Phase separation behavior and morphology development of phenolic resin/PMMA/hexamethylenetetrarnine blends

Summary In order to obtain materials with nanopores which will be applicable for many fields, the structures of the cured blends of phenolic resin (PhN), poly(methyl methacrylate) (PMMA) and curing agent were studied. After PMMA was extracted from cured blends, the structures of cured phenolic resins were observed with SEM. As a results, it was found that nanosized continuous pore structures were formed in extremely wide composition region if curing temperature was high.     

Ni含量对TiNi形状记忆合金相变行为的影响

用示差扫描热分析仪和光学显微镜系统研究了Ｎｉ含量对ＴｉＮｉ形状记忆合金Ｒ相和Ｍ相相变温度，相变热，热滞的影响。结果表明：在加热和冷却过程中，Ｔｉ－３３．３％Ｎｉ和Ｔｉ－７５．０％Ｎｉ不发生相变；ＴＭ，ΔＭ，ΔＨＭ和ΔＨＲ是Ｎｉ是含量的函数，ＴＲ和ΔＲ基本为一定值，与Ｎｉ含量有关。     

Analysis of electro‐optical properties of polymer‐stabilized OCB and the application to TFT‐LCDs

Abstract— A 9‐in. full‐color polymer‐stabilized OCB TFT‐LCD with stable bend alignment in the absence of an electric field was developed. The condition of the polymer stabilization, the characteristics of UV‐curable monomers, and their influence on the configurations of the polymer network in the cell were studied. Possible models of the configuration were proposed and their relationship to the electro‐optical properties was analyzed using a novel simulation method considering the distribution of anchoring effects from both alignment surfaces and the polymer network. It was suggested that a good performance such as high contrast ratio and fast response could be expected in the polymer network originating from newly developed monomers composed of multifunctional LC acrylates due to a relatively weak‐anchoring effect and presumably its localization near the alignment surfaces. By using the newly developed monomers under the optimized polymer‐stabilizing process, a high contrast ratio of 250:1 and fast response nearly equal to that of a conventional OCB cell were achieved.     

Learning type PID control system using input dependence reinforcement scheme

PID control has widely used in the field of process control and a lot of methods have been used to design PID parameters. When the characteristic values of a controlled object are changed due to a change over the years or disturbance, the skilled operators observe the feature of the controlled responses and adjust the PID parameters using their knowledge and know-how, and a lot of labors are required to do it. In this research, we design a learning type PID control system using the stochastic automaton with learning function, namely learning automaton, which can autonomously adjust the control parameters updating the state transition probability using relative amount of controlled error. We show the effectiveness of the proposed learning type PID control system by simulations. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

An adaptive associative memory system based on autonomous reaction between image memories

To construct a “thinking-like” processing system, a new architecture of an adaptive associative memory system is proposed. This memory system treats “images” as basic units of information, and adapts to the environment of the external world by means of autonomous reactions between the images. The images do not have to be clear, distinct symbols or patterns; they can be ambiguous, indistinct symbols or patterns as well. This memory system is a kind of neural network made up of nodes and links called a localist spreading activation network. Each node holds one image in a localist manner. Images in high-activity nodes interact autonomously and generate new images and links. By this reaction between images, various forms of images are generated automatically under constraints of links with adjacent nodes. In this system, three simple image reaction operations are defined. Each operation generates a new image by combining pseudofigures or features and links of two images. This work was presented, in part, at the Fourth International Symposium on Artificial Life and Robotics, Oita, Japan, January 19–22, 1999     

Resource assessment of copper deposits in China

Copper-bearing deposits of China are statistically analyzed in terms of ore grade, metal amount and ore tonnage. Each of grade and metal amount shows more or less a lognormal distribution. Analysis gives 10 copper metallogenic districts, each having specific densities of deposit numbers and copper reserves larger than 3. Based on the ratio of copper in ore value (R _Cu), Chinese copper deposits are classified into two groups: mainly copper-producing deposits (MC: R _Cu⩾0.5) and accessorily copper-producing deposits (AC: R _Cu<0.5). The grade-tonnage relation of MC deposits can be combined by two exponential functions approximating high grade (>3.0%) and low grade (<2.0%) parts. The critical copper grade, which is obtained from the low grade part of the relation, is 0.34%. Chinese copper resources are concluded to become pessimistic, because some mines are working with grades close to this critical value. Taking account of the fact that many copper deposits are actually polymetallic, Cu-equivalent grades, which are converted from ratios of metal prices to the copper price, are also introduced. The critical Cu-equivalent grade of MC deposits (0.43%) also suggests that Chinese copper resources are pessimistic.     

Surface analysis of β-FeSi2 layer epitaxially grown on Si(100)

The epitaxial growth process of β-FeSi₂ on Si(100) surface under ultrahigh vacuum condition has been studied by low energy electron diffraction (LEED) and low energy ion scattering spectroscopy (LEIS). The LEED pattern of Si (100)-2×1 changes into amorphous structure with Fe deposition of about 10 Å at room temperature. With annealing at 540 °C, the LEED pattern shows 2×2 structure corresponding to the formation of the epitaxial β-FeSi₂ (100) template layer. The α-scan in Li⁺-LEIS and X-ray diffraction (XRD) study strongly suggest that the topmost surface of the 2×2 structure is terminated by Si atoms. By XRD, it is shown that the β-FeSi₂ develops with characteristic orientation even if iron reactant is deposited onto the template surface.     

Elevated Alpha 1(I) to Alpha 2(I) Collagen Ratio in Dermal Fibroblasts Possibly Contributes to Fibrosis in Systemic Sclerosis

Systemic sclerosis (SSc) is characterized by excessive collagen deposition in the skin and internal organs. Activated fibroblasts are the key effector cells for the overproduction of type I collagen, which comprises the α1(I) and α2(I) chains encoded by COL1A1 and COL1A2, respectively. In this study, we examined the expression patterns of α1(I) and α2(I) collagen in SSc fibroblasts, as well as their co-regulation with each other. The relative expression ratio of COL1A1 to COL1A2 in SSc fibroblasts was significantly higher than that in control fibroblasts. The same result was observed for type I collagen protein levels, indicating that α2(I) collagen is more elevated than α2(I) collagen. Inhibition or overexpression of α1(I) collagen in control fibroblasts affected the α2(I) collagen levels, suggesting that α1(I) collagen might act as an upstream regulator of α2(I) collagen. The local injection of COL1A1 small interfering RNA in a bleomycin-induced SSc mouse model was found to attenuate skin fibrosis. Overall, our data indicate that α2(I) collagen is a potent regulator of type I collagen in SSc; further investigations of the overall regulatory mechanisms of type I collagen may help understand the aberrant collagen metabolism in SSc.     

Association of Ligamentum Flavum Hypertrophy with Adolescent Idiopathic Scoliosis Progression—Comparative Microarray Gene Expression Analysis

The role of the ligamentum flavum (LF) in the pathogenesis of adolescent idiopathic scoliosis (AIS) is not well understood. Using magnetic resonance imaging (MRI), we investigated the degrees of LF hypertrophy in 18 patients without scoliosis and on the convex and concave sides of the apex of the curvature in 22 patients with AIS. Next, gene expression was compared among neutral vertebral LF and LF on the convex and concave sides of the apex of the curvature in patients with AIS. Histological and microarray analyses of the LF were compared among neutral vertebrae (control) and the LF on the apex of the curvatures. The mean area of LF in the without scoliosis, apical concave, and convex with scoliosis groups was 10.5, 13.5, and 20.3 mm², respectively. There were significant differences among the three groups (p < 0.05). Histological analysis showed that the ratio of fibers (Collagen/Elastic) was significantly increased on the convex side compared to the concave side (p < 0.05). Microarray analysis showed that ERC2 and MAFB showed significantly increased gene expression on the convex side compared with those of the concave side and the neutral vertebral LF cells. These genes were significantly associated with increased expression of collagen by LF cells (p < 0.05). LF hypertrophy was identified in scoliosis patients, and the convex side was significantly more hypertrophic than that of the concave side. ERC2 and MAFB genes were associated with LF hypertrophy in patients with AIS. These phenomena are likely to be associated with the progression of scoliosis.     

Application of Near-Infrared Spectroscopy for Evaluation of Drying Stress on Lumber Surface: A Comparison of Artificial Neural Networks and Partial Least Squares Regression

This study aimed to examine the feasibility of evaluating the stress level at the surface of lumber during drying using near-infrared (NIR) spectroscopy combined with artificial neural networks (ANNs). Sugi (Cryptomeria japonica D. Don) lumber with an initial moisture content ranging from 41.1 to 85.8% was dried using a commercial drying schedule. An ANN model for predicting surface-released strain (SRS) was developed based on NIR spectra collected from the lumber during drying. The predictive ability of the ANN model was compared with a partial least squares (PLS) regression model.

The ANN model showed good correlation between laboratory-measured SRS and predicted SRS with an R ² of 0.79, a root mean square error of prediction (RMSEP) of 0.0009, and a ratio of performance to deviation (RPD) of 1.81. The PLS regression model gave a lower R ² of 0.69, a higher RMSEP of 0.0010, and a lower RPD of 1.38 than the ANN model, suggesting that the predictive performance of the ANN model was superior to the PLS regression model. The SRS evolution during drying as predicted by the models showed a similar trend to the laboratory-measured one. The predicted elapsed times to reach maximum tensile SRS and stress reversal roughly coincided with the laboratory-measured times. These results suggest that NIR spectroscopy combined with multivariate analysis has the potential to predict the drying stress level on the lumber surface and the critical periods during drying, such as the points of maximum tensile stress and stress reversal.