Precipitation is a key manufacturing unit during the immunoglobulin G (IgG) production, which guarantees the quality of the final product. Ethanol is usually used to purify IgG during the precipitation process, so it is important to monitor the ethanol concentration online. Nearinfrared (NIR) spectroscopy is a powerful process analytical technology (PAT) which has been proved to be feasible to determine the ethanol concentration during the precipitation process. However, the NIR model is usually established based on the specific process, so a universal model is needed. And the clarity degree of solution will affect the quality of the spectra. Therefore, in this study an integrated NIR system was introduced to establish a universal NIR model which could predict the ethanol concentration online and determine the end-point of the whole process. First, a spectra acquisition device was designed and established in order to get high-quality NIR spectra. Then, a simple prepared ethanol NIR model was constructed to predict the actual manufacturing process. Finally, the end-point was determined to stop the peristaltic pump when the ethanol concentration reached 20%. The results showed that the spectra quality was good, model prediction was accurate, and process monitoring was accurate. In conclusion, all results indicated that the integrated NIR system could be used to monitor the biopharmaceutical process to help us understand the pharmaceutical process.

通用宽带换能器(含低频到高频)一般是将不同类型的换能器进行组合使用，单个换能器独立设计再组合成阵，其综合体积及质量均大，且安装后其性能指标受影响(如换能器开角变小等)。该文在分析当前国内外宽带换能器研究现状基础上，结合小型遥控无人潜水器(ROV)搭载探测需求，提出具体设计指标要求。将复合棒换能器与数个压电陶瓷圆环进行开放式一体化组合设计，在满足小型ROV安装要求的基础上，实现了发射3～100 kHz、接收1～100 kHz的超宽频带覆盖范围，且开角不小于70°。水池及湖上实航实验结果表明，研制的换能器与仿真设计相符，实航测量结果与国内外相关结论一致性较好，具有广泛的工程实用价值。

Near infrared (NIR) spectroscopy is now widely used in fluidized bed granulation. However, there are still some demerits that should be overcome in practice. Valid spectra selection during modeling process is now a hard nut to crack. In this study, a novel NIR sensor and a cosine distance method were introduced to solve this problem in order to make the fluidized process into "visualization". A NIR sensor was fixed on the side of the expansion chamber to acquire the NIR spectra. Then valid spectra were selected based on a cosine distance method to reduce the influence of dynamic disturbances. Finally, spectral pretreatment and wavelength selection methods were investigated to establish partial least squares (PLS) models to monitor the moisture content. The results showed that the root mean square error of prediction (RMSEP) was 0.124% for moisture content model, which was much lower than that without valid spectra selection treatment. All results demonstrated that with the help of valid spectra selection treatment, NIR sensor could be used for real-time determination of critical quality attributes (CQAs) more accurately. It makes the manufacturing easier to understand than the process parameter control.

Human albumin (HA) is a very important blood product which requires strict quality control strategy. Acid precipitation is a key step which has a great effect on the quality of final product. Therefore, a new method based on quality by design (QbD) was proposed to investigate the feasibility of realizing online quality control with the help of near infrared spectroscopy (NIRS) and chemometrics. The pH value is the critical process parameter (CPP) in acid precipitation process, which is used as the end-point indicator. Six batches, a total of 74 samples of acid precipitation process, were simulated in our lab. Four batches were selected randomly as calibration set and remaining two batches as validation set. Then, the analysis based on material information and three different variable selection methods, including interval partial least squares regression (iPLS), competitive adaptive reweighted sampling (CARS) and correlation coe±cient (CC) were compared for eliminating irrelevant variables. Finally, iPLS was used for variables selection. The quantitative model was built up by partial least squares regression (PLSR). The values of determination coe±cients (R2c and R2p ), root mean squares error of prediction (RMSEP), root mean squares error of calibration (RMSEC) and root mean squared error of cross validation (RMSECV) were 0.969, 0.953, 0.0496, 0.0695 and 0.0826, respectively. The paired t test and repeatability test showed that the model had good prediction ability and stability. The results indicated that PLSR model could give accurate measurement of the pH value.

在液晶面板制造设备故障诊断中, 传统方法存在效率低、经验分散等缺陷, 为此设计了一种基于规则的设备故障诊断专家系统, 能够缩短诊断设备故障时间, 高效地整合了故障诊断经验资源。产生式规则按照固定的格式, 并具有与人的思维相似, 直观、自然、容易理解等特点, 将其应用到该专家系统中的知识库中, 提高了知识库的增长速度和准确度。实际应用表明, 该系统可准确判别液晶面板设备故障原因并提供解决方案, 将诊断设备故障平均时间降低了35.5% 。

As an important process analysis tool, near infrared spectroscopy (NIRS) has been widely used in process monitoring. In the present work, the feasibility of NIRS for monitoring the moisture content of human coagulation factor VIII (FVIII) in freeze-drying process was investigated. A partial least squares regression (PLS-R) model for moisture content determination was built with 88 samples. Different pre-processing methods were explored, and the best method found was standard normal variate (SNV) transformation combined with 1st derivation with Savitzky– Golay (SG) 15 point smoothing. Then, four different variable selection methods, including uninformative variable elimination (UVE), interval partial least squares regression (iPLS), competitive adaptive reweighted sampling (CARS) and manual method, were compared for eliminating irrelevant variables, and iPLS was chosen as the best variable selection method. The correlation coe±cient (R), correlation coe±cient of calibration set (R_cal), correlation coe±cient of validation set (R_val), root mean square errors of cross-validation (RMSECV) and root mean square errors of prediction (RMSEP) of PLS model were 0.9284, 0.9463, 0.8890, 0.4986% and 0.4514%, respectively. The results showed that the model for moisture content determination has a wide range, good linearity, accuracy and precision. The developed approach was demonstrated to be a potential for monitoring the moisture content of FVIII in freeze-drying process.

Near infrared spectroscopy (NIRS) is based on molecular overtone and combination vibrations. It is difficult to assign specific features under complicated system. So it is necessary to find the relevance between NIRS and target compound. For this purpose, the chondroitin sulfate (CS) ethanol precipitation process was selected as the research model, and 90 samples of 5 different batches were collected and the content of CS was determined by modified carbazole method. The relevance between NIRS and CS was studied throughout optical pathlength, pretreatment methods and variables selection methods. In conclusion, the first derivative with Savitzky–Golay (SG) smoothing was selected as the best pretreatment, and the best spectral region was selected using interval partial least squares (iPLS) method under 1mm optical cell. A multivariate calibration model was established using PLS algorithm for determining the content of CS, and the root mean square error of prediction (RMSEP) is 3.934 g·L^-1. This method will have great potential in process analytical technology in the future.

霍山石斛是一种非常珍贵的中药材, 具有很高的商品价值和药用价值。 不同种的霍山石斛具有不同的商品价格和药效作用, 因此需要建立一种快速且绝对无损的方法来鉴别不同种的霍山石斛。 该实验, 采用微型近红外光谱仪MicroNIR 1700 实现对来自于三个不同种的五个不同商品等级的霍山石斛鉴别研究。 经光谱预处理、 波段选择及主成分数优化后所建最佳SIMCA模型结果的识别率和拒绝率均达到100%, 表明微型近红外光谱仪MicroNIR 1700能够成功实现对五类霍山石斛的快速及绝对无损鉴别。

Signal degradation due to physical impairments may result in unacceptable bit-error rates of received signals at the destination. Based on earlier work, we study the impairment-aware quality of service (QoS) provisioning problem in dual-header optical burst switching (OBS) networks that employ two control packets for each data burst. At an OBS node, the proposed algorithm schedule bursts for transmission by searching for available resources using admission control and preemption. The algorithm also verifies signal quality. Simulation results show that this algorithm is effective in providing QoS support in OBS networks while considering physical impairment effects.

自制了紫外-可见分光光度计的微柱电泳高效分离附件, 介绍了X射线衍射法在电泳微柱制备中的应用以及微柱电泳与紫外-可见分光光度法的在线联用。 使用水热法合成均匀石英微米晶粒, 采用X射线衍射法表征和控制产物的晶相, 并用扫描电子显微镜观察产物形貌。 将合成的石英微米晶粒均匀填充在2 mm i.d.石英管中, 制成电泳微柱。 通过微柱电泳与紫外-可见分光光度法在线联用, 对非衍生的色氨酸、 苯丙氨酸和酪氨酸进行了分离检测。 检出限分别为0.037, 0.20和0.20 μmol?L-1, 色氨酸的分离效率为每米4.5×104, 电泳微柱的样品容量达到35 μL。 实验结果表明, 填充石英微米晶粒的微柱电泳可抑制大柱径电泳热效应, 增大样品容量, 提高检测灵敏度。 微柱电泳与常规紫外-可见分光光度法联用可简便地对混合物进行在线分离和测定, 进一步拓宽了紫外-可见分光光度计在光谱重叠组分痕量分析中的应用。Spectrophotometry