Imaging flow cytometry (IFC) is an emerging technology that acquires single-cell images at high-throughput for analysis of a cell population. Rich information that comes from high sensitivity and spatial resolution of a single-cell microscopic image is beneficial for single-cell analysis in various biological applications. In this paper, we present a fast image-processing pipeline (R-MOD: Real-time Moving Object Detector) based on deep learning for high-throughput microscopy-based label-free IFC in a microfluidic chip. The R-MOD pipeline acquires all single-cell images of cells in flow, and identifies the acquired images as a real-time process with minimum hardware that consists of a microscope and a high-speed camera. Experiments show that R-MOD has the fast and reliable accuracy (500 fps and 93.3% mAP), and is expected to be used as a powerful tool for biomedical and clinical applications.

Fixed-target serial femtosecond crystallography (FT-SFX) was an important advance in crystallography by dramatically reducing sample consumption, while maintaining the benefits of SFX for obtaining crystal structures at room temperature without radiation damage. Despite a number of advantages, preparation of a sample holder for the sample delivery in FT-SFX with the use of many crystals in a single mount at ambient temperature is challenging as it can be complicated and costly, and thus, development of an efficient sample holder is essential. In this study, we introduced a nylon mesh-based sample holder enclosed by a polyimide film. This sample holder can be rapidly manufactured using a commercially available nylon mesh with pores of a desired size at a low cost without challenging technology. Furthermore, this simple device is highly efficient in data acquisition. We performed FT-SFX using a nylon mesh-based sample holder and collected over 130,000 images on a single sample holder using a 30 Hz X-ray pulse for 1.2 h. We determined the crystal structures of lysozyme and glucose isomerase using the nylon mesh at 1.65 and 1.75 Å, respectively. The nylon mesh exposed to X-rays produced very low levels of background scattering at 3.75 and 4.30 Å, which are negligible for data analysis. Our method provides a simple and rapid but highly efficient way to deliver samples for FT-SFX.

Microcrystal delivery methods are pivotal in the use of serial femtosecond crystallography (SFX) to resolve the macromolecular structures of proteins. Here, the development of a novel technique and instruments for efficiently delivering microcrystals for SFX are presented. The new method, which relies on a one-dimensional fixed-target system that includes a microcrystal container, consumes an extremely low amount of sample compared with conventional two-dimensional fixed-target techniques at ambient temperature. This novel system can deliver soluble microcrystals without highly viscous carrier media and, moreover, can be used as a microcrystal growth device for SFX. Diffraction data collection utilizing this advanced technique along with a real-time visual servo scan system has been successfully demonstrated for the structure determination of proteinase K microcrystals at 1.85 Å resolution.

In this study, a forward dynamics-based control (FDC) framework is proposed for task space control of a non-redundant robot manipulator. The FDC framework utilizes forward dynamic robot simulation and an impedance controller to solve the inverse kinematics problem. For the practical use of the proposed control framework, the accuracy, robustness, and stability of robot motion are considered. Taking advantage of the stability of the implicit Euler method, a high-gain PD controller enables accurate position tracking in the task space without losing stability even near the kinematic singularities. Also, the robustness of the controller is enhanced by borrowing the structure of the nonlinear robust internal-loop compensator. Lastly, the selective joint damping injection and spring force saturation are applied to the impedance controller so that the robot motion can always stay within the given dynamic constraints. This study suggests a new, effective solution for the kinematic singularity problem of non-redundant robot manipulators.

Ensuring the safety of a teleoperation system is crucial, and optimization-based control approaches are an effective solution to ensure that the robot satisfies the multiple safety constraints. However, the control input reshaping via optimization can make a system nonpassive. Therefore, this study proposes a new optimization method for ensuring both the safety and passivity of a teleoperation system by integrating it with the task scaling method. Additionally, the energy tank method is implemented to modulate the tradeoff between dissipativity and control performance. The experiments demonstrated that the proposed method ensures the safety and passivity of the teleoperated system for all robot configurations and any operator’s command inputs.