HPLC法测定依诺沙星软膏的含量

ＨＰＬＣ法测定依诺沙星软膏的含量ＤｅｔｅｒｍｉｎａｔｉｏｎｏｆｅｎｏｘａｃｉｎｕｎｇｕｅｎｔｕｍｂｙＨＰＬＣ曾玲刘宁傅建ＺｅｎｇＬｉｎｇ，ＬｉｕＮｉｎｇａｎｄＦｕＪｉａｎ（江西省药品检验所，南昌３３００４６）（ＪｉａｎｘｉＰｒｏｖｉｎｃｉａｌＩｎｓｔ...

基于Kalman滤波器的状态估计软测量

软测量技术是当前过程控制中研究热点之一,状态观测器在现代控制理论的应用中,主要是用来对系统中不可浏量状态进行估计或重构。本文介绍了基于Kalman滤波器的状态估计软测量技术,从可测信息集通过运用Kalman滤波器对系统进行状态估计,把主导变量作为待估过程状态,通过扩展的Kalman滤波自适应算法推出主导变量的估计值,实现对用常规方法难以测量的参数的测量,并通过工业应用实例进行说明。最后对其发展和应用进行了展望。

神经系统软体征量表的信效度评估

目的 评估神经系统软体征量表的信效度。方法 对173例精神分裂症患者的神经系统软体征进行评定,并与病程、阴性症状各因子分、BPRS评分进行相关分析,同时对其中16名患者间隔1周后进行神经系统软体征重测。结果 重测信度r=0.907,各成分的重测信度在0.704～0.98之间;分半信度r_s=0.694;与阴性症状及其他各因子之间,与病程、BPRS分呈高度相关。结论 神经系统软体征量表具有良好信度和构想效度。

定量磁共振成像在关节软骨中的应用研究进展

在临床上,关节软骨损伤是一种常见病,其发生发展可由外伤、骨性关节炎(osteoarthritis, OA)以及剥脱性骨软骨炎等原因造成,而且这种损坏发生后很难修复。关节软骨损伤主要表现为关节疼痛及功能障碍,关节软骨的损伤以及退变都不同程度地发生在老年人及长期剧烈运动的人群中。关节镜检查被认为是诊断关节软骨病变的金标准。但由于其有创检查的性质,对检查者的技术水平要求很高,且无法深入了解软骨的内部情况。定量磁共振成像(quantitative magnetic resonance imaging, qMRI)既可显示软骨形态学变化,又可以定量评估软骨的生化成分,由于该技术具有无创、良好的软组织分辨力、多参数、多平面成像的优势,它能以非侵入性的定量测量来敏感地监测软骨的微细变化,提供可靠和可重复的成像生物标志物。

堆载预压法处理道路软基的效果分析

本文通过广州市一条堆载预压 7年的道路工程资料研究 ,发现软基区填方路堤在 2 .5～ 3.0m间存在一临界高度。路堤低于临界高度时 ,路基沉降量随路堤增高增加缓慢 ;路堤高于临界高度时 ,路基沉降量随路堤增高迅速增加 ;但路堤高度一定时 ,软基沉降量随软土层厚度变大增加缓慢。堆载 7年后 ,在原埋深 3.0m以上的软土的物理力学性质改善 2 7%～ 6 9% ,3.0m以下软土的物理力学性质改善 1%～ 5%。

灰色-马尔科夫模型对软土路基沉降预测的应用研究

为得到软土路基施工中较为准确的沉降预测值,本文以某段软土路基为实例,采用马尔科夫链优化过的灰色模型进行预测同时加以分析。结果表明:通过对比原有数据发现使用马尔科夫链优化过的灰色模型可以将软土路基观测沉降量预测值的相对误差下降至0.46%,并达到一级精度,该方法不仅可以对软土路基沉降值进行预测,而且也可以为相关施工部门提供一定理论依据。

饱水软粘土主固结理论研究

滨海饱和淤泥的加固普遍采用堆载预压排水固结方法,但是并不是预压时间越长,淤泥中孔隙水排出的越多,当淤泥含水量降低到一定程度后,(达到一个"极限含水量"),延长预压时间对淤泥固结不起应有作用,研究表明这个"极限含水量",延长预压时间对淤泥固结不起应有作用,研究表明这个"极限含水量"和淤泥的"液限含水量"相当,对饱水软粘土的预压排水主固结研究应从其排水的本质上出发,即从软土在预压过程的含水量变化上研究主固结量的变化规律,利用土的基本性质指标,导出主固结比基本公式及主固结量(沉降量)、绝对主固结量、绝对固结度等理论计算方法,它们与传统的算法不一样在于这些算法与预压荷载(即固结应力)无关系,直接计算出主固结的效果及评价预压排水固结地基处理卸载的可行性。利用上述基本公式亦可导出剩余主固结量、主固结速率等计算式。通过实例的分析,证明上述理论方法与观测的数据基本相符。

Effect of chloride salt concentration on unconfined compression strength of cement-treated Lianyungang soft marine clay

This study aims to quantify the influence of the amount of cement and chloride salt on the unconfined compression strength （UCS） of Lianyungang marine clay. The clays with various sodium chloride salt concentrations were prepared artificially and stabilized by ordinary Portland cement with various contents. A series of UCS tests of cement stabilized clay specimen after 28 d curing were carried out. The results indicate that the increase of salt concentration results in the decrease in the UCS of cement-treated soil. The negative effect of salt concentration on the strength of cement stabilized clay directly relates to the cement content and salt concentration. The porosity-salt concentration/cement content ratio is a fundamental parameter for assessing the UCS of cement-treated salt-rich clay. An empirical prediction model of UCS is also proposed to take into account the effect of salt concentration. The findings of this study can be referenced for the stabilization improvement of chloride slat- rich soft clay.

Design of new biomedical titanium alloy based on d-electron alloy design theory and JMatPro software

A new kind offl biomedical titanium alloy, Ti-35Nb-4Sn-6Mo-9Zr, composed of non-toxic elements Nb, Mo, Zr and Sn with lower elastic modulus and higher strength was designed based on d-electron alloy design theory and JMatPro software using orthogonal experiment. The microstructure and basic mechanical properties of designed alloy were investigated. The results show that the alloy is composed of single fl equiaxed grains after solution treatment at 800 ~C. Compared with Ti-6A1-4V, the mechanical properties of the designed alloy are more excellent： E=65 GPa, σb=834 MPa, σ0.2=802 MPa, and σ=11%, which is expected to become a promising new type implanted material. The research approach adopted can reduce the experimental time and cost effectively, and get the ideal experimental results.

EVALUATION OF SOFTWARE OF FOUR-PARAMETER SINE WAVE CURVE -FIT

Sinusoid curve fit is a very useful method in precise measurement, based on the modeling measurement. There are many valuable uses. But, what′s the specifications of the sinusoid curve fit software, and how to evaluate the uncertainty of it are still unknown yet, because they involve manifold factors and are complicated. Every one using the sinusoid curve fit software wants to know it. In this paper, the basic process and the uses of sinusoid curve fit are described, and some specifications and evaluation methods are introduced. One evaluation example of sinusoid curve fit software is discussed, the results and the specification are good.

Quality prediction of batch process using the global-local discriminant analysis based Gaussian process regression model

The conventional single model strategy may be ill- suited due to the multiplicity of operation phases and system uncertainty. A novel global-local discriminant analysis （GLDA） based Gaussian process regression （GPR） approach is developed for the quality prediction of nonlinear and multiphase batch processes. After the collected data is preprocessed through batchwise unfolding, the hidden Markov model （HMM） is applied to identify different operation phases. A GLDA algorithm is also presented to extract the appropriate process variables highly correlated with the quality variables, decreasing the complexity of modeling. Besides, the multiple local GPR models are built in the reduced- dimensional space for all the identified operation phases. Furthermore, the HMM-based state estimation is used to classify each measurement sample of a test batch into a corresponding phase with the maximal likelihood estimation. Therefore, the local GPR model with respect to specific phase is selected for online prediction. The effectiveness of the proposed prediction approach is demonstrated through the multiphase penicillin fermentation process. The comparison results show that the proposed GLDA-GPR approach is superior to the regular GPR model and the GPR based on HMM （HMM-GPR） model.

Design and Implementation of Traceability Management System of Agricultural Products Quality and Safety Based on Domestic Basic Software of China

[Objective] To establish the traceability mechanism of agricultural products safety, and the application of promote domestic based software in the supervision area of agricultural products quality and safety. [Method] Through the analysis on the circulation characteristics of agricultural products, like fruits, vegetables, livestock and poultry, the agricultural products quality safety management and traceability query business component libraries were designed. Based on the run-time-supporting environment provided by domestic based software, traceability management system of agricultural products quality and safety was constructed. [Result] The traceability management system provided the information interaction and comprehensive management platform of agricultural product quality and safety based on domestic based software for the government, enterprises and consumers. [Conclusion] Through the application demonstration, the quality control and information traceability of full circulation of agricultural products was achieved effective and reliably, and the management level of agricultural products quality and safety was improved.

Dynamic software allocation algorithm for saving power in pervasive computing

A novel dynamic software allocation algorithm suitable for pervasive computing environments is proposed to minimize power consumption of mobile devices. Considering the power cost incurred by the computation, communication and migration of software components, a power consumption model of component assignments between a mobile device and a server is set up. Also, the mobility of components and the mobility relationships between components are taken into account in software allocation. By using network flow theory, the optimization problem of power conservation is transformed into the optimal bipartition problem of a flow network which can be partitioned by the max-flow rain-cut algorithm. Simulation results show that the proposed algorithm can save si^nificantlv more energy than existing algorithms.

Analysis of Yield and Quality Characteristics of Cultivars of Japonica Fragrant and Soft Rice in Yunnan Province

In plateau region of Yunnan Province, japonica rice-growing areas are characterized by high altitude, heavy rain in summer, low temperature and insuffi- cient accumulated temperature in grain-filling stage. In view of the characteristics above, the breeding of japonica soft rice was carried out. In this paper, the yield and quality characteristics of japonica soft rice cultivars bred recently in Yunnan Province were analyzed. The results showed that there was no difference in milling quality, but there were great differences in chemical indexes between soft rice and japonica rice, such as amylose content. For example, in soft rice, the amylose con- tent was significantly lower, but the protein content, gel consistency and taste meter value were significantly higher compared with those in japonica rice. However, there was no significant difference in alkali digestion value between soft rice and japonica rice. The starch RVA profile characteristics of soft rice were significantly better than those of japonica rice. The RVA starch profile of soft rice showed higher maximum viscosity, lower minimum viscosity, higher breakdown value, lower final viscosity, lower setback value and shorter time to reach the maximum viscosity （P〈0.05, P〈 0.01）. The analysis of yield and yield components showed that the yield of japonica soft rice was still lower than that of the control cultivar, which might be caused by weaker tillering capacity, less grains per panicle and lower 1 000-grain weight. In addition, the approaches to improve grain quality and yield of japonica soft rice were also discussed.

Heat Resisting Mechanism of Heat-Resisting Aluminum Alloy Conductor and Its Application in Transmission Line

In this paper the heat withstanding mechanism of heat-resisting aluminum alloy conductor is discussed, the types and performance of the conductor and its application on transmission lines are analyzed and introduced, and suggestions on accelerating exploitation and application of the conductor are put forward.

Adaptive double-threshold energy detection algorithm for cognitive radio

Due to the fact that the conventional spectrum sensing algorithm is susceptible to noise, an adaptive double-threshold energy detection algorithm for a cognitive radio is proposed. Based on double-threshold energy detection, the algorithm can adaptively switch between one-round sensing and two-round sensing by comparing the observations with the pre-fixed thresholds. Mathematical expressions for the probability of detection, the probability of false alarm, and the sensing time are derived. The relationships including signal to noise ratio （SNR） vs. the probability of detection and SNR vs. the sensing time are plotted using Monte Carlo simulation and the algorithm is verified in a real cognitive system based on GNU Radio and universal software radio peripheral （USRP）. Simulation and experimental results show that, compared with the existing spectrum sensing method, the proposed algorithm can achieve a higher probability of detection within a reasonable sensing time.

Multiple Model Soft Sensor Based on Affinity Propagation, Gaussian Process and Bayesian Committee Machine

Presented is a multiple model soft sensing method based on Affinity Propagation （AP）, Gaussian process （GP） and Bayesian committee machine （BCM）. AP clustering arithmetic is used to cluster training samples according to their operating points. Then, the sub-models are estimated by Gaussian Process Regression （GPR）. Finally, in order to get a global probabilistic prediction, Bayesian committee mactnne is used to combine the outputs of the sub-estimators. The proposed method has been applied to predict the light naphtha end point in hydrocracker fractionators. Practical applications indicate that it is useful for the online prediction of quality monitoring in chemical processes.

REENGINEERING THE ASSEMBLY PROCESSES OF PRINTED CIRCUIT BOARDS:A CASE STUDY

This paper reports the reengineering of the assembly processes of printed circuit boards (PCBs) used in computers.The new designed assembly processes are quite different from the traditional ones,and the business performance is dramatically improved through establishing parallel workstations,off line workstation,merging workstations and organizing a small teamwork who cooperates in stations.“ITHINK”,a software package of business process reengineering (BPR),was used to analyze the current processes and create new processes.ITHINK is a powerful tool of BPR in modeling business processes,“soft” variables and conducting sensitivity analysis.The new assembly processes were tested over a period of 8 hours simulation.The results show that the new processes can increase throughput by 80% with only requiring less additional resources.The throughput can increase further by 17.5% when a small teamwork cooperates in some stations.

可溶盐对水泥土强度影响的微观分析

为深入认识连云港地区软土中的易溶盐对水泥土搅拌桩桩身质量的影响,通过无侧限强度试验和扫描电子显微镜(SEM)及X-射线衍射试验研究方法,研究高含盐量特征对水泥土强度影响的内在原因。结果表明:Mg2+、Cl-、SO42-都对水泥土强度起了不同程度的负面作用,其中Cl-对早期和长期强度都有影响;Mg2+从中期开始发挥作用;SO42-则对水泥土长期强度影响较大。滨海地区软土及地下水中较多的Cl-,会与水泥成分和水化产物Ca(OH)2反应,一种强度较低的生成物会包裹在粘土颗粒表面,阻碍了水泥土的强度增长。当软土中含有较多SO42-时,大量钙矾石晶体的生成会使水泥土膨胀而变得疏松,从而使水泥土的长期强度变低。

Adaptive Soft-sensor Modeling Algorithm Based on FCMISVM and Its Application in PX Adsorption Separation Process

To overcome the problem that soft sensor models cannot be updated with the process changes, a soft sensor modeling algorithm based on hybrid fuzzy c-means （FCM） algorithm and incremental support vector machines （ISVM） is proposed. This hybrid algorithm FCMISVM includes three parts： samples clustering based on FCM algorithm, learning algorithm based on ISVM, and heuristic sample displacement method. In the training process, the training samples are first clustered by the FCM algorithm, and then by training each clustering with the SVM algorithm, a sub-model is built to each clustering. In the predicting process, when an incremental sample that represents new operation information is introduced in the model, the fuzzy membership function of the sample to each clustering is first computed by the FCM algorithm. Then, a corresponding SVM sub-model of the clustering with the largest fuzzy membership function is used to predict and perform incremental learning so the model can be updated on-line. An old sample chosen by heuristic sample displacement method is then discarded from the sub-model to control the size of the working set. The proposed method is applied to predict the p-xylene （PX） purity in the adsorption separation process. Simulation results indicate that the proposed method actually increases the model＇s adaptive abilities to various operation conditions and improves its generalization capability.