The interlaminar shear failure characteristics of asphalt pavement coupled heating cables

Nowadays, heating cables are used as heat sources for heating pavements in practical engineering. However, there is a contradiction between the snow melting function and the interlaminar stability of heating pavement. In order to solve the contradiction, the interlaminar failure behavior of asphalt mixture coupled heating cables specimen (AMCS) was researched, through experiments and the finite element method. Under the different conditions of heating cables and rolling times, a series of direct shear tests was performed at the interface of AMCS, to compare the interlaminar stability of three different AMCS. Meanwhile, based on the bilinear cohesive zone model and coulomb friction model a 2D finite element model was established, to simulate this shear failure processes and make up for the limitations of the experiment. According to above test and simulation results, the failure mechanism and the weakest interface in AMCS were found, and the influence of the heating cable’s diameter and embedded spacing on the interlaminar shear strength were found. Then, a modified coulomb theorem model was proposed to predict the shear strength of the AMCS. This research enriches the design theory of the heating pavement and it has great significance for its structural design of heating asphalt pavement.     

Unique role of non-mercapto groups in thiol-pinning-mediated Ag growth on Au nanoparticles

Owing to the strong affinity of thiols to Au and Ag, they are often employed to modify the surfaces of nanoparticles (NPs). Recently, these strong ligand-interface interactions have been employed to control NP growth, and this technique has emerged as a unique modulation strategy for creating unconventional plasmonic hybrid nanostructures. In these systems, the roles of the non-mercapto components of the thiol molecules and their structures are still unknown. Therefore, we herein present our investigation into this phenomenon. Primary amino (–NH₂) groups in thiols are found to play a key role in regulating growth kinetics, i.e., in accelerating Ag deposition on Au NPs. The–NH₂ groups are thought to bring Ag ions to the particle surface by coordinating to them, and thereby assist their reduction. The effect of molecular structure is non-trivial and thus provides the possibility of selective thiol detection. Based on the dependence of kinetic modulation on the non-mercapto components and molecular structures of molecules, we demonstrate the highly sensitive and specific detection of cysteine (limit of detection: 6 nM) in a mixture of 19 natural amino acids based on Ag growth on Au nanospheres. In addition, based on this modulation effect, we reveal the entrapping of chiral thiols within the growth layer through their plasmonic circular dichroism (PCD) responses. We believe that thiol-based growth regulation has great potential for creating plasmonic nanostructures with novel functionalities.

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Physics-Informed Multistage Machine Learning Strategy for the Nanomachining-Induced Plastic Deformation Behavior

The evolution of the dislocation density induced by the nanomachining process dominates the plastic deformation behaviors of materials, thus affecting the mechanical properties significantly. However, a challenging topic related to how to establish an accurate model for predicting the dislocation density based on the limited simulations and experiments arises due to the complicated thermal–mechanical coupling mechanism during the machining process. Herein, a multistage method integrating machine learning, physics, and high-throughput atomic simulation is proposed to investigate the effect of cutting speed on the dislocation behavior in polycrystal copper. Compared with the traditional one-step machine learning method, the constraint of physical features effectively improves the accuracy and generalization ability of the model. The results indicate that the dislocation behaviors depend on the competition between the cutting force and temperature. In the low-cutting speed, the predominated role of the cutting temperature leads to a rapid decline of the dislocation density. In contrast, the dislocation density tends to be stable under a high-speed cutting process due to the dynamic balance between the effects of the cutting force and temperature. Notably, the proposed strategy provides a new and universal framework to design the machining parameters to obtain high-quality products.     

Steady-state limiting currents determined by coupled diffusion, migration, and chemical equilibrium

A simple theoretical model is presented for the reduction of a singly charged cation under conditions where migration is important and the cation is coupled to a neutral species through a chemical equilibrium, AB = A(+) + B(-). Only the steady-state transport-limited current, I(l), is considered. Simple algebraic equations describe the ratio of I(l) to the diffusion-limited current, I(d), as it depends on the degree of dissociation, determined by the ratio of equilibrium constant to formal concentration, K(AB)/C*(AB). The ratio I(l)/I(d) is found to depend on the ratio of electrolyte to equilibrium concentration of A(+) in bulk solution just as for the well-known result for the case without the equilibrium (i.e., K(AB) → ∞). The results are in accord with published experimental data for weak acids. Agreement and disagreement with other theoretical treatments of this problem are discussed. The main results are for 1:1 supporting electrolytes; extensions are made to 2:1, 1:2, and 2:2 supporting electrolytes.     

Research on the group decision-making about emergency event based on network technology

In order to improve decision-making efficiency about emergency event, this paper proposes a novel concept, i.e., Agile-Delphi Method, which is an integration of agile decision and Delphi Method implicating that the decision-makers instantly deliver, respond, treat, and utilize information via Delphi process while conducting group decision-making about emergency event. The paper details the mechanism of group decision-making about emergency event based on network technology and Agile-Delphi Method. Finally, the paper conducts an empiric analysis taking the “111 event”, i.e., the liquid ammonia spill event happened on November 1, 2006 in a phosphorus chemical company in China, as an example.     

Interactive surgery simulation for the nose augmentation using CT data

Surgery to reshape the nose with an implant has been a regular procedure for enhancing a patient’s appearance and self-confidence. The purpose of this study was to establish a computed tomography (CT) based three-dimensional assistant plastic surgery systems, which can provide the patients with realistic prediction of their own postoperative appearance in computer and specifically produce a nose implant for an individual patient. Preoperative CT data and 3D reconstruction techniques were employed to generate 3D model of the patient’s skull. 3D collision detection and finite elements model deformation were then applied to simulate nose augmentation surgery and predict postoperative appearance. According to the patient’s expectation, digital models of the nose implants were constantly modified. When the patient is satisfied with the simulated results, custom made silicone implants were produced by a computer controlled device. Accurately regeneration of 3D images and realistic operative simulations could be achieved with this system. The implants produced exactly conformed to the results of simulation. No curving and reshaping were needed during operating. The clinical results extremely matched with the simulations. The system enhances surgeon patient communication and facilitates preoperative planning. It is especially desirable for implant surgery with less guesswork of size, contour, and orientation of the implant. The best chance of optimal results could be achieved.     

基于粒子系统和音频系统的烟花模拟

针对模糊物体的模拟方法存在着粒子数量绘制巨大、粒子运动状态复杂、计算耗时、实时性及逼真性不够等问题,提出了一种基于粒子系统和音频系统的烟花模拟方法,以三角形格作为绘制烟花粒子的基本图元,结合纹理映射,色彩融合技术来绘制烟花粒子,在显示列表中生成纹理,再结合FMOD引擎技术,加入音频系统,实验结果表明提出的方法增强了模拟的逼真性.     

Evaluation of Landsat 8 OLI imagery for unsupervised inland water extraction

The successful launch of the Landsat 8 satellite continues the Earth observation of the Landsat series, which has been taking place for nearly 40 years. With the increase in the band number and the improved spectral range compared with the previous Landsat imagery, it will be possible to expand the application of the new Landsat 8 imagery. The purpose of this study is to explore water extraction based on the new Landsat 8 Operational Land Imager (OLI) imagery. According to the specific inland water conditions (clear water, turbid water, and eutrophic water), a number of highly adaptable water indices are assessed for water extraction using Landsat OLI imagery. The results show that clear water is the easiest to extract among the different types of waterbodies, with the highest average accuracy of 97%. The highest-accuracy methods are the automated water extraction index for shadow pixels (AWEI_sh), the normalized difference water index using bands 4 and 7 (NDWI₄₇), and the normalized difference water index using bands 3 and 7 (NDWI₃₇), with accuracies of 98.55%, 95.50%, and 96.61%, corresponding to clear water, turbid water, and eutrophic water, respectively. Through the analysis of the different methods for optimal band selection, the seventh band OLI7 (shortwave infrared 2, SWIR-2) of Landsat OLI shows the best performance in water identification. When applying the water indices to water extraction, Otsu’s algorithm has been used to automatically select the water threshold. Using extensive experiments with Otsu’s algorithm and a manual method, it was found that Otsu’s algorithm can replace manual selection and has the ability to select an accurate threshold for water extraction.