珍珠粉、珍珠层粉、珍珠母粉的热重及热重动力学

采用热重及热重动力学方法 ,分别研究珍珠粉、珍珠层粉和珍珠母粉的热分解过程及其反应机理。结果表明 ,珍珠粉和珍珠层粉的热分解可分为二个阶段 :第一阶段为 2 50～ 370℃之间 ,失重率约 3% ,反应级数为 1 .6,活化能为 1 0 5～ 1 1 0 k J/ mol属于有机质的热分解 ;第二阶段为 60 0～ 770℃ ,失重率约为 40 % ,反应级数为 1 .3,活化能为 2 80～ 2 90 k J/ mol,属于碳酸钙的分解。珍珠母粉在 2 50～ 370℃之间不存在明显的失重。根据这一现象 ,可以通过热重分析来鉴别珍珠及其制品。     

Measurement of intrinsic rates for homogeneous gas‐phase reactions at high temperatures

A coiled quartz tubular reactor has been designed to measure the intrinsic reaction kinetics for homogeneous reactions at high temperatures up to 1100°C. Actual gas residence times were less than 100 ms. A simple and well‐studied test reaction (i.e., the decomposition of nitrous oxide, N₂O), with published intrinsic kinetics, was used to verify the operation of the experimental reactor. For this system, Peclet numbers (Pe = uL/DL) computed from experimental conversion data were greater than 1000, indicating that the plug flow assumption could be used with this reactor system to determine intrinsic rate expressions with errors of less than 5% for the conditions studied.     

在硫酸化氧化物催化剂上二氯甲烷的低温催化降解

采用色谱微反联用技术研究了在硫酸化氧化物催化剂上二氯甲烷的低温催化降解。实验发现，硫酸化氧化物催化剂如ＴｉＯ２－（ＳＯ４）在较低反应温度（如２７５℃）时表现出较高的反应活性，转化率１００％，并且其催化活性次序为：ＴｉＯ２－（ＳＯ４）＞ＺｒＯ２－（ＳＯ４）＞ＣｅＯ２－（ＳＯ４）。实验结果还表明：催化剂的酸性关联降解二氯甲烷的催化活性。同时，水汽的存在明显降低了其催化活性。     

小波包变换在火箭发动机脉动压力分析中的应用

在火箭发动机试验中,燃烧室脉动压力数据是考察推进剂燃烧状态的重要依据.通过对脉动压力数据特征分析,利用小波包变换多分辨分析的特点,以信噪比作为衡量标准,采用小波包自选阈值法对脉动压力数据进行去噪.通过与稳态参数数据的对比验证了去噪结果的准确性.采用Wicherhauser树状分解和Shannon信息熵基波选择标准等方法对脉动压力数据进行分频段分析.根据结果中各频段内的系数特征能够直观分析脉动压力在各频带中的能量分布.通过对脉动压力数据和相应振动测点数据的频谱分析,验证了分析结果的有效性.该方法在其他型号发动机和组合件试验脉动压力数据分析中有重要的应用和推广价值.     

Compositional metric learning for multi-label classification

Multi-label classification aims to assign a set of proper labels for each instance, where distance metric learning can help improve the generalization ability of instance-based multi-label classification models. Existing multi-label metric learning techniques work by utilizing pairwise constraints to enforce that examples with similar label assignments should have close distance in the embedded feature space. In this paper, a novel distance metric learning approach for multi-label classification is proposed by modeling structural interactions between instance space and label space. On one hand, compositional distance metric is employed which adopts the representation of a weighted sum of rank-1 PSD matrices based on component bases. On the other hand, compositional weights are optimized by exploiting triplet similarity constraints derived from both instance and label spaces. Due to the compositional nature of employed distance metric, the resulting problem admits quadratic programming formulation with linear optimization complexity w.r.t. the number of training examples.We also derive the generalization bound for the proposed approach based on algorithmic robustness analysis of the compositional metric. Extensive experiments on sixteen benchmark data sets clearly validate the usefulness of compositional metric in yielding effective distance metric for multi-label classification.     

Radio frequency interference suppression algorithm in the spatial domian for high-frequency radars

Radio frequency interference suppression is a very important issue in applications of high-frequency surface wave radar. This paper proposes a new interference suppression algorithm which makes use of RF interference azimuth information on the basis of learning common RF interference suppression algorithms and spatial spectrum estimation. First, we apply the MUSIC algorithm to estimate the interference azimuth and obtains the interference's signal space after the first Fourier transform; next, we use space decomposition to decompose the radar echo and obtain interference components; last, we subtract radio frequency interference components from the original signals. This algorithm can do great amount of RF interference suppression in actual data and get good results.     

苯并吡喃酮类化合物与Skp2蛋白的分子识别及其抑制机理

S期激酶相关蛋白2(S-phase kinase-associated protein 2,Skp2)与Skp1形成的蛋白质聚合物在调控癌细胞生长周期中发挥着重要作用,而苯并吡喃酮类抑制剂(简称BPC)可有效抑制Skp1-Skp2的形成,但其分子识别机制尚不明确.通过生物信息学统计分析已报道的Skp1-Skp2晶体结构,确定模拟体系后,首先用同源模建对其模拟体系缺失的结构进行补全;然后用分子对接方法获得Skp1-Skp2-BPC复合物模型并用于后续分子动力学模拟.计算结果表明:疏水相互作用是促使BPC特异性结合在由Skp2 W109、D110、L117、I120、R138和W139所构成口袋中的主要驱动力,自由能计算值与实验数据吻合较好.Skp2结合BPC后,结合口袋周围的氢键网络有所加强,口袋附近的溶剂化水分子数量明显减少,导致Skp1-Skp2的体系稳定性下降.体系构象成簇与运动性分析显示,Skp1-Skp2在结合BPC抑制剂后,Skp1的运动更加剧烈,这可能是BPC主要的抑制机理.     

BaO 对不同温度焙烧的 La1.6Sr0.4NiO4催化 NO 直接分解活性的影响

通过 XRD、 H2‐T PR、 NO‐T PD 等分析测试手段,研究了一定量的 BaO 对不同温度制备的La1.6 Sr0.4 NiO4催化NO直接分解活性的影响。研究发现低温焙烧得到的样品对NO直接催化分解活性高于高温焙烧得到的样品,且催化剂本身活性越大, BaO对其催化NO直接分解的活性促进作用越大。     

基于危险源分解条件下的安全网络计划技术

建筑工程施工是高危险行业,安全事故频发的最根本的原因是没有对造成安全事故的危险源进行有效的管理.要预防和控制安全事故的发生,就必须对施工现场实施以危险源控制为核心的安全施工管理.从项目管理动态控制原则出发,将安全管理与网络进度计划紧密结合,以网络计划的施工内容为基础,将危险源分解与汇总,制定施工安全网络计划,体现危险源与进度控制的同步、协调,最终实现对危险源全面、系统、动态的管理,进而达到施工安全管理的目标.     

改进AR模型特征提取及分类

目前,表面肌电信号（sEMG）是手势动作识别研究的重要信号源.本文以肌电信号为对象,从非平稳与非线性的角度出发,采用ICA独立成分分析和经验模式分解的方法,消除表面肌电信号中的工频干扰,对处理后的信号建立AR模型.将模型系数作为信号的特征,对6种手势动作进行模式识别.实验表明,该方法获得的特征具有较好的分类效果.