Bifurcation analysis of visual angle model with anticipated time and stabilizing driving behavior

In the light of the visual angle model (VAM), an improved car-following model considering driver's visual angle, anticipated time and stabilizing driving behavior is proposed so as to investigate how the driver's behavior factors affect the stability of the traffic flow. Based on the model, linear stability analysis is performed together with bifurcation analysis, whose corresponding stability condition is highly fit to the results of the linear analysis. Furthermore, the time-dependent Ginzburg-Landau (TDGL) equation and the modified Korteweg-de Vries (mKdV) equation are derived by nonlinear analysis, and we obtain the relationship of the two equations through the comparison. Finally, parameter calibration and numerical simulation are conducted to verify the validity of the theoretical analysis, whose results are highly consistent with the theoretical analysis.     

Shape morphing and topology optimization of fluid channels by explicit boundary tracking

An integrated shape morphing and topology optimization approach based on the deformable simplicial complex methodology is developed to address Stokes and Navier‐Stokes flow problems. The optimized geometry is interpreted by a set of piecewise linear curves embedded in a well‐formed triangular mesh, resulting in a physically well‐defined interface between fluid and impermeable regions. The shape evolution is realized by deforming the curves while maintaining a high‐quality mesh through adaption of the mesh near the structural boundary, rather than performing global remeshing. Topological changes are allowed through hole merging or splitting of islands. The finite element discretization used provides smooth and stable optimized boundaries for simple energy dissipation objectives. However, for more advanced problems, boundary oscillations are observed due to conflicts between the objective function and the minimum length scale imposed by the meshing algorithm. A surface regularization scheme is introduced to circumvent this issue, which is specifically tailored for the deformable simplicial complex approach. In contrast to other filter‐based regularization techniques, the scheme does not introduce additional control variables, and at the same time, it is based on a rigorous sensitivity analysis. Several numerical examples are presented to demonstrate the applicability of the approach.     

[2]Pseudorotaxane-Based Supramolecular Optical Indicator for the Visual Detection of Cellular Cyanide Excretion

Cyanide is extremely hazardous to living organisms and the environment. Owing to its wide range of applications and high toxicity, the development of functional materials for cyanide detection and sensing is highly desirable. Host–guest complexation between bis(p-phenylene)-34-crown-10 H and N-methylacridinium salt G remarkably decreases the detection limit for cyanide anions compared with that of the guest itself. The [2]pseudorotaxane selectively recognizes the cyanide anion with high optical sensitivity as a result of the nucleophilic addition of the cyanide anion at the 9-position of G . The host–guest complexation is further incorporated into supramolecular materials for the visual detection of cyanide anions, especially the detection of cellular cyanide excretion with a detection limit of 0.6 μm . This supramolecular method provides an extremely distinct strategy for the visual detection of cyanide anions.     

湍流大气传输中跟踪抖动对远场影响的仿真研究

分析了跟踪抖动对湍流大气传输远场光斑的影响。基于麦克斯韦电磁场理论,采用大气相干长度对大气湍流进行描述,推导了发射光束因跟踪抖动导致光轴偏离的远场表达式。在此基础上,利用相位屏法模拟抖动引起的倾斜相位和大气折射率起伏引起的相位调制,并采用低频补偿的功率谱反演法对传输过程进行了数值仿真。分析了不同跟踪抖动、湍流强度条件下远场光斑质心脱靶量的变化,以及不同尺寸模拟目标的回波概率。分析结果表明,在传输距离为10 km时,强湍流造成的远场光斑脱靶量可达几十μrad;当跟踪抖动较大时,湍流强弱对脱靶量影响差别很小。最后,对一定尺寸的模拟目标,从探测回波概率的角度给出了发射系统跟踪抖动量的控制范围。     

A velocity program using the Kanade–Lucas–Tomasi feature-tracking algorithm with demonstration for pressure and electroosmosis conditions

Investigating microfluidic flow profiles is of interest in the microfluidics field for the determination of various characteristics of a lab-on-a-chip system. Microparticle tracking velocimetry uses computational methods upon recording video footage of microfluidic flow to ultimately visualize motion within a microfluidic system across all frames of a video. Current methods are computationally expensive or require extensive instrumentation. A computational method suited to microparticle tracking applications is the robust Kanade–Lucas–Tomasi (KLT) feature-tracking algorithm. This work explores a microparticle tracking velocimetry program using the KLT feature-tracking algorithm. The developed program is demonstrated using pressure-driven and EOF and compared with the respective mathematical fluid flow models. An electrostatics analysis of EOF conditions is performed in the development of the mathematical using a Poisson's Equation solver. This analysis is used to quantify the zeta potential of the electroosmotic system. Overall, the KLT feature-tracking algorithm presented in this work proved to be highly reliable and computationally efficient for investigations of pressure-driven and EOF in a microfluidic system.     

Distinguishing and quantification of the human visual pathways using high-spatial-resolution diffusion tensor tractography

Quantification of the living human visual system using MRI methods has been challenging, but several applications demand a reliable and time-efficient data acquisition protocol. In this study, we demonstrate the utility of high-spatial-resolution diffusion tensor fiber tractography (DTT) in reconstructing and quantifying the human visual pathways. Five healthy males, age range 24–37 years, were studied after approval of the institutional review board (IRB) at The University of Texas Health Science Center at Houston. We acquired diffusion tensor imaging (DTI) data with 1-mm slice thickness on a 3.0-Tesla clinical MRI scanner and analyzed the data using DTT with the fiber assignment by continuous tractography (FACT) algorithm. By utilizing the high-spatial-resolution DTI protocol with FACT algorithm, we were able to reconstruct and quantify bilateral optic pathways including the optic chiasm, optic tract, optic radiations free of contamination from neighboring white matter tracts.     

A correlative classifiers approach based on particle filter and sample set for tracking occluded target

Target tracking is one of the most important issues in computer vision and has been applied in many fields of science, engineering and industry. Because of the occlusion during tracking, typical approaches with single classifier learn much of occluding background information which results in the decrease of tracking performance, and eventually lead to the failure of the tracking algorithm. This paper presents a new correlative classifiers approach to address the above problem. Our idea is to derive a group of correlative classifiers based on sample set method. Then we propose strategy to establish the classifiers and to query the suitable classifiers for the next frame tracking. In order to deal with nonlinear problem, particle filter is adopted and integrated with sample set method. For choosing the target from candidate particles, we define a similarity measurement between particles and sample set. The proposed sample set method includes the following steps. First, we cropped positive samples set around the target and negative samples set far away from the target. Second, we extracted average Haar-like feature from these samples and calculate their statistical characteristic which represents the target model. Third, we define the similarity measurement based on the statistical characteristic of these two sets to judge the similarity between candidate particles and target model. Finally, we choose the largest similarity score particle as the target in the new frame. A number of experiments show the robustness and efficiency of the proposed approach when compared with other state-of-the-art trackers.     

A novel lipid droplets-targeting fluorescent probe based on dicyanisophorone and carbazole for Cu2+ and its application

A novel fluorescent probe, LCH , based on dicyanisophorone and carbazole, was prepared for the visual detection of Cu²⁺. The probe LCH could recognize Cu²⁺ by fluorescence quenching in EtOH/H₂O (1/4, v/v) solution, which could be easily identified under the 365 nm UV lamp, and the detection limit was as low as 0.785 μM. The recognition mechanism of probe LCH with Cu²⁺ was determined by combining ¹H NMR titration, MS, and theoretical calculations. Practical application experiments showed that probe LCH could be used to detect Cu²⁺ in the test strip experiments. Cell imaging experiments showed that the probe LCH owned good cell permeability and could be applied to the imaging of Cu²⁺ in HepG2 cells. In addition, fluorescence colocalization experiments showed that LCH could target lipid droplets. These results indicate that the probe LCH will have a good application prospect in environmental detection and clinical medicine.