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This article aims to address the realistic path tracking control problem toward high-system performance for commercial autonomous ground vehicles (AGVs) with simultaneously guaranteeing the tracking accuracy, yaw and roll stability under limited vehicle network resources in global position system temporarily unavailable environments. In such conditions, the vehicle full state information and road topography might not be accessible in real time. To this end, this article proposes an effective adaptive event-trigger (AET)-based robust path tracking control strategy with introducing the reliable Takagi-Sugeno (T-S) fuzzy state observer for practical implementation. First, the vehicle yaw and roll coupled dynamics is incorporated into the vehicle-road system model, with modeling the tire cornering stiffness uncertainty by the T-S fuzzy technique and resolving the system disturbances as unknown inputs. Then, the fuzzy observer structure is established with unmeasurable premise variables which are handled by norm-bound method. Next, a well-designed AET control framework is constructed to reduce the real-time network occupation rate and economize the communication bandwidth resources. Besides, the input constraint and rollover prevention are handled using the robust set invariance. After that, the parallel distributed compensation (PDC) controller and observer are co-designed through solving the effective linear matrix inequalities (LMIs). In addition, the close-loop stability and $H\infty $ performance are ensured by means of the delay dependent Lyapunov-Krasovski method. Finally, the validity and superiority of the proposed control strategy have been verified by Carsim-Simulink co-simulations in different dynamic scenarios with high-fidelity full vehicle model.

Chiral pollutants often pose significant differential environmental health risks. In this study, the biotransformation of chiral dinotefuran (DIN) and its enantioselective metabolic toxicity mechanisms have been systemically investigated. Firstly, reversed-phase chromatography-high resolution mass spectrometry was developed to quantify the content of DIN R/S chiral enantiomer with pg level sensitivity, revealing a lower elimination rate constant (Ke) of S-DIN (0.730 h−1) than R-DIN (0.746 h−1). Secondly, the interaction mechanism between DIN metabolism and important endogenous bioactive molecules, such as aldehyde oxidase (AOX) and neurotransmitters, was revealed. The DIN nitro-group was converted into a guanidine group by the reducing site of nearby flavin adenine dinucleotide (FAD) in AOX with the preferred higher affinity of S-configuration. Meanwhile, the endogenous tryptophan (Trp) aldehyde metabolic intermediate, 5-hydroxyindoleacetaldehyde (5-HIAL), provides a persistent electron donor for DIN reduction viathe oxidation-catalyzed site in AOX, resulting in remarkable up-regulation of monoamine neurotransmitters such as serotonin and dopamine. Thirdly, the higher level of neurotransmitters further mediated dysregulation of oxylipin homeostasis viathe serotonergic pathway, where S-DIN exhibited more pronounced liver lipid damage and environmental health risk with the accumulated lipid biomarkers, oxidized triglyceride (OxTG) and oxidized sphingomyelin (OxSM). This study elucidates the AOX-mediated enantioselectivity metabolic pathway of DIN, providing a new analytical method for chiral pollutants and paves the way for their health risk assessments.

Aggressive driving behavior has greatly endangered vehicle safety and posed challenges to the design of advanced driver-assistance systems (ADASs). A novel driver–automation cooperative shared control system is proposed in this article to make steering assistance actions better cooperate with aggressive drivers. Based on investigating shared control modes, a driving activity parameter for drivers is introduced, which aims to modulate the shared control authority and mitigate the conflicts between aggressive drivers and ADAS. A polytope represented by finite vertices is employed to handle uncertain parameters, including driving activity and longitudinal velocity. Then, an H $\infty $ robust output-feedback control method satisfying the regional pole assignment is presented to provide robustness and stability of the polytope space while simplifying the control structure through reducing vertices. The driver-in-the-loop simulator experiments are carried out to verify the proposed controller, in which the driver model parameters are identified. The results demonstrate that the developed assistance controller can effectively ensure path-tracking accuracy and simultaneously improve aggressive drivers’ comfort.

In this paper, we propose and analyze a fully discrete finite element projection method for the magnetohydrodynamic (MHD) equations. A modified Crank–Nicolson method and the Galerkin finite element method are used to discretize the model in time and space, respectively, and appropriate semi-implicit treatments are applied to the fluid convection term and two coupling terms. These semi-implicit approximations result in a linear system with variable coefficients for which the unique solvability can be proved theoretically. In addition, we use a second-order decoupling projection method of the Van Kan type [Van Kan, SIAM J. Sci. Statist. Comput.7(1986) 870–891] in the Stokes solver, which computes the intermediate velocity field based on the gradient of the pressure from the previous time level, and enforces the incompressibility constraint viathe Helmholtz decomposition of the intermediate velocity field. The energy stability of the scheme is theoretically proved, in which the decoupled Stokes solver needs to be analyzed in details. Error estimates are proved in the discrete L∞(0, T; L2) norm for the proposed decoupled finite element projection scheme. Numerical examples are provided to illustrate the theoretical results.

Here, the transcriptomics and metabolomics on a model of exposure to a cocktail of neonicotinoids (Neo) containing seven commercial compounds and a synergist piperonyl butoxide (PBO) were established. The results showed that Neo and PBO disrupted mRNA and metabolite levels in a dose-dependent manner. Neo caused tryptophan pathway-related neurotoxicity, reduced lipolysis, and promoted fat mass accumulation in the liver, while PBO induced an increase in inflammatory factors and damage to intercellular membranes. Co-exposure enhanced Neo-induced liver steatosis, focal necrosis, and oxidative stress by inhibiting oxidative phosphorylation (OXPHOS). Furthermore, diglycerides and metabolic biomarkers demonstrated that the activation of insulin signaling is associated with restricted OXPHOS, which commonly leads to a high risk of non-alcoholic fatty liver disease (NAFLD) and Alzheimer’s disease (AD) as the result of over-synthesis of lipids, low energy supply, and high thermogenesis. The study demonstrates that chronic disease can be induced by Neo and the synergist PBO at the molecular level.

Complex traffic scenarios pose a challenge to the cooperation control of connected and automated vehicles (CAVs). Conventional platoon control or advanced driver-assistance systems only provide an isolated solution due to their inadequacies in systematic perspective. To this end, a multi-agent system (MAS) based distributed control architecture together with a hierarchical controller is proposed for the CAVs cooperation control system. The upper layer considers the potential states of a CAV in the platoon evolution (i.e., vehicle-cruising maneuver and vehicle-following maneuver) and elaborates the transition rules for discrete maneuvering behaviors. The lower layer includes the corresponding motion controller for each CAV. Artificial potential field (APF) combined with the distributed model predictive control algorithm is adopted to realize the integrated longitudinal, lateral and yaw motion control of CAVs. Next, inspired by the Pareto-optimal method for tackling the MAS-cooperation system, an optimal solution strategy is introduced to solve the CAVs cooperation problem from the viewpoint of the control theory. Furthermore, multi-constraints are designed to ensure a safety inter-vehicle spacing between CAVs, while the vehicle stability can also be guaranteed. The simulation results demonstrate that the MAS-based hierarchical control architecture can effectively handle the cooperation control of CAVs in the typical traffic scenarios. The real-time implementation of the proposed controller also proves the feasibility.

This paper presents a robust finite frequency ${H} _{\infty }$ control strategy for improving vibration performance and ride comfort of electric vehicles through in-wheel motor-active suspension system(IWM-ASS). Since the human body is much sensitive to the vertical vibration of 4 -8 Hz, the main objective is dedicated to deal with the vibration challenge that matches the characteristics of the human body by applying the finite-frequency technique. Firstly, the uncertain quarter-vehicle active suspension model with dynamic damping in-wheel motor driven system is established, in which in-wheel motor is suspended as dynamic vibration absorber(DVA) to isolate the force transmitted to motor bearing in IWM-ASS. Based on the framework of generalized Kalman–Yakubovich–Popov lemma and stability theory, then the performance index of ${H} _{\infty }$ norm from external disturbance to controlled output for IWM-ASS is attenuated within the concerned frequency range while other system requirements such as parameter uncertainty, suspension deflection constraint and actuator saturation are also guaranteed in controller design. The resulting robust finite frequency state feedback ${H} _{\infty }$ controller is finally designed utilizing two new theorems, and solved via a set of linear matrix inequalities. Simulations for frequency-domain and time-domain responses are implemented and compared with the entire frequency control method to evaluate the effectiveness of the proposed strategy. It can be concluded from the results that the developed control strategy can effectively attenuate the negative vibration and enhance ride comfort and road-holding ability for electric vehicles of IWM-ASS.

With the rapid development of advanced driver assistance systems, driver-automation cooperative control becomes more challenging due to the uncertainty of driver behaviors. To this end, this paper proposes a shared control approach to assist drivers in path-tracking and collision avoidance. A high-fidelity CarSim vehicle model embedded driver simulator is built to collect the driver data, based on which the normalized steering angle input and the time to collision are defined to quantify the driving performance. Then, these performance indices are employed to develop the fuzzy controller and determine the control authority for the steering assistance system (SAS). A multi-constraints model predictive control is designed to follow the desired path, and simultaneously ensure the vehicle stability. Different from the traditional constraints handling method, the state constraint is transformed into the input constraint considering the nonlinearity. The effectiveness of the proposed method is verified with two less experienced drivers. The test results show that the path-tracking performance and vehicle stability can be guaranteed with less control effort.

Accurate knowledge about the motion state of preceding vehicles (PVs) contributes to the optimization of planning and decision making of autonomous vehicles, which in turn further enhances road safety. Existing studies generally rely on information from special sensors mounted on the ego vehicle to estimate PVs state. With the evolution of information technology, the use of vehicle-to-vehicle (V2V) communication to estimate the PVs state has attracted more and more attention. However, the problem of how to reduce the communication rate while ensuring the estimation accuracy of PVs state with the limited communication bandwidth has not been addressed yet. In addition, traditional studies on lateral state estimation of PVs assume that the longitudinal velocity of the PV is known or design an additional estimator to predict the longitudinal velocity. This results in the dynamical coupling characteristics of the vehicle not being fully considered. To address these problems, an event-triggered estimation framework by fusing an event-triggered mechanism with an embedded cubature Kalman filter based on a coupled vehicle model is proposed for PVs state estimation. Simulation and real vehicle test results demonstrate that the proposed prediction approach can strike an effective balance between the communication rate and the estimation performance. The estimation accuracy of the proposed method is still superior to that of the cubature Kalman filter, even if the communication rate drops to 37.55%.

Realistic uncertainties and disturbances cannot be ignored when striving towards high-performance autonomous driving. Meanwhile, advanced vehicular sensing technology enables more and more self-driving techniques to come out. Against this backdrop, this paper aims to holistically address the system uncertainties and disturbances in the path tracking control of autonomous vehicles (AVs) by the preview control theory to achieve superior control performance. First, unmeasureable multi-uncertainties and the external disturbance are considered simultaneously into the robust gain-scheduling framework with variable longitudinal velocity. Then, by the equivalent delay approach, ineluctable time-varying system delays are effectively handled. Next, the physical constraints of the steering system and direct yaw moment control (DYC) system are considered for practical implementation through robust set invariance theory. The parallel distributed compensation (PDC) technique and auxiliary feedback matrices approach are introduced for reducing design conservatism. After that, by incorporating the road curvature into the augmented system state, the path tracking preview control problem can be solved without online optimization. Thereafter, the closed-loop system stability and guaranteed performance have been proved through the Lyapunov- Krasovski approach. The proposed controller design is finally reformulated as the optimization problem based on linear matrix inequalities (LMIs) via specific convexification techniques. Finally, to verify the validity of the proposed controller, Software in Loop (SIL) tests with Carsim full-vehicle model under different dynamic conditions have been implemented.

This study addresses the problem of distributed robust control resistance to vehicle parametric uncertainty and hybrid attacks in heterogeneous vehicular platoon systems. First, an invaded heterogeneous vehicular platoon system is modeled accompanied by the technique of inverse model compensation to deal with the problem of non-linearities in longitudinal dynamics, a nominal vehicle mass is introduced to tackle the problem of heterogeneity and variability of vehicle masses. Besides, we quantize the effects of false-data injection (FDI) and message-delay (MD) attacks and integrate them into the proposed heterogeneous platoon system. Additionally, to obtain the desired inner-vehicle stability of a heterogeneous platoon, an inner-vehicle ${H}_\infty $ distributed robust stable controller is presented based on Lyapunov-Krasovskii functional. Finally, a ${\mathcal{L}}_2$-based string stability criterion is put forward to weaken the attacks' effects when they propagate along with the platoon. To explain the superiority of the derived theory more directly, simulations with two different control methods about the heterogeneous platoon under hybrid attacks are provided. The results show that, compared to regular platoon control method, the proposed robust controller performs better in achieving the desired inter-vehicle spacing tracking and can maintain string stability of the platoon.

Herein, the effects of the ionic types and content of alkali activator on the chloride-ion permeability of one-part alkali-activated nickel slag concrete were examined. The NT Build 492 method was adopted to measure the Cl−transport performance. In general, the total Cl−concentration in concrete decreases with the increase of penetration depth; however, the enrichment of Cl−concentration in the sample is not obvious. Anions have more effect on 28-d compressive strength, while cations have more effect on chlorine-ion permeability. For the same Na2O content, SiO32−-activator and Na+-activator perform better than other anions and cations, while OH–and K+perform worse than other ions. The chloride-ion permeability coefficient (DRCM) of concrete with Na2SiO3is the lowest and that with KOH is the highest. The DRCMof concrete prepared with KOH is 1.93 times higher than that of concrete prepared with Na2SiO3. When the activator is Na2SiO3, the DRCMof concrete decreases with the increase in Na2O content when the Na2O content is less than 7%. However, when the Na2O content exceeds 7%, the DRCMof concrete increases with the increase in Na2O content.

This paper aims to develop an automatic miscalibration detection and correction framework to maintain accurate calibration of LiDAR and camera for autonomous vehicle after the sensor drift. First, a monitoring algorithm that can continuously detect the miscalibration in each frame is designed, leveraging the rotational motion each individual sensor observes. Then, as sensor drift occurs, the projection constraints between visual feature points and LiDAR 3-D points are used to compute the scaled camera motion, which is further utilized to align the drifted LiDAR scan with the camera image. Finally, the proposed method is sufficiently compared with two representative approaches in the online experiments with varying levels of random drift, then the method is further extended to the offline calibration experiment and is demonstrated by a comparison with two existing benchmark methods.

Four-wheel independently driven electric vehicles (FWID-EV) endow a flexible and scalable control framework to improve vehicle performance. This paper integrates the torque vectoring and active suspension system (ASS) to enhance the vehicle’s longitudinal and vertical motion control performance. While the nonlinear characteristic of the tire model leads to a relatively heavier computational burden. To facilitate the controller design and ease the load, a half-vehicle dynamics system is built and simplified to the linear-time-varying (LTV) model. Then a model predictive controller is developed by formulating the objective function by comprehensively considering the safety, energy-saving and comfort requirements. The in-wheel motor efficiency and the power loss of tire slip are treated as optimization indices in this work to reduce energy consumption. Finally, the effectiveness of the proposed controller is verified through the rapid-control-prototype (RCP) test. The results demonstrate the enhancement of the energy-saving as well as comfort on the basis of vehicle stability.

Background: The impact of positive circumferential resection margin on prognosis in esophageal cancer is under controversy. Previous systematic reviews and meta-analyses had limitations. This updated systematic review and meta-analysis aimed to assess the prognostic impact of positive circumferential resection margin in esophageal cancer.PubMed and Web of Science were searched for studies investigating the association between circumferential resection margin status and prognosis in esophageal cancer. Study population were focused on T3 and/or T4a patients. Study selection was based on availability of survival information (Kaplan–Meier curves and adjusted analysis). Random-effects models were used to summarize hazard ratios for overall survival and disease-free survival.According to College of American Pathologists criteria, circumferential resection margin-positive patients had shorter median overall survival (P< 0.0001) and shorter median disease-free survival (P< 0.0001) compared with circumferential resection margin-negative patients. The pooled hazard ratios for overall survival and disease-free survival were 2.06 (95% confidence interval, 1.68–2.53; P< 0.0001) and 2.00 (95% confidence interval, 1.41–2.84; P< 0.0001), respectively. According to the Royal College of Pathologists criteria, circumferential resection margin-positive patients had shorter median overall survival (P< 0.0001) and shorter median disease-free survival (P< 0.0001) compared with circumferential resection margin-negative patients. The pooled hazard ratios for overall survival and disease-free survival were 1.31 (95% confidence interval, 1.16–1.48; P< 0.0001) and 1.31 (95% confidence interval, 1.09–1.57; P< 0.0001), respectively.ompared with negative circumferential resection margin, positive circumferential resection margin is associated with worse survival outcomes in esophageal cancer.

Most of the previous investigated adaptive cruise control methods focused on maintaining a safe front clearance of the host vehicle. Due to fault or heat fading, the vehicle behind an intelligent vehicle may lose part of braking performance and collide with the intelligent vehicle. Thus the control system of an intelligent vehicle should simultaneously maintain the front and rear clearances on such a critical condition, which is seldom discussed before. In this study, a bidirectional adaptive cruise control algorithm is proposed to reduce such collisions. Simulations have been done to confirm the validity of the proposed algorithm. The simulation results show that the proposed algorithm can reduce the collisions caused by the following vehicle with low braking performance, which cannot be resolved by traditional adaptive cruise control. Thus, compared with the traditional adaptive cruise control, the proposed algorithm can improve the safety of intelligent vehicles in collision avoidance.

Currently, due to the lack of long-term postoperative follow-up outcomes of the congenital divided eyelid nevus, we described our surgical approaches and presented the functional and cosmetic results of 13 patients with an average of 5-year follow-up. Based on the surgical treatments and the follow-ups, the selection of total or subtotal excision depends on the lesion location and the use of blepharoplasty approaches is determined by defect size. The CO2laser may be a useful second-stage procedure to ablate remnant lesions, but long-term monitoring is required.

This paper proposes a robust cooperative control strategy for multiple autonomous vehicles to achieve safe and efficient platoon formation, and it analyzes the effects of vehicle stability boundaries and parameter uncertainties. The cooperative vehicle control framework is composed of the upper planning level and lower tracking control level. In the planning level, the trajectory of each vehicle is generated by using the multi-objective flocking algorithm to form the platoon. The parameters of the flocking algorithm are optimized to prevent the vehicle speed and yaw rate from going beyond their limits. In the lower level, to realize the stable platoon formation, a lumped disturbance observer is designed to gain the stable-state reference, and a distributed robust model predictive controller is proposed to achieve the offset-free trajectory tracking while downsizing the effects of parameter uncertainties. The simulation results show the proposed cooperative control strategy can achieve safe and efficient platoon formation.

In this paper, we propose a two-layer overtaking control framework of the autonomous electric ground vehicle, including trajectory planning and tracking control. In the upper layer, a stable overtaking trajectory is derived by considering the duration of the overtaking, driving comfort and vehicle stability simultaneously. Besides, the safety spacing between the overtaking and overtaken vehicles is analyzed to prevent the potential collision. To track the generated reference trajectory precisely, we design a robust model predictive controller adopting the input-to-state stability property in the lower layer to reduce the affection of disturbances and parameter uncertainties. Two driving strategies with different lateral accelerations, that is, mild and aggressive, are simulated to verify the effectiveness of the proposed control framework. By comparing to the driver-vehicle control system, the proposed control framework can not only achieve safe, smooth, and rapid overtaking but also realize the accurate state tracking in the presence of tire cornering stiffness uncertainty.

Distributed drive electric vehicles (DDEVs) possess great advantages in the viewpoint of fuel consumption, environment protection and traffic mobility. Whereas the effects of inertial parameter variation in DDEV control system become much more pronounced due to the drastic reduction of vehicle weights and body size, and inertial parameter has seldom been tackled and systematically estimated. This paper presents a dual central difference Kalman filter (DCDKF) where two Kalman filters run in parallel to simultaneously estimate vehicle different dynamic states and inertial parameters, such as vehicle sideslip angle, vehicle mass, vehicle yaw moment of inertia, the distance from the front axle to centre of gravity. The proposed estimation method only integrates and utilizes real-time measurements of hub torque information and other in-vehicle sensors from standard DDEVs. The four-wheel nonlinear vehicle dynamics estimation model considering payload variations, Pacejka tire model, wheel and motor dynamics model is developed, the observability of the DCDKF observer is analysed and derived via Lie derivative and differential geometry theory. To address system nonlinearities in vehicle dynamics estimation, the DCDKF and dual extended Kalman filter (DEKF) are also investigated and compared. Simulation with various maneuvers are carried out to verify the effectiveness of the proposed method using Matlab/Simulink-Carsim®. The results show that the proposed DCDKF method can effectively estimate vehicle dynamic states and inertial parameters despite the existence of payload variations and variable driving conditions.This research provides a boot-strapping procedure which can performs optimal estimation to estimate simultaneously vehicle system state and inertial parameter with high accuracy and real-time ability.

In the system of tracking and detection based on the four-quadrant detector (4-QD), the energy distribution of the incident spot and the blind area of the photosensitive surface will affect the location accuracy. The current model of the spot is based on the ideal circular Gauss spot, which makes the error caused by the spot shape easily ignored. In this paper, the model of the spot energy distribution is improved, which can adapt to the elliptical Gauss distribution. The width of the blind area is also added to the response models of the detector so that the output of each quadrant and the error of the localization algorithm can be calculated more accurately. The simulation results show that the measurement accuracy of 4-QD decreases with the increase of the blind area, the shape, and the inclination of the light spot. In the experiment, we first verify the correctness and practicability of the improved model of the spot energy distribution, and then the improved model is proved to be able to make the response and error calculation more accurate.

We consider a nonlinear integral eigenvalue problem, which is a reformulation of the transmission eigenvalue problem arising in the inverse scattering theory. The boundary element method is employed for discretization, which leads to a generalized matrix eigenvalue problem. We propose a novel method based on the spectral projection. The method probes a given region on the complex plane using contour integrals and decides whether the region contains eigenvalue(s) or not. It is particularly suitable to test whether zero is an eigenvalue of the generalized eigenvalue problem, which in turn implies that the associated wavenumber is a transmission eigenvalue. Effectiveness and efficiency of the new method are demonstrated by numerical examples.

A rapid, sensitive and selective ultra-high performance liquid chromatography tandem mass spectrometry method was developed and validated for the determination and pharmacokinetic investigation of seven catechins in rat plasma. The rat plasma was extracted with simple liquid–liquid extraction using ethyl acetate. Plasma sample was separated by UHPLC on a Hypersil GOLD C18column (1.9 μm, 50 × 2.1 mm) using a mobile phase consisting of methanol–0.05% formic acid in water with gradient elution. The total run time was 10.5 min and seven catechins were efficiently separated. The detection was performed on a selected reaction monitoring using the respective transitions m/z289.070 → 109.010 for (−)-epicatechin/(+)-catechin, 305.089 → 125.228 for (−)-epigallocatechin/(−)-gallocatechin and 441.150 → 169.325 for (−)-epicatechin gallate and 456.840 → 169.257 for (−)-epigallocatechin gallate/(−)-gallocatechin gallate. Mean recovery of seven catechins was in the range of 84.92–102.18%. The intra- and inter-day precisions (RSD) of these analytes were all less than 6.17% and 5.84%. This method was successfully applied in the pharmacokinetic study of seven catechins in the plasma of rats after oral administration of 700 mg kg−1tea polyphenols.

Pesticides are used in agricultural production worldwide, resulting in widespread environmental pollution. Many diseases are closely related to exposure to pesticide residues. In this study, the association between exposure to the pesticide flupyradifurone (FPF), a substitute for neonicotinoids, and sex-dependent thyroid dysfunction was explored for the first time. Exposure using rat models revealed that the FPF metabolism is sex-dependent, with males preferring N-dealkylation and hydrolytic metabolism and females preferring hydroxylation. In particular, novel chloropyridine-site hydroxylation I and II metabolic pathways of FPF were discovered. More importantly, differential metabolic pathways of FPF induced sex-based dysregulation of the hypothalamic–pituitary–thyroid axis, in which females exhibited subclinical hyperthyroidism, while males displayed abnormal hypothyroidism. This may be attributed to the potential agonistic or antagonistic effect of FPF sex-dependent metabolites on liver thyroid hormone receptors. Furthermore, FPF exposure further mediated sex-specific dysregulation of cellular lipid homeostasis, with abnormal fatty acid β-oxidation and excessive energy expenditure in females and the risk of excessive accumulation of triglycerides in males. These results illustrate the potential risk of sex-related thyroid metabolic diseases caused by FPF and provide an important basis and support for further studies of FPF on human health and as an environmental pollutant.

Abstract: In this paper, we propose and numerically investigate a family of locally divergence-free central discontinuous Galerkin methods for ideal magnetohydrodynamic (MHD) equations. The methods are based on the original central discontinuous Galerkin methods (SIAM Journal on Numerical Analysis 45 (2007) 2442–2467) for hyperbolic equations, with the use of approximating functions that are exactly divergence-free inside each mesh element for the magnetic field. This simple strategy is to locally enforce a divergence-free constraint on the magnetic field, and it is known that numerically imposing this constraint is necessary for numerical stability of MHD simulations. Besides the designed accuracy, numerical experiments also demonstrate improved stability of the proposed methods over the base central discontinuous Galerkin methods without any divergence treatment. This work is part of our long-term effort to devise and to understand the divergence-free strategies in MHD simulations within discontinuous Galerkin and central discontinuous Galerkin frameworks. [Copyright &y& Elsevier]

Environmental contextApatites form a large family of minerals and compounds that can incorporate a variety of ions, including arsenate that can substitute for phosphate. Apatites may therefore control the concentration of arsenic in some aqueous environments. This manuscript describes the synthesis and characterisation of the arsenate–phosphate hydroxylapatite solid solution and the solid solution–aqueous solution interaction.AbstractNine different members of the arsenate–phosphate hydroxylapatite solid solution [Ca5(PxAs1–xO4)3(OH)] were prepared and characterised by various techniques, and then dissolution of the synthetic solids was studied at 25°C and pH 2 in a series of batch experiments. The concentrations of aqueous arsenate species increased rapidly at the beginning of the dissolution and reached a steady-state after 480h. The concentrations of aqueous phosphate species increased very fast initially and reached a peak value within the first hour of dissolution and then declined slowly with time and remained constant after 240–360h. The solubility of the Ca5(PxAs1–xO4)3(OH) solid solution increased and its stability decreased with an increase in the mole fraction of Ca5(AsO4)3(OH). The dissolution followed or slightly overshot the Lippmann solutus curve, then approached the solutus curve. The Ca5(AsO4)3(OH)-poor solid solution was in equilibrium with the arsenate-rich aqueous solution.

Most researches focus on the regenerative braking system design in vehicle components control and braking torque distribution, few combine the connected vehicle technologies into braking velocity planning. If the braking intention is accessed by the vehicle-to-everything communication, the electric vehicles (EVs) could plan the braking velocity for recovering more vehicle kinetic energy. Therefore, this paper presents an energy-optimal braking strategy (EOBS) to improve the energy efficiency of EVs with the consideration of shared braking intention. First, a double-layer control scheme is formulated. In the upper-layer, an energy-optimal braking problem with accessed braking intention is formulated and solved by the distance-based dynamic programming algorithm, which could derive the energy-optimal braking trajectory. In the lower-layer, the nonlinear time-varying vehicle longitudinal dynamics is transformed to the linear time-varying system, then an efficient model predictive controller is designed and solved by quadratic programming algorithm to track the original energy-optimal braking trajectory while ensuring braking comfort and safety. Several simulations are conducted by jointing MATLAB and CarSim, the results demonstrated the proposed EOBS achieves prominent regeneration energy improvement than the regular constant deceleration braking strategy. Finally, the energy-optimal braking mechanism of EVs is investigated based on the analysis of braking deceleration, battery charging power, and motor efficiency, which could be a guide to real-time control.

The extensive use of neonicotinoid pesticides has led to their widespread presence in the environment, resulting in considerable safety risks to the ecosystem and human health. In this study, we investigated the biotransformation behavior of a cocktail of multiple neonicotinoids and piperonyl butoxide (PBO) synergist in vivoand their potential environmental health risk. It was found that neonicotinoids with a cyano group, such as acetamiprid and thiacloprid, tended to accumulate in liver and spleen tissues, while others with nitro groups (imidacloprid, thiamethoxam, clothianidin, dinotefuran, and nitenpyram) were mostly excreted in urine. In the presence of the synergist PBO, the metabolism of neonicotinoids in vivochanged, mainly through the nitro reduction pathway, while a low abundance of related metabolites was observed in the conventional hydroxylation and demethylation metabolic pathways, due to inhibition of CYP450 enzymes by the synergist. Furthermore, DNA methylation damage in vivowas exacerbated by the induction of hydroxylamine metabolites formed in the intermediate process of neonicotinoid metabolism with the synergistic effect of PBO, which resulted in a higher level of the O6-methyldeoxyguanosine (O6-medG) biomarker in the liver. Therefore, during the comprehensive evaluation of pesticide environmental risks, attention should be paid not only to the co-exposure mode under real environmental conditions but also to the potential risks of intermediate metabolism and related intermediate metabolites. This study provides a referential strategy and theoretical support for the health risk assessment of co-exposure of chemicals.

Nanodrug delivery systems possess the potential to revolutionize cancer therapy. An ideal nanoplatform should can effectively avoid the clearance of reticuloendothelial system (RES) and targeted accumulate at tumor sites. In addition, it should be nontoxic to the organism. Herein, the authors fabricated a biomimetic nanodrug delivery system possessed with these properties for targeted colorectal carcinoma therapy. This bilayer system was composed of irinotecan (IRN)-loaded gelatin nanogels (GN) as the inner cores and platelets membranes (PTM) as the outer shells, noted as PTM/GN/IRN. The resulting core–shell nanostructure of PTM/GN/IRN could effectively prevent the premature release of the laden IRN, which was beneficial for reducing the system side effects of IRN. Meanwhile, because of the tumor targeting ability of the coated PTM, PTM/GN/IRN could effectively accumulate at tumor sites. The in vivoantitumor activity results towards the HT-29 xenografts mouse models indicated that the PTM/GN/IRN could obviously suppress the tumor cells growth through causing the necrosis and apoptosis of tumor cells. In addition, since the PTM coating could avoid the premature release of the laden IRN, PTM/GN/IRN exhibited minimal side effects. The work presented here provides a promising strategy for effective targeted therapy of colorectal carcinoma.

We report a cladding-pumped actively Q-switched ring Tm-doped fiber laser (TDFL). This laser is Q-switched by a free space acousto-optic modulator. A pulse energy up to 150 μJ with a pulse width of 207 ns at a repetition rate of 100 Hz is achieved for a cavity optical length of 6.68 m. The pulse amplitude’s stability at this repetition rate is better than 95%. To the best of our knowledge, this is the first free space structure Q-switched ring TDFL report.