Synthesis of amino acid-containing polyacids and their application in self-cured glass-ionomer cement

Six methacrylate or acrylate derivatives of natural amino acids were synthesized and characterized. Based upon these monomers, six terpolymers [poly(acrylic) acid-co-itaconic acid-co-amino acid] were prepared and characterized. The synthesized polymers were used to formulate glass-ionomer cements (GICs) using Fuji II glass filler. The effects of the molecular weight (MW) and powder/liquid (P/L) ratio were evaluated. Scanning electron microscopy (SEM) was used to examine the fracture surfaces of the selected cement specimens. Results show that all the amino acid modified GICs exhibited higher compressive strengths (CS, 193-236 MPa) and much higher flexural strengths (FS, 55-71 MPa) as compared to commercial Fuji II GIC (191 in CS and 16 in FS). Both MW and P/L ratio affected the strength of the formed cement. It was important to find the optimal MW and P/L ratio to obtain the highest FS. In this study, optimized MW (number average) of the polyacids and P/L ratio were around 50,000 and 2.7/1, respectively. The microstructures of the fracture surfaces helped to explain the strength differences among the materials tested in the study. SEM analysis suggests that more integrated microstructures and fewer defects can lead to higher FS.     

A Noise-Aware Real-Time Processing Approach for Electroencephalogram Signal Classification

Electroencephalogram (EEG) signal processing has emerged as a critical problem for biometric applications due to its real-time requirement. While compressive sensing is an efficient method for signal compression, its application in EEG signal processing is limited due to its noise unawareness during transmission and time-consuming reconstruction procedure. In this paper, we propose a noise-aware sparse Bayesian learning approach with block structure (NA-BSBL) to achieve higher efficiency on data compression, reconstruction and classification. By applying novel structure for parameter and introducing the Mahalanobis Distance, our approach achieves an almost 20% reconstruction performance lift and 10% accuracy lift under noise condition. For further application of reconstructed EEG signal, we extract both the spatial and frequency domain features for classification. Experimental results show that the proposed approach can achieve 94% classification accuracy with 16% speed up compared with the conventional approach.     

Compressively sampled light field reconstruction using orthogonal frequency selection and refinement

This paper considers the compressive sensing framework as a way of overcoming the spatio-angular trade-off inherent to light field acquisition devices. We present a novel method to reconstruct a full 4D light field from a sparse set of data samples or measurements. The approach relies on the assumption that sparse models in the 4D Fourier domain can efficiently represent light fields. The proposed algorithm reconstructs light fields by selecting the frequencies of the Fourier basis functions that best approximate the available samples in 4D hyper-blocks. The performance of the reconstruction algorithm is further improved by enforcing orthogonality of the approximation residue at each iteration, i.e. for each selected basis function. Since sparsity is better preserved in the continuous Fourier domain, we propose to refine the selected frequencies by searching for neighboring non-integer frequency values. Experiments show that the proposed algorithm yields performance improvements of more than 1 dB compared to state-of-the-art compressive light field reconstruction methods. The frequency refinement step also significantly enhances the visual quality of reconstruction results of our method by a 1.8 dB average.     

Strain rate effects on compressive behavior of covalently bonded CNT networks

In this study, strain rate effects on the compressive mechanical properties of randomly structured carbon nanotube (CNT) networks were examined. For this purpose, three-dimensional atomistic models of CNT networks with covalently-bonded junctions were generated. After that, molecular dynamics (MD) simulations of compressive loading were performed at five different strain rates to investigate the basic deformation characteristic mechanisms of CNT networks and determine the effect of strain rate on stress–strain curves. The simulation results showed that the strain rate of compressive loading increases, so that a higher resistance of specimens to deformation is observed. Furthermore, the local deformation characteristics of CNT segments, which are mainly driven by bending and buckling modes, and their prevalence are strongly affected by the deformation rate. It was also observed that CNT networks have superior features to metal foams such as metal matrix syntactic foams (MMSFs) and porous sintered fiber metals (PSFMs) in terms of energy absorbing capabilities.     

Relation between interfacial shear strength and compressive strength of carbon fiber/epoxy resin composite strands

The mechanism with which the fiber-matrix interfacial strength exerts its influence on the compressive strength of fiber reinforced composites has been studied by measuring the axial compressive strength of carbon fiber/epoxy resin unidirectional composite strands having different levels of interfacial shear strength. The composite strands are used for experiments in order to investigate the compressive strength which is not affected by the delamination taking place at a weak interlayer of the laminated composites. The interfacial strength is varied by applying various degrees of liquid-phase surface treatment to the fibers. The efficiency of the compressive strength of the fibers utilized in the strength of the composite strands is estimated by measuring the compressive strength of the single carbon filaments with a micro-compression test. The compressive strength of the composite strands does not increase monotonically with increasing interfacial shear strength but showes lower values at higher interfacial shear strengths. With increasing interfacial shear strength, the suppression of the interfacial failure in the misaligned fiber region increases the compressive strength, while at higher interfacial shear strengths, the enhancement of the crack sensitivity decreases the compressive strength.     

确定性矩阵可分离压缩成像

针对可分离压缩传感使用的可分离随机正交矩阵在处理大尺度图像等高维信号感知时难度太大或成本过高的问题,引入确定性测量矩阵,提出确定性矩阵可分离压缩传感,可将如托普利兹矩阵及循环矩阵等具有确定性结构的矩阵作为可分离压缩传感的左、右可分离矩阵.该方案可以降低独立元素的数目,从而显著降低前端物理实现的难度与成本.数值模拟实验分别评估了该方法在不同采样率及不同图像尺寸下的压缩重建性能,结果表明该方法在独立元素非常少的情形下得到与原随机正交矩阵相近的重建质量,证明了其可行性.     

Single image non-uniformity correction using compressive sensing

A non-uniformity correction (NUC) method for an infrared focal plane array imaging system was proposed. The algorithm, based on compressive sensing (CS) of single image, overcame the disadvantages of “ghost artifacts” and bulk calculating costs in traditional NUC algorithms. A point-sampling matrix was designed to validate the measurements of CS on the time domain. The measurements were corrected using the midway infrared equalization algorithm, and the missing pixels were solved with the regularized orthogonal matching pursuit algorithm. Experimental results showed that the proposed method can reconstruct the entire image with only 25% pixels. A small difference was found between the correction results using 100% pixels and the reconstruction results using 40% pixels. Evaluation of the proposed method on the basis of the root-mean-square error, peak signal-to-noise ratio, and roughness index (ρ) proved the method to be robust and highly applicable.     

Temperature-dependent ratcheting of PTFE gaskets under cyclic compressive loads with small stress amplitude

Uniaxial stress-controlled ratcheting experiments on PTFE gaskets under cyclic compressive loads with small stress amplitude were performed. The effect of temperature on the deformation behavior was considered. Results showed that the compressive modulus decreases rapidly when the temperature increases from 100 °C to 200 °C. Compressive ratcheting deformation with cycles increase significantly with the increases of temperature. The ratcheting deformations at 100 °C, 150 °C and 200 °C are nearly two, three and five times that at room temperature, respectively. Most of ratcheting deformation mainly occurs during the first 20 cycles because the subsequent ratcheting rate and strain range are small and much less than those in the previous cycles. The accumulated deformation under cyclic loads with small stress amplitude is relatively approach to the static compressive creep with the same peak stress. Therefore, the accumulated deformation with time of PTFE gaskets obtained by cyclic compression with small stress amplitude can be estimated by the corresponding static creep deformation with good accuracy under the approximate stress rate and the same temperature, especially at room temperature.     

Preservation of beech and spruce wood by allyl alcohol-based copolymers

Allyl alcohol (AA), acrylonitrile (AN), methyl methacrylate (MMA), monomers and monomer mixtures AA+AN, AA+MMA were used to conserve and consolidate Beech and Spruce. After impregnation, copolymerisation and polymerisation were accomplished by gamma irradiation. The fine structure of wood+polymer(copolymer) composites was investigated by Scanning Electron Microscopy (SEM). It was observed that copolymer obtained from AA+MMA monomer mixture showed the optimum compatibility. The compressional strength and Brinell Hardness Numbers determined for untreated and treated wood samples indicated that the mechanical strength of wood+copolymer composites was increased. It was found that the mechanical strength of the wood samples containing the AA+MMA copolymer was higher than the others. In the presence of P(AA/MMA), at highest conversion, the compressive strength perpendicular to the fibres in Beech and Spruce increased approximately 100 times. The water uptake capacity of wood+copolymer composites was observed to decrease by more than 50% relative to the original samples, and biodegradation did not take place.