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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 via the 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 via the 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

We construct a modified rotated- Q 1 finite element, where we replace the P 2 bubbles of the Rannacher–Turek rotated- Q 1 element by multi-piece linear polynomials. In 2D, we use { 1 , x , y , | λ 1 | } as the basis on a general quadrilateral, where λ 1 is a linear polynomial which vanishes at the middle edge x 3 x 4 of two opposite mid-edge nodes x 1 and x 2 . In 3D, we use { 1 , x , y , z , | λ 1 | , | λ 3 | } as the basis on a general hexahedron, where λ 1 is a linear polynomial which vanishes at the mid plane x 3 x 4 x 5 x 6 between the two opposite mid-face nodes x 1 and x 2 , and λ 3 is a linear polynomial which vanishes at the mid plane x 1 x 2 x 5 x 6 between the two opposite mid-face nodes x 3 and x 4 . The new rotated- Q 1 finite element is shown inf-sup stable and quasi-optimal in solving the Stokes equations, on general quadrilateral and hexahedral meshes. Numerical tests in 2D and 3D show the method does converge quasi-optimally on non-asymptotic parallelogram or parallelepiped meshes, while the Rannacher–Turek rotated- Q 1 element fails to converge on such meshes. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Lightweight electric vehicles (LEVs) possess great advantages in the viewpoint of fuel consumption, environment protection and traffic mobility. However, due to the drastic reduction of vehicle weights and body size, the effects of payload parameter variation in LEV control and estimation system become much more pronounced and have to be systematically analysed. This paper proposes a novel payload parameter sensitivity analysis to provide quantitative insight into the sensitivity of payload parameter on the LEV system responses and state estimation. The analysis-oriented LEV dynamic model considering payload parameter variations is developed. Then, the trajectory sensitivity index of the influential parameters is defined and derived with the perturbation approach, the median method is used to improve the calculation accuracy for the trajectory sensitivity of payload parameter. Finally, the extended Kalman filter is designed to show the effect and importance of the sensitive payload parameters on the observation accuracy, the payload parameter variations along with fundamental state estimation such as vehicle sideslip angle, longitudinal velocity and vehicle roll angle are analysed. Simulation results with Matlab/Simulink-Carsim® show that the proposed method can accurately describe the relationship between the vehicle payload parameters and system state estimation, which is helpful to design and evaluate LEV controller and observer performances. [ABSTRACT FROM AUTHOR]

In this paper, we propose a stochastic Gauss–Newton (SGN) algorithm to study the online principal component analysis (OPCA) problem, which is formulated by using the symmetric low-rank product model for dominant eigenspace calculation. Compared with existing OPCA solvers, SGN is of improved robustness with respect to the varying input data and algorithm parameters. In addition, turning to an evaluation of data stream based on approximated objective functions, we develop a new adaptive stepsize strategy for SGN which requires no priori knowledge of the input data, and numerically illustrate its comparable performance with SGN adopting the manaully-tuned diminishing stepsize. Without assuming the eigengap to be positive, we also establish the global and optimal convergence rate of SGN with the specified stepsize using the diffusion approximation theory. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Prior research has ignored the influence of fluctuation factors on online public opinion in emergencies, which has led to low prediction accuracy. This paper determines fluctuation factors through text analysis and emotional calculation; it identifies the main factors that cause the fluctuation in public opinion through the Granger causality test. Furthermore, we built a trend prediction model based on the gray prediction model and optimized it by considering the fluctuation factors of online public opinion. Optimization enhances the precision of the model and makes it more suitable to forecast trends for online public opinion. Finally, by looking at a large number of online public opinion on four kinds of typical emergencies, we verified the validity of the proposed model. In short, this paper provides a novel theoretical perspective for trend prediction of online public opinion research. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In this study, we investigated the in vivo behaviors of chiral cobalt oxide nanoparticles (Co3O4 NPs) stabilized with D- or L-cysteine (denoted D- or L-NPs, respectively), as representative chiral metal oxide NPs. Chiral Co3O4 NPs exerted no observable cytotoxicity within the tested dose range. Both D-NPs and L-NPs were internalized by dendritic cells through caveola-dependent endocytosis, and L-NPs entered the cells faster than D-NPs. Significantly, a metabolic analysis indicated that chiral L-NPs had the same effect on the level of bile acids in the liver as D-NPs, which is attributed to the almost equal amount of farnesoid X receptor (FXR) induced by the chiral NPs. This study suggests that low chiroptical activity nanomaterials would not affect the metabolism and kinetics under physiological conditions even if there is some difference in their transport. [ABSTRACT FROM AUTHOR]

It is well known that the Fourier series Dirichlet-to-Neumann (DtN) boundary condition can be used to solve the Helmholtz equation in unbounded domains. In this work, applying such DtN boundary condition and using the finite element method, we analyze and solve a two dimensional transmission problem describing elastic waves inside a bounded and closed elastic obstacle and acoustic waves outside it. We are mainly interested in analyzing the DtN boundary condition of the Helmholtz equation in order to establish the well-posedness results of the approximated variational equation, and further derive a priori error estimates involving effects of both the finite element discretization and the truncation of DtN map. Finally, some numerical results are presented to illustrate the accuracy of the numerical scheme. [ABSTRACT FROM AUTHOR]

The quad-curl problem arises in magnetohydrodynamics, inverse electromagnetic scattering problems, and electromagnetic transmission eigenvalue problems. In this paper, we propose a hybridizable discontinuous Galerkin method to solve the quad-curl problem, and perform the analysis with a relatively low regularity assumption. The efficiency and accuracy of the proposed method are illustrated through numerical experiments. [ABSTRACT FROM AUTHOR]

Semiconductor superlattice secure key distribution (SSL-SKD) has been experimentally demonstrated to be a novel scheme to generate and agree on the identical key in unconditional security just by public channel. The error correction in the information reconciliation procedure is introduced to eliminate the inevitable differences of analog systems in SSL-SKD. Nevertheless, the error correction has been proved to be the performance bottleneck of information reconciliation for high computational complexity. Hence, it determines the final secure key throughput of SSL-SKD. In this paper, different frequently-used error correction codes, including BCH codes, LDPC codes, and Polar codes, are optimized separately to raise the performance, making them usable in practice. Firstly, we perform multi-threading to support multi-codeword decoding for BCH codes and Polar codes and updated value calculation for LDPC codes. Additionally, we construct lookup tables to reduce redundant calculations, such as logarithmic table and antilogarithmic table for finite field computation. Our experimental results reveal that our proposed optimization methods can significantly promote the efficiency of SSL-SKD, and three error correction codes can reach the throughput of Mbps and provide a minimum secure key rate of 99%. [ABSTRACT FROM AUTHOR]

Vehicle dynamics plays a significant role on the formation of a vehicle platoon, especially at high speed condition. This paper proposes a distributed platoon formation framework for homogeneous autonomous vehicles which takes the vehicle dynamics into consideration. The boundaries of vehicle stability are firstly calculated by considering both lateral dynamics and actuator saturation. By combining the stability boundaries with multi-objective flocking (MOF) algorithm, a distributed formation controller is designed, which can form the vehicle platoon with high cruising speed steadily and rapidly. In addition, a low-level tracking controller is proposed to constitute a hierarchical control architecture which can achieve stable and accurate formation of platoon. Simulation results show the proposed platoon formation controller achieves safe, stable and rapid platoon formation than the traditional MOF-based formation controller which does not consider the vehicle dynamics. [ABSTRACT FROM AUTHOR]

In this paper, we first present a family of high order central discontinuous Galerkin methods defined on unstructured overlapping meshes for the two-dimensional conservation laws. The primal mesh is a triangulation of the computational domain, while the dual mesh is a quadrangular partition which is formed by connecting an interior point and the three vertexes of each triangle on the primal mesh. We prove the L 2 stability of the present method for linear equation. Then we design and analyze high order maximum-principle-satisfying central discontinuous Galerkin methods for two-dimensional scalar conservation law, and high order positivity-preserving central discontinuous Galerkin methods for two-dimensional compressible Euler systems. The performance of the proposed methods is finally demonstrated through a set of numerical experiments. [ABSTRACT FROM AUTHOR]

In this paper, we consider the development of central discontinuous Galerkin methods for solving the nonlinear shallow water equations over variable bottom topography in one and two dimensions. A reliable numerical scheme for these equations should preserve still-water stationary solutions and maintain the non-negativity of the water depth. We propose a high-order technique which exactly balances the flux gradients and source terms in the still-water stationary case by adding correction terms to the base scheme, meanwhile ensures the non-negativity of the water depth by using special approximations to the bottom together with a positivity-preserving limiter. Numerical tests are presented to illustrate the accuracy and validity of the proposed schemes. [ABSTRACT FROM AUTHOR]

We consider a non-selfadjoint fourth order eigenvalue problem using a discontinuous Galerkin (DG) method. For high order problems, DG methods are competitive since they use simple basis functions and have less degrees of freedom. The numerical implementation is much easier compared with classical conforming finite element methods. In this paper, we propose an interior penalty discontinuous Galerkin method using $$C^0$$ Lagrange elements ( $$C^0$$ IP) for the transmission eigenvalue problem and prove the optimal convergence. The method is applied to several examples and its effectiveness is validated. [ABSTRACT FROM AUTHOR]