强化质量意识 提高市场竞争力

介绍了企业在面临国际陶瓷市场竞争激烈的形势下，努力转变发展思路，拓宽市场，强化质量意识。根据市场变化，生产适销对路搞档优质陶瓷产品，增强产品的市场能力，提高了企业的经济效益。     

气相色谱法测定3-氯-1-丙醇

以填充柱气相色谱对 3 氯 1 丙醇进行了分析研究 ,方法变异系数 0 .5 % ,回收率99.5 0 %～ 10 0 .6 7%     

Ultrasound as a Tool to Synthesize Nano-Sized Silica–Alumina Catalysts with Controlled Mesoporous Distribution by a Novel Sol–Gel Process

A novel sol–gel process is used to synthesize mesoporous silica–alumina catalysts with controlled pore size distribution without using templates or pore-regulating agents. The nitrogen sorption analysis shows that the synthesized materials have high specific surface area in the range 587–692 m²/g and similar mesoporous distribution within 2–11 nm. Ultrasound is applied to prepare precursor silica–alumina sol with narrow particle diameter distribution. By calculation, it is found that ultrasonic treatment is able to provide 22.94 kJ/mol energy, which is just in accordance with the weak bond's bonding energy. Based on the calculation result, it is proposed that the role of ultrasonic treatment followed by acid peptization is to provide energy to break down the weak bonds. After gelation, the regular and close packing of similar-sized sol particles is capable of formation of controlled-sized interstices which are the precursors of mesopores. Solid-state ²⁷Al MAS NMR and TEM are used to characterize the samples' structure and particle morphology. They show that most of the aluminum is located in the tetrahedral position in the present materials. According to TEM results, it is shown that the synthesized materials have spherical particles with size of about 15 nm.     

以废弃的耐火材料、高铝瓷、催化剂等生产耐磨陶瓷

从技术、经济、生态、政策等角度，对采用氧化铝和硅酸铝质工业废料制取耐磨陶瓷作了全面、系统的分析研究，论证了废渣制瓷技术上的可行性，阐明了经济上和生态上的优越性，提出了解决具体问题的办法。     

大掺量粉煤灰高性能混凝土的研究

本文从高分散性表面活性剂显著影响粉煤灰的形态效应而大幅降低混凝土用水量的角度出发,利用复合激发剂激发粉煤灰的火山灰效应,结合粉煤灰自身的微集料效应提高混凝土强度的技术手段,探讨了大掺量粉煤灰在混凝土中的应用,分析了高分散性表面活性剂与复合激发剂的组合对大掺量粉煤灰混凝土的作用机理。     

Image super-resolution based on multi-space sparse representation

Sparse representation provides a new method of generating a super-resolution image from a single low resolution input image. An over-complete base for sparse representation is an essential part of such methods. However, discovering the over-complete base with efficient representation from a large amount of image patches is a difficult problem. In this paper, we propose a super-resolution construction based on multi-space sparse representation to efficiently solve the problem. In the representation, image patches are decomposed into a structure component and a texture component represented by the over-complete bases of their own spaces so that their high-level features can be captured by the bases. In the implementation, a prior knowledge about low resolution images generation is combined to the typical base construction for high construction quality. Experiment results demonstrate that the proposed method significantly improves the PSNR, SSIM and visual quality of reconstructed high-resolution image.     

Optimal entropy-constrained non-uniform scalar quantizer design for low bit-rate pixel domain DVC

In this paper, an optimal entropy-constrained non-uniform scalar quantizer is proposed for the pixel domain DVC. The uniform quantizer is efficient for the hybrid video coding since the residual signals conforming to a single-variance Laplacian distribution. However, the uniform quantizer is not optimal for pixel domain distributed video coding (DVC). This is because the uniform quantizer is not adaptive to the joint distribution of the source and the SI, especially for low level quantization. The signal distribution of pixel domain DVC conforms to the mixture model with multi-variance. The optimal non-uniform quantizer is designed according to the joint distribution, the error between the source and the SI can be decreased. As a result, the bit rate can be saved and the video quality won’t sacrifice too much. Accordingly, a better R-D trade-off can be achieved. First, the quantization level is fixed and the optimal RD trade-off is achieved by using a Lagrangian function J(Q). The rate and distortion components is designed based on P(Y|Q). The conditional probability density function of SI Y depend on quantization partitions Q, P(Y|Q), is approximated by a Guassian mixture model at encocder. Since the SI can not be accessed at encoder, an estimation of P(Y|Q) based on the distribution of the source is proposed. Next, J(Q) is optimized by an iterative Lloyd-Max algorithm with a novel quantization partition updating algorithm. To guarantee the convergence of J(Q), the monotonicity of the interval in which the endpoints of the quantizer lie must be satisfied. Then, a quantizer partition updating algorithm which considers the extreme points of the histogram of the source is proposed. Consequently, the entropy-constrained optimal non-uniform quantization partitions are derived and a better RD trade-off is achieved by applying them. Experiment results show that the proposed scheme can improve the performance by 0.5 dB averagely compared to the uniform scalar quantization.     

Know by a handful the whole sack: efficient sampling for top-k influential user identification in large graphs

Influence Maximization aims to find the top-K influential individuals to maximize the influence spread within a social network, which remains an important yet challenging problem. Most existing greedy algorithms mainly focus on computing the exact influence spread, leading to low computational efficiency and limiting their application to real-world social networks. While in this paper we show that through supervised sampling, we can efficiently estimate the influence spread at only negligible cost of precision, thus significantly reducing the execution time. Motivated by this, we propose ESMCE, a power-law exponent supervised Monte Carlo estimation method. In particular, ESMCE exploits the power-law exponent of the social network to guide the sampling, and employs multiple iterative steps to guarantee the estimation accuracy. Moreover, ESMCE shows excellent scalability and well suits large-scale social networks. Extensive experiments on six real-world social networks demonstrate that, compared with state-of-the-art greedy algorithms, ESMCE is able to achieve almost two orders of magnitude speedup in execution time with only negligible error (2.21 % on average) in influence spread.     

管材超声波分层缺陷检测中盲区的构成探析

管材超声波分层检测作为控制产品质量的关键步骤,必须引起相关从业人员的重视,特别是要重点分析分层缺陷检测中盲区的构成原因和分布特征。只有这样,才能切实保证检测结果的准确性,更好地控制管材质量。通过对超声波分层缺陷检测的重要性进行阐释,分析了其中盲区的构成和分布等问题。     

壳聚糖固定化脲酶生物传感器选择性测定铜离子

基于重金属对脲酶的抑制作用,研制了用于测定铜离子的生物传感器。该生物传感器的制备以壳聚糖为载体,将脲酶固定于pH电极表面。由于壳聚糖对Cu2+的富集,该生物传感器展现出高灵敏度。在样品溶液中加入5 mmol/L NaI,可以消除Hg2+和Ag+的干扰,从而实现Cu2+的选择性检测。在0.005～0.5μg/mL的浓度范围内,脲酶活性的抑制率与Cu2+浓度的对数呈良好的线性响应关系,其检出限为0.002μg/mL。将使用后的生物传感器浸泡于0.5 mmol/L的EDTA溶液再生5 min,被Cu2+抑制的脲酶的活性可以得到恢复。