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Transmission matrix (TM) linearly maps the incident and transmitted complex fields, and has been used widely due to its ability to characterize scattering media. It is computationally demanding to reconstruct the TM from intensity images measured by a reference-less experimental setup. Removing reference beam for interference gains the advantage of simple experimental setup. However, the long computational time still limits its practical application. We propose an efficient reference-less TM retrieval method for multimode fiber (MMF). Our method adopts a data acquisition scheme which employs Fourier transform matrix in the design of the incident fields. We develop a nonlinear optimization algorithm to solve the TM retrieval problem in a parallel manner. The data acquisition scheme allows the algorithm to be implemented with fast Fourier transform (FFT), and hence achieves great efficiency improvement. Further, our method acquires intensity images at a defocus plane and correct the error of relative phase offset of TM recovered from the intensity images measured at one fixed plane. We validate the proposed TM retrieval method with both simulations and experiments. By using FFT, our TM retrieval algorithm achieves 1200x speed-up in computational time, and recovers $2286 \times 8192$ TM of a 0.22 NA and $50 \ \mu m$ diameter MMF with 124.9 seconds by a computer of 32 CPU cores. With the advantages of efficiency and the correction of phase offset, our method paves the way for the application of reference-less TM retrieval in real practice.

Super-resolution microscopy normally requiring complex and cumbersome optics is not applicable for in situ imaging through a narrow channel. Here, we demonstrate single hair-thin multimode fiber (MMF) endoscope (less than 250 ${\mu}m$) for in vivo light-field nano-imaging, which is called spatial-frequency tracking adaptive beacon light-field encoded nano-endoscopy (STABLE nano-endoscopy) that enables three-dimensional (3D) subcellular-scale imaging. Spatial-frequency tracking provides up to $10^3$ Hz disorder tracking that ensures stable imaging in long-haul MMFs (up to 200 m) under various conditions. Full-vector modulation and fluorescence emission difference are combined to enhance the imaging signal-to-noise ratio two times and to improve the resolution to sub-diffraction-limited 250 nm (${\lambda}/3NA$). STABLE nano-endoscopy and white-light endoscopy (WLE) are integrated to achieve cross-scale in vivo imaging inside the lumen. This high-resolution and robust observation in a minimally invasive manner paves the way to gain a deeper understanding of the disease mechanisms and to bridge clinical and biological sciences., Comment: 14 pages, 5 figures

Reinforcement learning based recommender systems (RL-based RS) aim at learning a good policy from a batch of collected data, by casting recommendations to multi-step decision-making tasks. However, current RL-based RS research commonly has a large reality gap. In this paper, we introduce the first open-source real-world dataset, RL4RS, hoping to replace the artificial datasets and semi-simulated RS datasets previous studies used due to the resource limitation of the RL-based RS domain. Unlike academic RL research, RL-based RS suffers from the difficulties of being well-validated before deployment. We attempt to propose a new systematic evaluation framework, including evaluation of environment simulation, evaluation on environments, counterfactual policy evaluation, and evaluation on environments built from test set. In summary, the RL4RS (Reinforcement Learning for Recommender Systems), a new resource with special concerns on the reality gaps, contains two real-world datasets, data understanding tools, tuned simulation environments, related advanced RL baselines, batch RL baselines, and counterfactual policy evaluation algorithms. The RL4RS suite can be found at https://github.com/fuxiAIlab/RL4RS. In addition to the RL-based recommender systems, we expect the resource to contribute to research in applied reinforcement learning., Comment: 4-th version, SIGIR2023

An in-situ synthesized WC/TaC reinforced nickel-based composite coatings have been fabricated on AISI 1045 mild carbon steel substrate by laser cladding of powder mixture of Ni60/WC with Ta2O5 and graphite. The microstructure and hardness distribution of WC/TaC/Ni60 composite coating were investigated by scanning electron microscopy (SEM) and X-ray diffraction (XRD) techniques. Results show that the microstructure of the coating has a metallurgical bonding with substrate and is mainly composed of γ-Ni dendrites, W2C, M7C3 carbides, and dispersed TaC particles. The hardness HV of WC/TaC/Ni60 composite coating has been enhanced to a value similar to 9650 MPa, which is 1.3 times higher than that of Ni60 coating. Measurement results demonstrate that these improvements are attributed to the presence of in-situ synthesized TaC particles, microstructure change and phase variations.

Temperature is a very important factor in laser moxibustion. This paper foucus on temperature field in simulated living-porcine liver tissue radiated by laser. Firstly, we place simulated blood vessels in isolated porcine liver to simulate living liver and obtain simulation temperature field by the finite element analysis; then we use K type thermocouples and thermocouple amplifier respectively measured the temperature field of isolated porcine liver and simulated living liver. The experiment results of the two are basically consistent, in the same position of organization, blood perfusion rate will be significantly lower the temperature. These researches provide the basis for the establishment of laser moxibustion in TCM.