Enhanced Physical and Mechanical Properties of Nitrile-Butadiene Rubber Composites with N-Cetylpyridinium Bromide-Carbon Black

The physical and mechanical properties of nitrile–butadiene rubber (NBR) composites with N-cetylpyridinium bromide-carbon black (CPB-CB) were investigated. Addition of 5 parts per hundred rubber (phr) of CPB-CB into NBR improved the tensile strength by 124%, vulcanization rate by 41%, shore hardness by 15%, and decreased the volumetric wear by 7% compared to those of the base rubber-CB composite.     

Effects of a High-Molecular-Weight Polysaccharides Isolated from Korean Persimmon on the Antioxidant,Anti-Inflammatory,and Antiwrinkle Activity

Persimmon (Diospyros kaki), a familiar and widespread fruit worldwide, is known to exhibit several physiological effects because of the presence of pharmacologically active compounds called phytochemicals. However, its high-molecular-weight compounds, particularly polysaccharides, have not been extensively studied. In this study, D. kaki extract (DK) was fractionated into low- and high-molecular-weight fractions (DK-L and DK-H, respectively) through ethanol fractionation, and their effects on antioxidant, anti-inflammatory, and antiwrinkle activities were investigated by an in vitro system. DK-H contained significantly higher contents of neutral sugar, uronic acid, and polyphenols compared to DK and DK-L. Furthermore, DK-H exhibited significantly improved pharmacological activities, such as antioxidant, anti-inflammatory, and antiwrinkle properties, compared to those of DK and DK-L, demonstrating that DK-H may play an important role in mediating the beneficial effects of persimmon. Sugar composition analysis and molecular characterization indicated that DK-H consisted of a galacturonic acid (GalA)-rich polysaccharide with a molecular weight of >345 kDa that mainly comprised GalA and small amounts of neutral sugar and polyphenol residues. These results suggest that the bioactive fraction DK-H is likely to be a GalA-rich pectic polysaccharide containing a small number of polyphenol residues, which may be a novel candidate in the pharmaceutical and cosmeceutical industries.     

MOFs/水凝胶复合材料的制备及其应用研究

金属有机框架(MOFs)具有大量的孔隙结构和活性位点,在气体吸附、催化、医疗等领域均发挥了巨大的作用。MOFs是晶体粉末,具有脆性较大、在水中易分解和不易回收等缺点,从而限制了其应用。通过MOFs与柔性高分子的复合,特别是与水凝胶的复合,极大地改善了复合材料的柔顺性、可回收和可加工性等特性,进一步拓宽了MOFs的应用领域。本文详细阐述了基于水凝胶MOFs原位生成法、MOFs /水凝胶同时生成法和水凝胶包裹MOFs法等三种不同方法制备MOFs/水凝胶复合材料的研究进展,并对上述三种制备方法的特点及其产物特征进行了总结,进一步归纳了复合材料在生物医药、催化、废水处理和气体吸附等领域的应用。最后,对MOFs/水凝胶复合材料制备方法的改进和复合材料应用前景进行了深入讨论和展望。     

甚高频激发容性耦合氩等离子体的电子能量分布函数的演变

甚高频激发的容性耦合等离子体由于离子通量和能量的相对独立可控而受到人们的关注. 本文采用朗缪尔探针诊断技术测量了40.68 MHz激发的容性耦合Ar等离子体的特性(如电子能量概率分布、电子温度和密度等)随宏观参量的演变情况. 实验结果表明, 电子能量概率分布随着气压的增加从双麦克斯韦分布逐步转变为单麦克斯韦分布并最终演变为Druyvesteyn分布, 而射频激发功率的增加促进了低能电子布居数的增强; 在从等离子体放电中心移向边界的过程中, 低能电子的布居数显著下降, 而高能电子的布居则有所上升; 放电极板间距的变化直接导致了等离子体中电子加热模式的转变. 另外, 我们也对等离子体中的高低能电子密度和温度的分配情况进行了讨论.     

聚焦形貌恢复方法模型设计

采用基于拉普拉斯算符聚焦形貌恢复方法,提出了模拟目标深度测量的数值模型。数值模拟的核心是基于通过几何光学预测的理想图像的卷积与透镜广义孔径函数的多色点扩散函数,即用聚焦误差替代抛物线圆柱形貌或高斯函数。该模型可以使用基于聚焦形貌恢复方法的传感器真实组件参数、光源光谱、光学系统离差、相机的光谱灵敏度。提出了光学系统离差（消球差、消色差、色差）对确定目标表面形貌的精确度和可靠性的影响。结果表明,该模型可以有效提高实验效率,缩短时滞,降低成本。     

Scale-space point spread function based framework to boost infrared target detection algorithms

Small target detection is one of the major concern in the development of infrared surveillance systems. Detection algorithms based on Gaussian target modeling have attracted most attention from researchers in this field. However, the lack of accurate target modeling limits the performance of this type of infrared small target detection algorithms. In this paper, signal to clutter ratio (SCR) improvement mechanism based on the matched filter is described in detail and effect of Point Spread Function (PSF) on the intensity and spatial distribution of the target pixels is clarified comprehensively. In the following, a new parametric model for small infrared targets is developed based on the PSF of imaging system which can be considered as a matched filter. Based on this model, a new framework to boost model-based infrared target detection algorithms is presented. In order to show the performance of this new framework, the proposed model is adopted in Laplacian scale-space algorithms which is a well-known algorithm in the small infrared target detection field. Simulation results show that the proposed framework has better detection performance in comparison with the Gaussian one and improves the overall performance of IRST system. By analyzing the performance of the proposed algorithm based on this new framework in a quantitative manner, this new framework shows at least 20% improvement in the output SCR values in comparison with Laplacian of Gaussian (LoG) algorithm.     

Infrared/laser multi-sensor fusion and tracking based on the multi-scale model

The state estimation problem of targets detected by infrared/laser composite detection system with different sampling rates was studied in this paper. An effective state estimation algorithm based on data fusion is presented. Because sampling rate of infrared detection system is much higher than that of the laser detection system, the theory of multi-scale analysis is used to establish multi-scale model in this algorithm. At the fine scale, angle information provided by infrared detection system is used to estimate the target state through the unscented Kalman filter. It makes full use of the high frequency characteristic of infrared detection system to improve target state estimation accuracy. At the coarse scale, due to the sampling ratio of infrared and laser detection systems is an integer multiple, the angle information can be fused directly with the distance information of laser detection system to determine the target location. The fused information is served as observation, while the converted measurement Kalman filter (CMKF) is used to estimate the target state, which greatly reduces the complexity of filtering process and gets the optimal fusion estimation. The simulation results of tracking a target in 3-D space by infrared and laser detection systems demonstrate that the proposed algorithm in this paper is efficient and can obtain better performance than traditional algorithm.     

Multiple mobility edges in a 1D Aubry chain with Hubbard interaction in presence of electric field: Controlled electron transport

Electronic behavior of a 1D Aubry chain with Hubbard interaction is critically analyzed in presence of electric field. Multiple energy bands are generated as a result of Hubbard correlation and Aubry potential, and, within these bands localized states are developed under the application of electric field. Within a tight-binding framework we compute electronic transmission probability and average density of states using Green's function approach where the interaction parameter is treated under Hartree–Fock mean field scheme. From our analysis we find that selective transmission can be obtained by tuning injecting electron energy, and thus, the present model can be utilized as a controlled switching device.     

Correcting saturation effects of the arterial input function in dynamic susceptibility contrast-enhanced MRI: a Monte Carlo simulation

To prevent systematic errors in quantitative brain perfusion studies using dynamic susceptibility contrast-enhanced magnetic resonance imaging (DSC-MRI), a reliable determination of the arterial input function (AIF) is essential. We propose a novel algorithm for correcting distortions of the AIF caused by saturation of the peak amplitude and discuss its relevance for longitudinal studies. The algorithm is based on the assumption that the AIF can be separated into a reliable part at low contrast agent concentrations and an unreliable part at high concentrations. This unreliable part is reconstructed, applying a theoretical framework based on a transport-diffusion theory and using the bolus-shape in the tissue. A validation of the correction scheme is tested by a Monte Carlo simulation. The input of the simulation was a wide range of perfusion, and the main aim was to compare this input to the determined perfusion parameters. Another input of the simulation was an AIF template derived from in vivo measurements. The distortions of this template was modeled via a Rician distribution for image intensities. As for a real DSC-MRI experiment, the simulation returned the AIF and the tracer concentration-dependent signal in the tissue. The novel correction scheme was tested by deriving perfusion parameters from the simulated data for the corrected and the uncorrected case. For this analysis, a common truncated singular value decomposition approach was applied. We find that the saturation effect caused by Rician-distributed noise leads to an overestimation of regional cerebral blood flow and regional cerebral blood volume, as compared to the input parameter. The aberration can be amplified by a decreasing signal-to-noise ratio (SNR) or an increasing tracer concentration. We also find that the overestimation can be successfully eliminated by the proposed saturation-correction scheme. In summary, the correction scheme will allow DSC-MRI to be expanded towards higher tracer concentrations and lower SNR and will help to increase the measurement to measurement reproducibility for longitudinal studies.