Microstructure and damage evolution of SiCf/PyC/SiC and SiCf/BN/SiC mini-composites: A synchrotron X-ray computed microtomography study

SiC_f/PyC/SiC and SiC_f/BN/SiC mini-composites comprising single tow SiC fibre-reinforced SiC with chemical vapor deposited PyC or BN interface layers are fabricated. The microstructure evolutions of the mini-composite samples as the oxidation temperature increases (oxidation at 1000, 1200, 1400, and 1600?°C in air for 2?h) are observed by scanning electron microscopy, energy dispersive spectrometry, and X-ray diffraction characterization methods. The damage evolution for each component of the as-fabricated SiC_f/SiC composites (SiC fibre, PyC/BN interface, SiC matrix, and mesophase) is mapped as a three-dimensional (3D) image and quantified with X-ray computed tomography. The mechanical performance of the composites is investigated via tensile tests.The results reveal that tensile failure occurs after the delamination and fibre pull-out in the SiC_f/PyC/SiC composites due to the volatilization of the PyC interface at high temperatures in the air environment. Meanwhile, the gaps between the fibres and matrix lead to rapid oxidation and crack propagation from the SiC matrix to SiC fibre, resulting in the failure of the SiC_f/PyC/SiC composites as the oxidation temperature increases to 1600?°C. On the other hand, the oxidation products of B₂O₃ molten compounds (reacted from the BN interface) fill up the fracture, cracks, and voids in the SiC matrix, providing excellent strength retention at elevated oxidation temperatures. Moreover, under the protection of B₂O₃, the SiC_f/BN/SiC mini-composites show a nearly intact microstructure of the SiC fibre, a low void growth rate from the matrix to fibre, and inhibition of new void formation and the SiO₂ grain growth from room to high temperatures. This work provides guidance for predicting the service life of SiC_f/PyC/SiC and SiC_f/BN/SiC composite materials, and is fundamental for establishing multiscale damage models on a local scale.     

Metabolism and biochemical effects of 3,3',4,4'-tetrachlorobiphenyl in pregnant and fetal rats

The metabolism and distribution of a single oral dose of 25 mumol 14C-labelled 3,3',4,4'-tetrachlorobiphenyl (14C-TCB) were investigated in pregnant female Wistar rats and their fetuses. TCB was administered on day 13 of gestation and the elimination was followed for 7 days. Non-pregnant rats were treated similarly for comparison. Fecal elimination of 14C-TCB derived radioactivity was significantly lower in pregnant rats than in non-pregnant rats. The major metabolite found in adult liver and plasma, placental tissue, whole fetuses and fetal plasma was 3,3',4',5-tetrachloro-4-biphenylol (4-OH-TCB). Tissue levels (liver, abdominal fat, skin, skeletal muscle, kidney and plasma) of 14C-TCB-derived radioactivity declined by 65-85% over a 7-day period following administration in the adult animals. However, 14C-TCB-derived radioactivity accumulated more than 100-fold in the fetuses over the same time period, and GC/MS analysis revealed that the fetal accumulation in radioactivity was due primarily to 4-OH-TCB, and not the parent compound. On day 20 of gestation, concentrations of 4-OH-TCB were 14 times greater in fetal plasma than maternal plasma. Treatment with 14C-TCB significantly reduced plasma thyroxine levels by at least 28% up to 7 days after administration in non-pregnant animals and up to 4 days after administration in pregnant rats (31% decrease). By 7 days after administration plasma thyroxine levels had returned to control levels in the TCB-treated pregnant rats. However, fetal plasma thyroxine levels were significantly decreased by 35% in fetuses from 14C-TCB-treated dams 7 days after TCB administration. Hepatic microsomal ethoxyresorufin-O-deethylase (EROD) activity was significantly induced in TCB-treated dams relative to controls at 4 and 7 days after administration, while no EROD activity was detected in hepatic microsomes from control or TCB treated fetal rats at day 20 of gestation. These data suggest that hydroxylated metabolites of polychlorinated biphenyls may play a role in the development toxicity of these compounds.     

SURF1, encoding a factor involved in the biogenesis of cytochrome c oxidase, is mutated in Leigh syndrome

A drug with cationic characteristics such as procaine can be conveyed in a Carbomer hydrogel in two different ways: (i) in the form of salt in solution in the aqueous phase, and (ii) in the base form salified with the same polymer. Introduction of the drug into the hydrogel with different concentrations of polymer produced, in both cases, a reduction in viscosity in relation to drug concentration. The gels with procaine salified with the polymer showed greater viscosity. The drug release rate, in general, diminished with the increase in polymer concentration. Nevertheless, when this concentration was maintained, there was no variation in release rate when the viscosity produced as a consequence of drug concentration was changed. Gels with procaine salified with the carboxyvinylic polymer had a faster release rate than those with procaine in the hydrochloride form dissolved in the aqueous phase. These results have also been confirmed by a simulated absorption test.     

Location-Dependent Lane-Changing Behavior for Arterial Road Traffic

Lane-changing behavior plays an important role in characterizing urban arterial road traffic dynamics. This paper investigates efficiency-driven and objective-driven motives for drivers to change lanes on arterial roads. The former motive is determined by the circumstances of the surrounding traffic flow, whereas the latter depends on position. A location-dependent lane changing model is then established by weighing the two motives for lane changing. Both continuous and discrete versions of the arterial traffic model are obtained using the LWR (Lighthill–Whitham–Richards) model with the two types of lane changing. Simulations show that the proposed model can reproduce macroscopic traffic phenomena such as spillover and a decrease in the concomitant departure flow, which is the reason for capacity loss. It is concluded that 1) there exists a critical condition under which there is no capacity loss and that 2) a different flow composition could result in a different capacity loss, which varies according to the flow direction. Hence, traffic management and control should take this loss into account.     

论高等教育大众化与农村人口转移

促进我国农村人口转移是当前解决“三农”问题、促进经济腾飞和社会进步的重大的战略之一。然而，农村人口素质低是制约着转移的“瓶颈”。高等教育要充分发挥提高农村人口素质，促进农村人口转移的积极作用，应逐渐完善大众化高等教育体系。具体而言，可采取以下改革举措：高等教育资源向农村地区倾斜；大力发展高等职业教育；调整、优化学科结构；发展农村高等教育等。     

Phase Separation Derived Core/Shell Structured Cu11V6O26/V2O5 Microspheres: First Synthesis and Excellent Lithium‐Ion Anode Performance with Outstanding Capacity Self‐Restoration

Novel amorphous vanadium oxide coated copper vanadium oxide (Cu₁₁V₆O₂₆/V₂O₅) microspheres with 3D hierarchical architecture have been successfully prepared via a microwave‐assisted solution method and subsequent annealing induced phase separation process. Pure Cu₁₁V₆O₂₆ microspheres without V₂O₅ coating are also obtained by an H₂O₂ solution dissolving treatment. When evaluated as an anode material for lithium‐ion batteries (LIBs), the as‐synthesized hybrid exhibits large reversible capacity, excellent rate capability, and outstanding capacity self‐recovery. Under the condition of high current density of 1 A g^?1, the 3D hierarchical Cu₁₁V₆O₂₆/V₂O₅ hybrid maintains a reversible capacity of ≈1110 mA h g^?1. Combined electrochemical analysis and high‐resolution transmission electron microscopy observation during cycling reveals that the amorphous V₂O₅ coating plays an important role on enhancing the electrochemical performances and capacity self‐recovery, which provides an active amorphous protective layer and abundant grain interfaces for efficient inserting and extracting of Li‐ion. As a result, this new copper vanadium oxide hybrid is proposed as a promising anode material for LIBs.     

Maximum entropy models and subjective interestingness: an application to tiles in binary databases

Recent research has highlighted the practical benefits of subjective interestingness measures, which quantify the novelty or unexpectedness of a pattern when contrasted with any prior information of the data miner (Silberschatz and Tuzhilin, Proceedings of the 1st ACM SIGKDD international conference on Knowledge discovery and data mining (KDD95), 1995; Geng and Hamilton, ACM Comput Surv 38(3):9, 2006). A key challenge here is the formalization of this prior information in a way that lends itself to the definition of a subjective interestingness measure that is both meaningful and practical. In this paper, we outline a general strategy of how this could be achieved, before working out the details for a use case that is important in its own right. Our general strategy is based on considering prior information as constraints on a probabilistic model representing the uncertainty about the data. More specifically, we represent the prior information by the maximum entropy (MaxEnt) distribution subject to these constraints. We briefly outline various measures that could subsequently be used to contrast patterns with this MaxEnt model, thus quantifying their subjective interestingness. We demonstrate this strategy for rectangular databases with knowledge of the row and column sums. This situation has been considered before using computation intensive approaches based on swap randomizations, allowing for the computation of empirical p-values as interestingness measures (Gionis et al., ACM Trans Knowl Discov Data 1(3):14, 2007). We show how the MaxEnt model can be computed remarkably efficiently in this situation, and how it can be used for the same purpose as swap randomizations but computationally more efficiently. More importantly, being an explicitly represented distribution, the MaxEnt model can additionally be used to define analytically computable interestingness measures, as we demonstrate for tiles (Geerts et al., Proceedings of the 7th international conference on Discovery science (DS04), 2004) in binary databases.     

Temporal kernel CCA and its application in multimodal neuronal data analysis

Data recorded from multiple sources sometimes exhibit non-instantaneous couplings. For simple data sets, cross-correlograms may reveal the coupling dynamics. But when dealing with high-dimensional multivariate data there is no such measure as the cross-correlogram. We propose a simple algorithm based on Kernel Canonical Correlation Analysis (kCCA) that computes a multivariate temporal filter which links one data modality to another one. The filters can be used to compute a multivariate extension of the cross-correlogram, the canonical correlogram, between data sources that have different dimensionalities and temporal resolutions. The canonical correlogram reflects the coupling dynamics between the two sources. The temporal filter reveals which features in the data give rise to these couplings and when they do so. We present results from simulations and neuroscientific experiments showing that tkCCA yields easily interpretable temporal filters and correlograms. In the experiments, we simultaneously performed electrode recordings and functional magnetic resonance imaging (fMRI) in primary visual cortex of the non-human primate. While electrode recordings reflect brain activity directly, fMRI provides only an indirect view of neural activity via the Blood Oxygen Level Dependent (BOLD) response. Thus it is crucial for our understanding and the interpretation of fMRI signals in general to relate them to direct measures of neural activity acquired with electrodes. The results computed by tkCCA confirm recent models of the hemodynamic response to neural activity and allow for a more detailed analysis of neurovascular coupling dynamics.