The learning-type artificial pancreas system achieved good glycemic regulation and provided increased effectiveness over time. It showed a satisfactory performance even when the blood glucose was challenged by exercise or alcohol.

NSAID treatment, when administered before femtosecond laser-assisted cataract surgery, was effective in maintaining intraoperative pupil dilation, preventing miosis, and reducing PGE levels.

In this article, we propose a framework for crowd behavior prediction in complicated scenarios. The fundamental framework is designed using the standard encoder-decoder scheme, which is built upon the long short-term memory module to capture the temporal evolution of crowd behaviors. To model interactions among humans and environments, we embed both the social and the physical attention mechanisms into the long short-term memory. The social attention component can model the interactions among different pedestrians, whereas the physical attention component helps to understand the spatial configurations of the scene. Since pedestrians’ behaviors demonstrate multi-modal properties, we use the generative model to produce multiple acceptable future paths. The proposed framework not only predicts an individual’s trajectory accurately but also forecasts the ongoing group behaviors by leveraging on the coherent filtering approach. Experiments are carried out on the standard crowd benchmarks (namely, the ETH, the UCY, the CUHK crowd, and the CrowdFlow datasets), which demonstrate that the proposed framework is effective in forecasting crowd behaviors in complex scenarios.

Due to environmental and energy policies in recent years, some countries will install many PV generations into power systems in the future. Under this condition, it is worrisome that the disconnection of the PV occurs because of a voltage drop triggered via a system fault, which impacts the stability of the PV(photovoltaic).A technique of FRT (Fault Ride Through) is an expected solution for PVs. However, just the FRT requirements for PVs do not inevitably increase the stability of the power system. Solving the problem of the instability of the inverter control in a grid-connected PV needs reasonable consideration. This paper proposed an automatically independent controlling algorithm of the PV inverter considering dynamic load features and Active LVRT (low voltage ride through) capability to increase the robustness and performance of the grid-connected PV system, and both simulation and experimental results showed that the condition of a range from an IM rate = 20[%] to an IM rate=40[%] could best meet the requirements for the PV Outputting recovery and the average tracking error of the input current reduced by nearly 10%, also the average output current tracking error reduced by about 4%, which shows that the tracking performance has significantly improved.