Synergistic Damage Mechanic Model for Stiffness Properties of Early Fatigue Damage in Composite Laminates

AbstractIn the initial period of the life in the composite laminates, the principal types of damage are diffused ones, such as matrix crack, diffused fiber breaking and local delamination. On account of these diffused damages, a synergistic damage mechanic model was proposed for the stiffness properties. The model included the microcosmic responses of the physical damage and macroscopic performance of the material's stiffness. In micro-level, mesoscopic RVE(representative volume element) model was established to obtain crack opening displacement and crack sliding displacement, which were used to define the damage tensor. In macro- level, through homogenizing the material strain and the surface displacement of the damage, the relationship of the stiffness matrix of unidirectional laminate or laminates in damage statue and damage tense was set up. Due to restriction of NDT (non- destructive testing) technology development, only the constitutive relations of matrix cracks were constructed. The influences of the transverse matrix cracks on the stiffness properties of the laminates [0/±45]s was analyzed with the present model and showed that it is capable to predict the reduction of the stiffness properties resulted from the fatigue diffused damage in the laminates

Deep Descriptor Transforming for Image Co-Localization

Reusable model design becomes desirable with the rapid expansion of machine learning applications. In this paper, we focus on the reusability of pre-trained deep convolutional models. Specifically, different from treating pre-trained models as feature extractors, we reveal more treasures beneath convolutional layers, i.e., the convolutional activations could act as a detector for the common object in the image co-localization problem. We propose a simple but effective method, named Deep Descriptor Transforming (DDT), for evaluating the correlations of descriptors and then obtaining the category-consistent regions, which can accurately locate the common object in a set of images. Empirical studies validate the effectiveness of the proposed DDT method. On benchmark image co-localization datasets, DDT consistently outperforms existing state-of-the-art methods by a large margin. Moreover, DDT also demonstrates good generalization ability for unseen categories and robustness for dealing with noisy data.Comment: Accepted by IJCAI 201

Intermediate-statistics quantum bracket, coherent state, oscillator, and representation of angular momentum (su(2)) algebra

In this paper, we first discuss the general properties of an intermediate-statistics quantum bracket, $[ u,v]_{n}=uv-e^{i2\pi /(n+1)}vu$, which corresponds to intermediate statistics in which the maximum occupation number of one quantum state is an arbitrary integer, $n$. A further study of the operator realization of intermediate statistics is given. We construct the intermediate-statistics coherent state. An intermediate-statistics oscillator is constructed, which returns to bosonic and fermionic oscillators respectively when $n\to \infty$ and $n=1$. The energy spectrum of such an intermediate-statistics oscillator is calculated. Finally, we discuss the intermediate-statistics representation of angular momentum ($su(2)$) algebra. Moreover, a further study of the operator realization of intermediate statistics is given in the Appendix.Comment: 12 pages, no figures. Revte

Research on Self-adaptive Online Vehicle Velocity Prediction Strategy Considering Traffic Information Fusion

In order to increase the prediction accuracy of the online vehicle velocity prediction (VVP) strategy, a self-adaptive velocity prediction algorithm fused with traffic information was presented for the multiple scenarios. Initially, traffic scenarios were established inside the co-simulation environment. In addition, the algorithm of a general regressive neural network (GRNN) paired with datasets of the ego-vehicle, the front vehicle, and traffic lights was used in traffic scenarios, which increasingly improved the prediction accuracy. To ameliorate the robustness of the algorithm, then the strategy was optimized by particle swarm optimization (PSO) and k-fold cross-validation to find the optimal parameters of the neural network in real-time, which constructed a self-adaptive online PSO-GRNN VVP strategy with multi-information fusion to adapt with different operating situations. The self-adaptive online PSO-GRNN VVP strategy was then deployed to a variety of simulated scenarios to test its efficacy under various operating situations. Finally, the simulation results reveal that in urban and highway scenarios, the prediction accuracy is separately increased by 27.8% and 54.5% when compared to the traditional GRNN VVP strategy with fixed parameters utilizing only the historical ego-vehicle velocity dataset.Comment: 9 pages, 7 figure

The Effects of a Non-Ferroelectric Slab on the Polarization and the Susceptibility of the Ferroelectric Multilayer

The polarization and the susceptibility of a ferroelectric multilayer with a non-ferroelectric slab are investigated within the framework of transverse Ising model with a four-spin interaction term. The effect of the thickness and the position of the non-ferroelectric slab are investigated in this paper. We find that the increase of the thickness of the non-ferroelectric will decrease the polarization and the susceptibility of the film. If the position of the non-ferroelcetric slab shifts from the center of the film to the surface, the number of the peaks of the susceptibility will change. And a step-like polarization curve is found.Comment: 15 pages, 4 figure

Functional α7β2 Nicotinic Acetylcholine Receptors Expressed In Hippocampal Interneurons Exhibit High Sensitivity To Pathological Level Of Amyloid β Peptides

Background: β-amyloid (Aβ) accumulation is described as a hallmark of Alzheimer\u27s disease (AD). Aβ perturbs a number of synaptic components including nicotinic acetylcholine receptors containing α7 subunits (α7-nAChRs), which are abundantly expressed in the hippocampus and found on GABAergic interneurons. We have previously demonstrated the existence of a novel, heteromeric α7β2-nAChR in basal forebrain cholinergic neurons that exhibits high sensitivity to acute Aβ exposure. To extend our previous work, we evaluated the expression and pharmacology of α7β2-nAChRs in hippocampal interneurons and their sensitivity to Aβ.Results: GABAergic interneurons in the CA1 subregion of the hippocampus expressed functional α7β2-nAChRs, which were characterized by relatively slow whole-cell current kinetics, pharmacological sensitivity to dihydro-β-erythroidine (DHβE), a nAChR β2* subunit selective blocker, and α7 and β2 subunit interaction using immunoprecipitation assay. In addition, α7β2-nAChRs were sensitive to 1 nM oligomeric Aβ. Similar effects were observed in identified hippocampal interneurons prepared from GFP-GAD mice.Conclusion: These findings suggest that Aβ modulation of cholinergic signaling in hippocampal GABAergic interneurons via α7β2-nAChRs could be an early and critical event in Aβ-induced functional abnormalities of hippocampal function, which may be relevant to learning and memory deficits in AD. © 2012 Liu et al.; licensee BioMed Central Ltd

Indoor Particulate Matter Transfer in CNC Machining Workshop and The Influence of Ventilation Strategies—A Case Study

Particulate matter in Computer Numerical Control (CNC) machining workshop is harmful to workers’ health. This paper studies particulate matter transfer and the performance of various ventilation strategies in a CNC machining workshop. To obtain the boundary condition of the particle field, instruments were installed to obtain the particle size attenuation characteristics and source strength, respectively. The results show that the 99% cumulative mass concentration of particles is distributed within 1.5 μm, and the release rate of particles from the full enclosure. Next, the indoor flow field and particle field were simulated by numerical simulation with the measured boundary conditions. The working area’s age of air, particle concentration, and ventilation efficiency were compared between four displacement ventilation methods and one mixed ventilation method. The results show that the working area’s mean particle concentration and ventilation efficiency under longitudinal displacement ventilation is better than other methods. At the same time, the mean age of air is slightly worse. In addition, mixed ventilation can obtain lower mean age of air, but the particle concentration is higher in the working area. The bilateral longitudinal ventilation can be improved by placing axial circulation fans with vertical upward outlets in the center of the workshop