Background: Stroke survivors are accompanied by dysfunctions, greatly declining their activities of daily living and bringing burden to families and societies. Although modern rehabilitation therapy has a systematic program in post-stroke motor rehabilitation, numbers of patients still recover slowly. Eye-acupuncture (EA), as an important type of acupuncture, has been widely applied effectively in rehabilitation of stroke for about 50 years. So we combine EA with modern rehabilitation which has achieved successful results. Therefore, we need to adopt an objective and accurate evaluation method to study the effect of this method. Methods: We aim to design a multi-center, block randomized, parallel control trial to assess the effect of eye-acupuncture combined with rehabilitation training therapy for patients with hemiplegia in the convalescent stage of stroke. 360 patients will be enrolled from 6 centres, with half of them (n = 180) in the control group (routine treatment group) and others (n = 180) in the experimental group (eye-acupuncture combined with routine treatment group). Stratified block randomization will be used in the study and the serial number 001-360 which corresponds to a participant will be assigned to each center randomly. We will use the sequentially sealed envelopes to hide the generating of assignment sequence. The cases of dropouts will be recorded with reasons. And the clinical CRFs will be filled in accurately, completely, and timely for statistical analysis. Results: To verify the clinical effects, we will measure the change of bellows from visit 1 to visit 4. Primary outcomes: activity of daily living (ADL) scales (modified Barthel index); simple Fugl–Meyer motor function score; functional magnetic resonance imaging (fMRI) of the brain in the resting state. Secondary outcomes: traditional Chinese medicine (TCM) syndrome score scale; western aphasia battery (WAB); water swallow test; Montreal cognitive assessment (MoCA); growth-associated protein-43 (GAP-43); microtubule-associated protein-2 (MAP-2). Conclusion: The results of this study will provide present evidence on assessing effectiveness of EA combined with rehabilitation training for patients with hemiplegia in the convalescent stage of stroke. Trial registration: This trial has been registrated in Chinese Clinical Trail Registry with the registration number as ChiCTR1900027835 ( http://www.chictr.org.cn/ ).

Background. Tension-type headache (TTH) is the most common headache disorder. Current treatments for TTH have been reported to be associated with insufficient long-term benefits and unwanted adverse events (AEs). The Chinese herbal formula Xuefu Zhuyu (XFZY) has been utilized in TTH treatment, but the evidence supporting its efficacy remains unclear. This study will evaluate the efficacy and safety of XFZY for TTH. Methods. This multicenter, double-blind, randomized, placebo-controlled trial will be undertaken in China. A total of 174 eligible participants will be randomly assigned to either an XFZY group or a placebo group (20 ml each dose, three times daily for 4 weeks) at a ratio of 1 : 1. The primary outcome is the change in mean headache intensity measured by a 10 cm visual analogue scale (VAS). Secondary outcomes include the area-under-the headache curve (AUC), headache frequency, rescue medication use, qi-stagnation and blood-stasis pattern measurement, quality of life measured by the EuroQol-5-Dimensions-5-Level (EQ-5D-5L), global evaluation of medication, and health economic indexes. Discussion. The results of the study are expected to provide evidence of high methodological and reporting quality on the efficacy and safety of XFZY for TTH. This trail is registered with ChiCTR1900026716 (registered on 19 October, 2019).

With excess slurry pressures exerted on the tunnel face, slurry particles tend to infiltrate into the soil in front of the tunnel. There will be excess pore pressure ahead of the tunnel in the case of infiltration, leading to an impairment in the supporting effect contributed by the excess slurry pressure. Corresponding to three slurry infiltration scenarios distinguished by the forms of the filter cake, different pressure transfer models are employed to describe the pore pressure distribution. Using the kinematic approach of limit analysis and the numerically simulated seepage field, the study of tunnel face stability under different slurry infiltration cases is extended by employing a 3D discretization-based failure mechanism. In addition, two simple empirical formulas describing the pore pressure distributions above the tunnel and in advance of the tunnel are established and verified. Combined with the dichotomy method and strength reduction method, the safety factors yielding rigorous upper-bound solutions are obtained by optimization. The proposed method is validated by a comparative analysis. The developed framework allows considering the influence of excess pore pressure on the whole failure mechanism and the three-dimensional characteristics of seepage. A parameter analysis is performed to study the effect of the excess slurry pressure, hydraulic conditions, soil strength properties, and pressure drop coefficient. The results show that the steady-state flow model leads to much more conservative results than the full-membrane model. The safety factor increases with the increasing excess slurry pressure and the decreasing pressure drop coefficient. The present work provides an effective framework to quickly assess the face stability of tunnels under excess slurry pressure considering different filter cake scenarios.

Catching high-speed targets in the flight is a complex and typical highly dynamic task. However, existing methods require manual setting of catching height or time, resulting in lacks of adaptability and flexibility and cannot deal with multiple targets. To bridge this gap, we propose a planning-with-decision scheme called Catch Planner. For sequential decision making, a lightweight policy search method based on deep reinforcement learning is proposed. It is jointly trained with the motion planning and decoupled from physics to speed up training. For motion planning, we propose a trajectory optimization method that jointly optimizes the highly coupled catching time and terminal state. The core is the flexible-terminal constraint transcription. It converts the three unique constraints of catching into differentiable metrics, including equality constraints for terminal position and time, and inequality constraints that enable reasonable terminal position offset and attitude relaxation. In addition, sparse parameterization based on MINCO class considers both dynamic feasibility and collision avoidance constraints. As a result, a generally constrained quadrotor planning problem is transformed into an unconstrained optimization that can be solved reliably and efficiently. We also propose an online iterative optimization method for predicting differentiable trajectories of targets. Catch Planner provides a new paradigm for the combination of learning and planning, where all algorithms can be run in real time onboard at 100hz. Extensive experiments are carried out in real-world and simulated scenes to verify the robustness and expansibility when facing a variety of high-speed flying targets.