采用信息增益率的混合入侵检测模型设计

针对现有混合入侵检测模型仅定性选取特征而导致检测精度较低的问题，同时为了充分结合误用检测模型和异常检测模型的优势，提出一种采用信息增益率的混合入侵检测模型.首先，利用信息增益率定量地选择特征子集，最大程度地保留样本信息；其次，采用余弦时变粒子群算法确定支持向量机参数构建误用检测模型，使其更好地平衡粒子在全局和局部的搜索能力，然后，选取灰狼算法确定单类支持向量机参数构建异常检测模型，以此来提高对最优参数的搜索效率和精细程度，综合提高混合入侵检测模型对攻击的检测效果；最后，通过两种数据集进行仿真实验，验证了所提混合入侵检测模型具有较好的检测性能.     

一种抗运动干扰的实时心率提取方法

针对基于容积脉搏波（PPG）提取运动心率时，传统心率提取算法由于运动噪声干扰使测量结果误差大、实时性不好的问题，提出一种抗运动干扰的实时心率提取方法。该方法通过实时小波去噪，同时结合三轴加速度信号（ACC）对运动进行分类训练，计算各运动状态心率增益，对实时心率值进行补偿。实验结果表明，通过与同时采集的ECG信号计算出的实时心率进行对比，绝对误差率仅为1.2%左右。相比传统心率提取算法，该算法具有抗干扰性强，实时准确的特点。     

一种5 重real-time PCR筛查转基因水稻方法的建立

以转基因水稻中最常用的CaMV35S启动子、NOS终止子、Cry1Ab/Ac基因、HPT基因及SPS水稻内标基因为研究对象，利用5 种不同的荧光信号（FAM、HEX、Taxas Red、Cy5、Cy5.5）进行多重实时聚合酶链式反应（real-time polymerase chain reaction，real-time PCR）检测方法的研究。通过引物组合筛选、反应体系优化、特异性测试、灵敏度测试、适用性测试等一系列实验，建立了5 重real-time PCR方法，灵敏度可达0.032%。此方法具有灵敏度高、结果准确、通量大等优点，可实现水稻中转基因成分的快速、高效检测。     

Different hydrothermal corrosion results between two sides of sodalime float glass and the possible corrosion mechanism

Sodalime float (SF) glass is widely used in our societies and industries. Hydrothermal corrosion method is one of the effective ways to prepare a superhydrophobic glass, but there is still lack of knowledge about hydrothermal corrosion behavior and mechanism of SF glass. We have hydrothermally treated SF glass at 180 °C for different time, and tried to reveal the aqueous corrosion process of SF glass. We have characterized the morphologies and chemical compositions of samples, and found that (1) the two sides of SF glass have different corrosion resistances, and (2) a multilayer structural coating with a nanoflake layer (Mg-rich gel layer), a nanowire layer (Ca-rich gel layer), and a porous layer (etched layer) is formed on the air-side of SF glass. Based on the experimental results, we have proposed an aqueous corrosion mechanism of SF glass. The insights of the hydrothermal corrosion behaviors and mechanism provide helpful guidelines to glass surface structural control and functionalization.     

液相色谱法快速检测染色梅鱼中日落黄、柠檬黄的含量

目的建立一种快速、低成本检测染色梅鱼中日落黄、柠檬黄的方法。方法将染色梅鱼剥皮,鱼皮经70%甲醇氨水提取液提取,经EclipseXDB-C_(18)色谱柱分离,以甲醇和乙酸铵水溶液为流动相,进行梯度洗脱,流速为1.0 mL/min,柱温35℃,利用紫外检测器检测日落黄、柠檬黄的含量。结果日落黄、柠檬黄在1.25、2.5、12.5、25 mg/kg添加水平的加标回收率为80%～90%,相对标准偏差小于10%(n=6),柠檬黄检出限为0.05 mg/kg,日落黄检出限为0.025 mg/kg。结论该方法快速、准确、成本低,适合染色梅鱼中日落黄、柠檬黄的快速检测。     

The biological mechanisms of butanol tolerance and the application of solvent-tolerant bacteria for environmental protection

Toxicity caused by the accumulation of butanol in fermentation media is an important factor limiting the concentration of butanol. There is currently no systematic research in place investigating the butanol tolerance mechanism of bacteria such as Clostridium acetobutylicum, which adapts to butanol stress and regulates its growth and metabolism. Here, research results related to the butanol tolerance of C. acetobutylicum are reviewed to understand the molecular basis of changes in butanol-tolerant strains. Organic solvent-tolerant bacteria play an important role in the fields of biofuel production, enzyme preparation and bioremediation. An analysis of limitations of the application of organic solvent-tolerant bacteria has revealed that future research should focus on combining the microbial tolerance phenotype with specific utilization to achieve an optimal balance between organic solvent tolerance and production. This review serves as a reference for the improvement and engineering of strains that tolerate organic solvents. © 2019 Society of Chemical Industry     

宝山铅锌银矿石选矿现状与对策

对宝山铅锌银矿石原矿性质、工艺流程、药剂制度及技术指标情况进行了介绍,指出了存在粉矿粒度过粗、磨矿效果不佳、金银回收率过低、矿种变化频繁及原矿品位波动大等问题,同时从降低粉矿粒度、完善磨矿自动化、浮选采用X荧光在线分析仪,有效回收金银矿物、合理配矿等方面,提出了解决问题的对策。     

Wearing prediction of stellite alloys based on opposite degree algorithm

In order to predict the wearing of stellite alloys,the related methods of rare metals data processing were discussed. The method of opposite degree(OD) algorithm was put forward to predict the wearing of stellite alloys.OD algorithm is based on prior numerical data, posterior numerical data and the opposite degree between numerical forecast data. To compare the performance of predicted results based on different algorithms, the back propagation(BP) and radial basis function(RBF) neural network methods were introduced. Predicted results show that the relative error of OD algorithm is smaller than those of BP and RBF neural network methods. OD algorithm is an effective method to predict the wearing of stellite alloys and it can be applied in practice.