In Situ

The durability of existing concrete structures has increasingly attracted widespread attention in recent years. The phenomenon of performance degradation is often associated with the intrusion of hazardous ions from outside. As the first barrier to external substances intrusion, the near-surface concrete plays an important role in durability. So the performance of in-service concrete structures often depends on the transport properties of the near-surface concrete. Accordingly, information on service conditions and life prediction can be obtained by testing these transport properties. In this paper, an in situ method for chloride ion diffusion coefficient determination is proposed based on the relationship between the alternating current impedance spectroscopy parameters and the chloride ion diffusion coefficient. By a rational design, the new method can synthetically reflect the transport properties of near-surface concrete and is not affected by the presence of the reinforcing bar. In addition, the experimental results show that the method is in good agreement with “PERMIT” migration test which has been widely used. The proposed method is less time consuming and nondestructive and has good reproducibility

Determination of the Transport Properties of Structural Concrete Using AC Impedance Spectroscopy Techniques

All over the world, particularly in severe environmental conditions, there are reinforced concrete structures that develop nonnegligible phenomena of durability problems. Most of the durability problems are related to hazardous substances invasion. Both engineering practice and scientific studies have revealed that the transport property of near-surface concrete is a main factor in the durability of concrete structures. Among many transport parameters, the chloride ion diffusion coefficient is the most important one, which provides important information on material design and service life prediction. In this paper, AC impedance spectroscopy technology was employed in the measurement of chloride ion diffusion coefficient. The relationship between mesostructure parameters and chloride ion diffusion coefficient was deduced by introducing a reasonable equivalent circuit model. Taking into account the conductivity difference caused by various cementitious material systems, the diffusion coefficient can be corrected, and a diffusion coefficient determination method based on AC impedance spectroscopy technique was established. For the convenience of application, a relationship between the newly proposed method and a widely recognized standard method was obtained. The proposed method can be applied to laboratory testing and establishes the theoretical basis for field tests

Mimicry, Knowledge Spillover and Expatriate Assignment Strategy in Overseas Subsidiaries

Based on neo-institutional theory and knowledge spillover, we argue that the probability of a firm assigning an expatriate manager to a foreign subsidiary is influenced by a combination of mimicry and knowledge spillover from any existing expatriate community in the foreign location. The expatriate community's influence is hypothesized to be weaker when the firm's ownership share in its foreign subsidiary is greater but stronger when the cultural distance between a firm's home country and the foreign host country is greater. Data on 95,156 foreign-invested manufacturing ventures in China is used to test these predictions. The findings show an inverted U-shaped relationship between the assignment of expatriates and the number of expatriates previously sent to the same location by prior foreign investors. This relationship is shown to be moderated by subsidiary ownership, but not by the cultural distance between the investor's home country and the host country. Implications for research and practice are discussed

Research on Energy Response Characteristics of Rock under Harmonic Vibro-Impacting Drilling

Open access via Springer Compact Agreement The support of National Natural Science Foundation of China (No. 51704074) and Youth Science Foundation of Heilongjiang Province (No. QC2018049) are gratefully acknowledged. The work is also supported by Talent Cultivation Foundation (No. SCXHB201703; No. ts26180119; No. td26180141) and Youth Science Foundation (No. 2019QNL-07) of Northeast Petroleum University.Peer reviewedPublisher PD

Investigation of low-dissipation monotonicity-preserving scheme for direct numerical simulation of compressible turbulent flows

© 2014 Elsevier Ltd. The influence of numerical dissipation on direct numerical simulation (DNS) of decaying isotropic turbulence and turbulent channel flow is investigated respectively by using the seventh-order low-dissipation monotonicity-preserving (MP7-LD) scheme with different levels of bandwidth dissipation. It is found that for both benchmark test cases, small-scale turbulence fluctuations can be largely suppressed by high level of scheme dissipation, while the appearance of numerical errors in terms of high-frequency oscillations could destabilize the computation if the dissipation is reduced to a very low level. Numerical studies show that reducing the bandwidth dissipation to 70% of the conventional seventh-order upwind scheme can maximize the efficiency of the MP7-LD scheme in resolving small-scale turbulence fluctuations and, in the meantime preventing the accumulation of non-physical numerical errors. By using the optimized MP7-LD scheme, DNS of an impinging oblique shock-wave interacting with a spatially-developing turbulent boundary layer is conducted at an incoming free-stream Mach number of 2.25 and the shock angle of 33.2°. Simulation results of mean velocity profiles, wall surface pressure, skin friction and Reynolds stresses are validated against available experimental data and other DNS predictions in both the undisturbed equilibrium boundary layer region and the interaction zone, and good agreements are achieved. The turbulence kinetic energy transport equation is also analyzed and the balance of the equation is well preserved in the interaction region. This study demonstrates the capability of the optimized MP7-LD scheme for DNS of complex flow problems of wall-bounded turbulent flow interacting with shock-waves

CLUE: Calibrated Latent Guidance for Offline Reinforcement Learning

Offline reinforcement learning (RL) aims to learn an optimal policy from pre-collected and labeled datasets, which eliminates the time-consuming data collection in online RL. However, offline RL still bears a large burden of specifying/handcrafting extrinsic rewards for each transition in the offline data. As a remedy for the labor-intensive labeling, we propose to endow offline RL tasks with a few expert data and utilize the limited expert data to drive intrinsic rewards, thus eliminating the need for extrinsic rewards. To achieve that, we introduce \textbf{C}alibrated \textbf{L}atent g\textbf{U}idanc\textbf{E} (CLUE), which utilizes a conditional variational auto-encoder to learn a latent space such that intrinsic rewards can be directly qualified over the latent space. CLUE's key idea is to align the intrinsic rewards consistent with the expert intention via enforcing the embeddings of expert data to a calibrated contextual representation. We instantiate the expert-driven intrinsic rewards in sparse-reward offline RL tasks, offline imitation learning (IL) tasks, and unsupervised offline RL tasks. Empirically, we find that CLUE can effectively improve the sparse-reward offline RL performance, outperform the state-of-the-art offline IL baselines, and discover diverse skills from static reward-free offline data

Probing the Cytoadherence of Malaria Infected Red Blood Cells under Flow

Malaria is one of the most widespread and deadly human parasitic diseases caused by the Plasmodium (P.) species with the P.falciparum being the most deadly. The parasites are capable of invading red blood cells (RBCs) during infection. At the late stage of parasites’ development, the parasites export proteins to the infected RBCs (iRBC) membrane and bind to receptors of surface proteins on the endothelial cells that line microvasculature walls. Resulting adhesion of iRBCs to microvasculature is one of the main sources of most complications during malaria infection. Therefore, it is important to develop a versatile and simple experimental method to quantitatively investigate iRBCs cytoadhesion and binding kinetics. Here, we developed an advanced flow based adhesion assay to demonstrate that iRBC’s adhesion to endothelial CD36 receptor protein coated channels is a bistable process possessing a hysteresis loop. This finding confirms a recently developed model of cell adhesion which we used to fit our experimental data. We measured the contact area of iRBC under shear flow at different stages of infection using Total Internal Reflection Fluorescence (TIRF), and also adhesion receptor and ligand binding kinetics using Atomic Force Microscopy (AFM). With these parameters, we reproduced in our model the experimentally observed changes in adhesion properties of iRBCs accompanying parasite maturation and investigated the main mechanisms responsible for these changes, which are the contact area during the shear flow as well as the rupture area size.Global Enterprise for Micro-Mechanics and Molecular MedicineUnited States. Dept. of Defense (DOD-ARO (W 911 NF-09-0480))Singapore–MIT Alliance for Research and Technology ((SMART) Fellowship)National Science Foundation (U.S.) (NSF Grant No.1112825

Towards Unified Representation of Multi-Modal Pre-training for 3D Understanding via Differentiable Rendering

State-of-the-art 3D models, which excel in recognition tasks, typically depend on large-scale datasets and well-defined category sets. Recent advances in multi-modal pre-training have demonstrated potential in learning 3D representations by aligning features from 3D shapes with their 2D RGB or depth counterparts. However, these existing frameworks often rely solely on either RGB or depth images, limiting their effectiveness in harnessing a comprehensive range of multi-modal data for 3D applications. To tackle this challenge, we present DR-Point, a tri-modal pre-training framework that learns a unified representation of RGB images, depth images, and 3D point clouds by pre-training with object triplets garnered from each modality. To address the scarcity of such triplets, DR-Point employs differentiable rendering to obtain various depth images. This approach not only augments the supply of depth images but also enhances the accuracy of reconstructed point clouds, thereby promoting the representative learning of the Transformer backbone. Subsequently, using a limited number of synthetically generated triplets, DR-Point effectively learns a 3D representation space that aligns seamlessly with the RGB-Depth image space. Our extensive experiments demonstrate that DR-Point outperforms existing self-supervised learning methods in a wide range of downstream tasks, including 3D object classification, part segmentation, point cloud completion, semantic segmentation, and detection. Additionally, our ablation studies validate the effectiveness of DR-Point in enhancing point cloud understanding

Dielectric Property of MoS2 Crystal in Terahertz and Visible Region

Two-dimensional materials such as MoS2 have attracted much attention in recent years due to their fascinating optoelectronic properties. Dielectric property of MoS2 is desired for the optoelectronic application. In this paper, terahertz (THz) time-domain spectroscopy and ellipsometry technology are employed to investigate the dielectric response of MoS2 crystal in THz and visible region. The real and imaginary parts of the complex dielectric constant of MoS2 crystal are found to follow a Drude model in THz region, which is due to the intrinsic carrier absorption. In visible region, the general trend of the complex dielectric constant is found to be described with a Lorentz model, while two remarkable peaks are observed at 1.85 and 2.03 eV, which have been attributed to the splitting arising from the combined effect of interlayer coupling and spin-orbit coupling. This work affords the fundamental dielectric data for the future optoelectronic applications with MoS2.Comment: 6 page