Analysis of the population displacement phenomenon under tourism economy development in Chinese historical areas:Based on Social Exchange Theory

In recent years, tourism’s commercial exploitation of China’s historical areas has been in full swing. However, the status quo of those historical sites is increasingly worrying due to their over-commercialization, the dissimilation of original lifestyles and, especially, the phenomenon of population displacement, with historical residents moving out and the non-native population flooding in, which directly gives rise to the loss of traditional culture. As per our investigation of Kulangsu, concerning its current population and culture situations, this paper aims to dig out the root cause of the population displacement, grasp the law and features of this phenomenon, analyze the significance and impacts it brings about and put forward optimization proposals for the sustainable development of Kulangsu Island

The Acute Toxicity and Hematological Characterization of the Effects of Tentacle-Only Extract from the Jellyfish Cyanea capillata

To investigate the hematologic changes and the activities of jellyfish venoms other than hemolytic and cardiovascular toxicities, the acute toxicity of tentacle-only extract (TOE) from the jellyfish Cyanea capillata was observed in mice, and hematological indexes were examined in rats. The median lethal dose (LD50) of TOE was 4.25 mg/kg, and the acute toxicity involved both heart- and nervous system-related symptoms. Arterial blood gas indexes, including pH, PCO2, HCO3−, HCO3std, TCO2, BEecf and BE (B), decreased significantly. PO2 showed a slight increase, while SO2c (%) had no change at any time. Na+ and Ca2+ decreased, but K+ increased. Biochemical indexes, including LDH, CK, CK-MB, ALT, AST and sCr, significantly increased. Other biochemical indexes, including BUN and hemodiastase, remained normal. Lactic acid significantly increased, while glucose, Hct% and THbc showed slight temporary increases and then returned to normal. These results on the acute toxicity and hematological changes should improve our understanding of the in vivo pathophysiological effects of TOE from C. capillata and indicate that it may also have neurotoxicity, liver toxicity and muscular toxicity in addition to hemolytic and cardiovascular toxicities, but no kidney or pancreatic toxicity

A distributionally robust optimization model for vehicle platooning under stochastic disturbances

Inspired by connected and autonomous driving technologies, this paper proposes a closed-loop Distributionally Robust Model Predictive Control (DRMPC) method to address the problem of longitudinal platoon control disturbed by V2V communication noise. In particular, a Model Predictive Control (MPC)-based vehicle platoon control model subject to stochastic disturbances is first developed. Vehicle control and state are imposed with probabilistic chance constraints, and a state feedback structure is designed to ensure the stability of the platoon system, which poses a significant challenge to the platoon control system. To solve this computationally intractable DRMPC model, a Ball ambiguity set is constructed using the characteristic information (expectation and variance) of random variables. The original DRMPC model is reformulated into a computationally tractable robust counterpart approximation framework. Furthermore, the recursive feasibility of the proposed DRMPC and the string stability of the platoon vehicles are demonstrated by introducing an initialization strategy for nominal states. Finally, a simulation study in a platooning system consisting of six vehicles is performed to verify the validity of the DRMPC model under stochastic V2V noise disturbances

Efficient robust control of mixed platoon for improving fuel economy and ride comfort

The emergence of connected and automated vehicle technology has improved the operational efficiency of mixed traffic systems. This paper studies a two-tier trajectory optimization problem for mixed platooning to improve fuel efficiency, ride comfort, and operational safety during vehicle operations. The proposed model follows a two-tier control logic to plan the trajectory of platooning vehicles with three objectives, including minimizing fuel consumption, maximizing ride comfort, and enhancing the anti-disturbance performance of the platoon. The first is the planning tier, which aims to design the optimal trajectory for Connected and Automated Vehicles (CAVs) based on the optimal fuel consumption and comfort and obtain the expected acceleration curve of CAV. The second is the control tier, which aims to ensure the safe operation of platooning vehicles in the presence of uncertain disturbances in real time. Specifically, we propose a robust tube MPC control method, which dynamically adjusts the CAV acceleration according to the reference trajectory obtained by the planning tier to resist the effects of uncertain disturbances, and the tracking behaviour of Human-Driven Vehicles (HDVs) is offline solved by the robust optimal velocity model. Finally, we design simulation experiments to verify the effectiveness of the proposed two-tier optimization framework. The experimental results show the effectiveness and advantages of the two-tier framework in terms of fuel economy, ride comfort, and robustness against different noise disturbances

Robust cooperative communication optimization for multi-UAV-aided vehicular networks

Aerial-ground cooperative vehicular networks are envisioned as a novel paradigm in B5G/6G visions. In this letter, the challenge of optimizing the global energy-efficiency (EE) of multi-UAV-aided vehicular networks in the presence of uncertain air-to-ground (A2G) channels is addressed. Specifically, we propose a maximin paradigm to characterize the system, which aims to maximize its global EE meanwhile satisfying Quality-of-Service (QoS)-oriented data rate requirements in the worst-case situation. We theoretically derive a closed-form optimal solution for an embedded minimization subproblem under a parametric channel uncertainty set and thus develop a computationally tractable robust counterpart, which leads to a robust EE optimization design. Simulation results show that the proposed method significantly outperforms conventional EE schemes in terms of achieving higher global system performance and better robustness under random uncertain environments

Joint optimization of platoon control and resource scheduling in cooperative vehicle-infrastructure system

Vehicle platooning technology is essential in achieving group consensus, on-road safety, and fuel-saving. Meanwhile, Vehicle-to-Infrastructure (V2I) communication significantly facilitates the development of connected vehicles. However, the coupled effects of the longitudinal vehicle’s mobility, platoon control and V2I communication may result in a low reliable communication network between the platoon vehicle and the roadside unit, there is a tradeoff between the platoon control and communication reliability. In this paper, we investigate a biobjective joint optimization problem where the first objective is to maximize the success probability of data transmission (communication reliability) and the second objective function is to minimize the traffic oscillation flow. The vehicle’s mobility state of the platoon vehicle affects the channel capacity and transmission performance. In this context, we deeply explore the relationship between control signals and resource scheduling and theoretically deduce a closed-form expression of the optimal communication reliability objective. Through this closed expression, we transform the bi-objective model into a single objective MPC model by using ϵ-constraint method. We design an efficient algorithm for solving the joint optimization model and prove the convergence. To verify the effectiveness of the proposed method, we finally evaluate the spacing error, speed error, and resource scheduling of platooning vehicles through simulation experiments in two experimental scenarios. The results show that the proposed control-communication co-design can improve the platoon control performance while satisfying the high reliability of V2I communications

Robust car-following control of connected and autonomous vehicles: a Stochastic Model Predictive Control approach

Vehicle platooning has attracted growing attention for its potential to enhance traffic capacity and road safety. This paper proposes an innovative distributed Stochastic Model Predictive Control (SMPC) for a vehicle platoon system to enhance the robustness and safety of the vehicles in uncertain traffic environments. In particular, considering the similarity between the acceleration or deceleration behaviour of neighbouring vehicles and the spring-scale properties, we use a two-mass spring system for the first time to construct an uncertain dynamic model of a formation system. In the presence of uncertain perturbations with known distributional attributes (expectation, variance), we propose an objective function in the form of expectation along with probabilistic chance constraints. Subsequently, a state feedback control mechanism is devised accordingly. Under the cumulative probability distribution function of stochastic perturbations, we theoretically derive a computationally tractable equivalent of the SMPC model. Finally, simulation experiments are designed to validate the control performance of the SMPC platoon controllers, along with an analysis of the stability performance under varying probabilities. The experimental findings demonstrate that the model can be efficiently solved in real-time with appropriately chosen prediction horizon lengths, ensuring robust and safe longitudinal vehicle formation control

Tumor exosome-based nanoparticles are efficient drug carriers for chemotherapy

Developing biomimetic nanoparticles without loss of the integrity of proteins remains a major challenge in cancer chemotherapy. Here, we develop a biocompatible tumor-cell-exocytosed exosome-biomimetic porous silicon nanoparticles (PSiNPs) as drug carrier for targeted cancer chemotherapy. Exosome-sheathed doxorubicin-loaded PSiNPs (DOX@E-PSiNPs), generated by exocytosis of the endocytosed DOX-loaded PSiNPs from tumor cells, exhibit enhanced tumor accumulation, extravasation from blood vessels and penetration into deep tumor parenchyma following intravenous administration. In addition, DOX@E-PSiNPs, regardless of their origin, possess significant cellular uptake and cytotoxicity in both bulk cancer cells and cancer stem cells (CSCs). These properties endow DOX@E-PSiNPs with great in vivo enrichment in total tumor cells and side population cells with features of CSCs, resulting in anticancer activity and CSCs reduction in subcutaneous, orthotopic and metastatic tumor models. These results provide a proof-of-concept for the use of exosome-biomimetic nanoparticles exocytosed from tumor cells as a promising drug carrier for efficient cancer chemotherapy.Peer reviewe