筛机筛分质量差的原因分析及技术改造

通过分析筛机筛分质量差的原因,对榆中钢铁公司焦化焦炭筛分系统第二筛序振动筛进行了改造,对第一筛序的铸石蓖条筛改为直线振动筛的可行性进行了初步论证。     

产耐温漆酶菌的筛选及培养基优化

采用愈创木酚CPDA平板法对由广州地区多个不同场所采集的土样进行了菌种分离纯化,筛选出1株产耐温漆酶的菌株Tr0702,通过形态学观察初步判断该菌为木霉属．该菌所产漆酶的最适反应温度为65℃,在70℃下保温60min后残余酶活保留60％以上;发酵培养基经响应面法优化后关键参数如下：可溶性淀粉44．40g／L、吐温（80）9．00g／L、愈创木酚15．04mmol／L,以此优化培养基发酵酶活可达50．15U／mL     

高效微生物絮凝剂产生菌BJ-Ⅰ的筛选鉴定及絮凝特性研究

从活性污泥中筛选出1株高效微生物絮凝剂产生菌BJ-Ⅰ,其絮凝率达87．6％．通过生理生化分析及16S rDNA序列鉴定该菌株为短芽孢杆菌（Bacillus brevis）．该菌产絮凝剂的最适碳源和氮源分别为20g/L的葡萄糖和2．0g／L的蛋白胨;适宜的初始pH和培养温度分别为7．0和30℃;在培养基中添加0．5g／L的Mg^2＋有利于菌体生长,但对絮凝剂合成无影响．对该絮凝剂的特性研究结果表明：菌液投放量3％、pH值在5．9、温度为60℃条件下絮凝效果最好,加入浓度为8％的Ca^2＋可显著提高其絮凝活性．实验证明,该菌起絮凝作用的物质存在于发酵液中,主要成分为杂多糖．     

番茄晚疫病病菌培养条件筛选

本试验选用佳木斯地区采集的番茄晚疫病病菌,分别在不同培养基、碳源、氮源、Ph、温度及光照时间的条件下培养,观察并记录菌落直径、产孢量及萌发率．来筛选番茄晚疫病病菌最佳培养条件．结果表明：黑麦培养基最适宜菌丝生长及产孢,以蔗糖做碳源最好,甘露糖最差;氮源以氨基丙酸最好,胱氨酸最差．孢子囊萌发的最适温度为15℃,低于5℃和高于35℃都不能萌发;光照抑制孢子囊的萌发,pH为7时孢子囊萌发率最高．     

Isolation, identification and characterization of cadmium-resistant Pseudomonas aeruginosa strain E1

Strain E₁ with resistance to 18 mmol/L cadmium (Cd), isolated from Cd-contaminated soil was identified by morphological observation, biochemical and physiological characterization and 16S rDNA sequence analysis. The resistance to heavy metals Cd, Cu, Co, Mn, Pb, Zn and 12 antibiotics was examined. The ability of removing Cd from solution was studied. The characterizations show that strain E₁ is affiliated to Pseudomonas aeruginosa (P. aeruginosa). Strain E₁ has high resistance to heavy metals and the order is found to be Cd>Mn>Zn>Cu>Pb>Co in solid media. Strain E₁ also exhibits the resistance to 12 antibiotics. Both living and non-living cells of strain E₁ can remove Cd from solution, and living cell has better biosorption than non-living cell. Foundation item: Project (50621063) supported by the National Natural Science Foundation of China; Project (2004CB619204) supported by the Major State Basic Research and Development Program of China     

Fetal phonocardiography--past and future possibilities

The paper presents an overview of the 15 year long development of fetal phonocardiography including the works on the applied signal processing methods for identification of sound components. Based on the improvements achieved on this field, the paper shows that beyond the traditional CTG test the phonocardiography may be successfully applied for long-term fetal measurements and home monitoring. In addition, by indication of heart murmurs based on a comprehensive analysis of the recorded heart sound congenital heart defects can also be detected together with additional features in the third trimester. This makes an early widespread screening possible combined with the prescribed CTG test even at home using a telemedicine system.     

一种基于Markov模型和协同克里格的插值方法

协同克里格是一种具有无偏性和最小预测方差的插值方法.它的主要优点在于充分考虑了空间信息点的相关性和不同变量间的交叉相关性,从而可以将不同信息进行融合.最初的协同克里格方法不能解决不同变量间交叉矩阵不稳定的问题.然而,根据Markov模型的屏蔽效应假设,可对协同克里格方法进行逼近.Markov模型的屏蔽效应假设:硬数据可以屏蔽在其位置以外的其他硬数据对其所在位置软数据的影响.因此在同位置协同克里格中引入Markov模型实现上述逼近.实验说明了该方法的有效性:(1)对该方法模拟结果与真实参考数据的方差和均值进行计算,误差分别为3.8%和2.9%;(2)插值结果具有与真实参考数据相似的直方图分布;(3)在模拟效果上要优于全局协同克里格和简单克里格方法.     

基于分子指纹的中药化合物数据库的层次聚类分析(英文)

作为高通量筛选的一种有效方法,虚拟筛选得到了越来越广泛的应用。当靶分子结构未知时,往往使用基于配体的虚拟筛选方法。在基于配体的虚拟筛选方法中,相似性方法起着非常重要的作用。基于中药有效成分化合物数据库,进行了层次凝聚聚类分析。在化学信息系统中,有许多的距离/相似性度量方法和相似性系数。在化学结构的表示和特征选择方面,使用了广泛使用的Daylight分子指纹。采用CDK项目来计算基于Daylight分子指纹的Tanimoto系数作为分子相似性度量方法。对TCM数据库进行了层次凝聚聚类分析,并在聚类之前应用了化学结构领域知识来进行待聚类数据的预处理。在层次聚类时,设定了0.75作为聚类的相似度阈值。计算了层次聚类过程中Kelly方法中的惩罚值来获取最合适的簇数量,通过该方法得到的簇数量与采用0.75作为相似度阈值聚类得到的簇数量非常接近。针对每一个包含多个化合物的簇,选取了多个化合物作为该簇的代表性化合物。同时根据聚类结果分析了Tanimoto系数的缺点。在后续工作中,可对TCM数据库进行分子骨架分析和多样性分析,并基于分子骨架进行聚类。     

CytoBrain: Cervical Cancer Screening System Based on Deep Learning Technology

Identification of abnormal cervical cells is a significant problem in computer-aided diagnosis of cervical cancer.In this study,we develop an artificial intelligence (AI) system,named CytoBrain,to automatically screen abnormal cervical cells to help facilitate the subsequent clinical diagnosis of the subjects.The system consists of three main modules:1) the cervical cell segmentation module which is responsible for efficiently extracting cell images in a whole slide image (WSI);2) the cell classification module based on a compact visual geometry group (VGG) network called CompactVGG which is the key part of the system and is used for building the cell classifier;3) the visualized human-aided diagnosis module which can automatically diagnose a WSI based on the classification results of cells in it,and provide two visual display modes for users to review and modify.For model construction and validation,we have developed a dataset containing 198952 cervical cell images (60238 positive,25001 negative,and 113713 junk) from samples of 2312 adult women.Since CompactVGG is the key part of CytoBrain,we conduct comparison experiments to evaluate its time and classification performance on our developed dataset and two public datasets separately.The comparison results with VGG11,the most efficient one in the family of VGG networks,show that CompactVGG takes less time for either model training or sample testing.Compared with three sophisticated deep learning models,CompactVGG consistently achieves the best classification performance.The results illustrate that the system based on CompactVGG is efficient and effective and can support for large-scale cervical cancer screening.     

基于主成分分析和LightGBM算法的风电场发电功率超短期预测

风力发电场发电功率的超短期预测越精确,越有利于电力系统的稳定运行和优化调度。为提高风电场发电功率超短期预测的准确率,提出了一种基于主成分分析和GBM算法的风电场发电功率超短期预测方法。该方法首先进行PCA主成分分析将与风电功率相关程度低的维度剔除,降低数据的冗余性,然后利用GBM算法建模实现风电场发电功率的超短期预测。实验结果表明基于GBM算法的风电场发电功率超短期预测效果良好,优于传统机器学习方法在风电场超短期的功率预测上的精度。