promise for scalable, large-FOV, high-speed, 3D imaging applications with compact device footprint. 

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4. Design of a micrometer-long superconducting nanowire perfect absorber for efficient high-speed single-photon detection

   https://doi.org/10.1364/PRJ.390945  

   Cheng, Risheng; Wang, Sihao; Zou, Chang-Ling; Tang, Hong X. (July 2020, Photonics Research)

   Despite very efficient superconducting nanowire single-photon detectors (SNSPDs) reported recently, combining their other performance advantages such as high speed and ultralow timing jitter in a single device still remains challenging. In this work, we present a perfect absorber model and the corresponding detector design based on a micrometer-long NbN nanowire integrated with a 2D photonic crystal cavity of ultrasmall mode volume, which promises simultaneous achievement of near-unity absorption, gigahertz counting rates, and broadband optical response with a 3 dB bandwidth of 71 nm. Compared to previous stand-alone meandered and waveguide-integrated SNSPDs, this perfect absorber design addresses the trade space in size, efficiency, speed, and bandwidth for realizing large on-chip single-photon detector arrays. 

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5. The sharp lifespan for a system of multiple speed wave equations: Radial case

   https://doi.org/10.3934/cam.2025026  

   Koonce, Marvin; Metcalfe, Jason (July 2025, Communications in Analysis and Mechanics)

   Ohta examined a system of multiple speed wave equations with small initial data and demonstrated a finite time blowup. We show, in the radial case, that the same system exists almost globally with the same lifespan as a lower bound. To do this, we use integrated local energy estimates, weighted local energy estimates, the Morawetz estimate that results from using the scaling vector field as a multiplier, and mixed-speed ghost weights. 

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