Optimal Online Transmission Policy for Energy-Constrained Wireless-Powered Communication Networks

This work considers the design of online transmission policy in a wireless-powered communication system with a given energy budget. The system design objective is to maximize the long-term throughput of the system exploiting the energy storage capability at the wireless-powered node. We formulate the design problem as a constrained Markov decision process (CMDP) problem and obtain the optimal policy of transmit power and time allocation in each fading block via the Lagrangian approach. To investigate the system performance in different scenarios, numerical simulations are conducted with various system parameters. Our simulation results show that the optimal policy significantly outperforms a myopic policy which only maximizes the throughput in the current fading block. Moreover, the optimal allocation of transmit power and time is shown to be insensitive to the change of modulation and coding schemes, which facilitates its practical implementation.Comment: 7 pages, accepted by ICC 2019. An extended version of this paper is accepted by IEEE TW

Simulation-Based Assessment of Multilane Separate Freeways at Toll Station Area: A Case Study from Huludao Toll Station on Shenshan Freeway

To support the rapid growth of demand in passengers and freight, separating trucks and passenger-cars is a potential solution to improve traffic efficiency and safety. The primary purpose of this paper is to comprehensively assess the multilane separate freeway at Huludao Toll Station in Liaoning Province, China. Based on the configuration and segmentation of the freeway near a toll station, a six-step guidance strategy is designed to adapt to the separate organization mode. Five conventional traffic scenarios are designed in the Vissim platform for comparative analysis between different guidance strategies. To investigate the vehicle-to-infrastructure (V2I) environment, a microscopic testbed is established with cooperative car-following and lane-changing models using the MATLAB platform. The numerical simulation results show that the guidance strategy significantly improves efficiency and safety, and also reduces emissions and fuel consumption. Meanwhile, pre-guidance before toll channels outperforms the scenario only applied with guidance measures after toll plaza. Compared to conventional conditions, the assessment of pollutant emissions and fuel consumption also embodies the superiority of the other five scenarios, especially in the sections of toll plaza and channels with the lowest efficiency and safety level. Generally, all indexes indicate that the cooperative V2I technology is the best alternative for multilane separate freeways

Neural control for constrained human-robot interaction with human motion intention estimation and impedance learning

In this paper, an impedance control strategy is proposed for a rigid robot collaborating with human by considering impedance learning and human motion intention estimation. The least square method is used in human impedance identification, and the robot can adjust its impedance parameters according to human impedance model for guaranteeing compliant collaboration. Neural networks (NNs) are employed in human motion intention estimation, so that the robot follows the human actively and human partner costs less control effort. On the other hand, the full-state constraints are considered for operational safety in human-robot interactive processes. Neural control is presented in the control strategy to deal with the dynamic uncertainties and improve the system robustness. Simulation results are carried out to show the effectiveness of the proposed control design

The Effect of Nonlinear Charging Function and Line Change Constraints on Electric Bus Scheduling

The recharging plans are a key component of the electric bus schedule. Since the real-world charging function of electric vehicles follows a nonlinear relationship with the charging duration, it is challenging to accurately estimate the charging time. To provide a feasible bus schedule given the nonlinear charging function, this paper proposes a mixed integer programming model with a piecewise linear charging approximation and multi-depot and multi-vehicle type scheduling. The objective of the model is to minimise the total cost of the schedule, which includes the vehicle purchasing cost and operation cost. From a practical point of view, the number of line changes of each bus is also taken as one of the constraints in the optimisation. An improved heuristic algorithm is then proposed to find high-quality solutions of the problem with an efficient computation. Finally, a real-world dataset is used for the case study. The results of using different charging functions indicate a large deviation between the linear charging function and the piecewise linear approximation, which can effectively avoid the infeasible bus schedules. Moreover, the experiments show that the proposed line change constraints can be an effective control method for transit operators

Multimodal multiphoton imaging for label-free monitoring of early gastric cancer

Background Early gastric cancer is associated with a much better prognosis than advanced disease, and strategies to improve prognosis is strictly dependent on earlier detection and accurate diagnosis. Therefore, a label-free, non-invasive imaging technique that allows the precise identification of morphologic changes in early gastric cancer would be of considerable clinical interest. Methods In this study, multiphoton microscopy (MPM) using two-photon excited fluorescence combined with second-harmonic generation was used for the identification of early gastric cancer. Results This microscope was able to directly reveal improved cellular detail and stromal changes during the development of early gastric cancer. Furthermore, two features were quantified from MPM images to assess the cell change in size and stromal collagen change as gastric lesion developed from normal to early cancer. Conclusions These results clearly show that multiphoton microscopy can be used to examine early gastric cancer at the cellular level without the need for exogenous contrast agents. This study would be helpful for early diagnosis and treatment of gastric cancer, and may provide the groundwork for further exploration into the application of multiphoton microscopy in clinical practice.Ope

Exploring the mechanisms under Zuogui Pill’s treatment of ischemic stroke through network pharmacology and in vitro experimental verification

Due to its high mortality, incidence and disability rates, ischemic stroke poses heavy economic burdens to families and society. Zuogui Pill (ZGP) is a classic Chinese medicine for tonifying the kidney, which is effective for the recovery of neurological function after ischemic stroke. However, Zuogui Pill has not been evaluated for its potential effects on ischemic strokes. Using network pharmacology, the research aimed to explore the mechanisms of Zuogui Pill on ischemic stroke, which were further validated in SH-SY5Y cells injured by oxygen and glucose deprivation/reperfusion (OGD/R). Network analysis of Zuogui Pill identified 86 active ingredients and 107 compound-related targets correlated with ischemic stroke. Additionally, 11 core active compounds were obtained, such as Quercetin, beta sitosterol, and stigmasterol. Most of the compounds have been proven to have pharmacological activities. Based on pathway enrichment studies, Zuogui Pill may exert neuroprotection through MAPK signaling, PI3K-Akt signaling and apoptosis, as well as enhance neurite outgrowth and axonal regeneration effect via mTOR signaling, p53 signaling and Wnt signaling pathways. In vitro experiment, the viability of ischemic neuron treated with Zuogui Pill was increased, and the ability of neurite outgrowth was significantly improved. Western blot assays shown that the pro-neurite outgrowth effect of Zuogui Pill on ischemic stroke may be relate to PTEN/mTOR signal pathway. The results of the study provided new insights into Zuogui Pill’s molecular mechanism in treatment of ischemic stroke, as well as clinical references for its use