两阶抽样中比率型估计量的平均精度

本文给出了两阶抽样中总体均值的比率型估计量的平均精度,它当样本容量充分大时主项不劣于无偏估计量的平均精度．     

Periodic operation of immobilized live cell bioreactor for the production of candicidin

A lumped model for cell growth and secondary metabolite production in an immobilized live cell bioreactor has been developed. This model is applied here to simulate the performance of an immobilized bioreactor under steady-state conditions and under conditions of periodically varying concentration of a growth-limiting substrate. The results of the simulation study were experimentally verified in the case of the production of the antibiotic candicidin by Streptomyces griseus in an immobilized bioreactor with forced periodic operation. The results of the studies suggest that periodically operated immobilized live cell bioreactors can provide a potent alternative for the production of non-growth-associated biochemicals, as compared to free cell fermentations, pulsed fermentations with process cycle regeneration, and nonregenerated bioreactors. This work has demonstrated that by frequent pulsing of the growth limiting nutrient, stable extended production can be obtained at high specific cellular productivities.     

Feasibility of hydrogen production from ripened fruits by a combined two-stage (dark/dark) fermentation system

Anaerobic fermentation for hydrogen (H₂) production was studied in a two-stage fermentation system fed with different ripened fruit feedstocks (apple, pear, and grape). Among the feedstocks, ripened apple was the most efficient substrate for cumulative H₂ production (4463.7 mL-H₂ L⁻¹-culture) with a maximum H₂ yield (2.2 mol H₂ mol⁻¹ glucose) in the first stage at a hydraulic retention time (HRT) of 18 h. The additional cumulative biohydrogen (3337.4 mL-H₂ L⁻¹-culture) was produced in the second stage with the reused residual substrate from the first stage. The major byproducts in this study were butyrate, acetate, and ethanol, and butyrate was dominant among them in all test runs. During the two-stage system, the energy efficiency (H₂ conversion) obtained from mixed ripened fruits (RF) increased from 4.6% (in the first stage) to 15.5% (in the second stage), which indicated the energy efficiency can be improved by combined hydrogen production process. The RF could be used as substrates for biohydrogen fermentation in a two-stage (dark/dark) fermentation system.     

在线推定和控制葡萄糖浓度改善谷氨酸发酵性能

谷氨酸发酵过程一般需要定时、人工分批式地添加葡萄糖。该流加操作方式会引起发酵罐内葡萄糖浓度的剧烈波动, 不利于高效、稳定的谷氨酸生产。谷氨酸发酵具有显著的非增殖耦联特征, 产酸期葡萄糖耗量与氨水耗量存在非常明显的关联性。通过在线计量氨水耗量推定糖耗以及葡萄糖浓度, 可比较准确地将谷氨酸发酵产酸期的糖浓度控制在预先设定的水平。当糖浓度控制在5 g/L~10 g/L的低水平时, 最终谷氨酸浓度可以达到80 g/L的较高水平, 高糖浓度下的渗透压效应有望得到缓解, 有利于发酵生产的稳定。     

腔内大量盐水灌洗辅助取出乳房内聚丙烯酰胺水凝胶临床应用

目的：探讨聚丙烯酰胺水凝胶注射隆胸后取出新方法.方法：对48例注射聚丙烯酰胺水凝胶隆胸患者术前行双乳MRI或彩超检查结合触诊准确定位.全麻小切口开放直视下吸出水凝胶,再用大量生理盐水反复灌洗所有腔隙,直至手感探测不到硬结,盐水中无水凝胶为止.结果：48例患者术后无继发感染和出血等并发症.术前诸症状体征消失,无明显乳房变形,乳房形态术后恢复满意.术后双乳MRI复查未见明显异物残留.术后1 ～12月（6.2±0.3月）45例随访复查MRI亦未见异物残留,乳房修复完好.结论：注射隆乳后腔内大量盐水灌洗辅助取出水凝胶具有创伤小、出血少、操作简单、费用低廉的优点,是一种较好的、值得推广的凝胶取出术式.     

操作条件对生物质催化热解产轻质芳烃的影响

以轻质芳烃苯、甲苯、二甲苯以及萘（BTXN）为目的产物,采用双颗粒流化床对松木进行了催化热分解实验。讨论了催化剂CoMo-B加氢催化作用下,静止床高、流化气速、床层压降的相互关系,得到了一个合适的操作条件,为热分解实验提供了必要的基础实验数据。在热分解实验中,调查了操作气速、床层高度以及热解温度对产物收率和分布的影响,得到了中间产物苯、甲苯、二甲苯和萘等轻质芳烃化合物最高收率为6．3％下的最佳操作条件：催化剂为CoMo-B,气速2．0cm／s,床层高度为0．08m,热解温度863K。     

内支架对大肠癌急性梗阻一期切除吻合疗效的探讨

目的:探讨内支架对大肠癌急性梗阻一期切除吻合的疗效。方法:选择2010年7月至2012年7月来我院急诊治疗确诊为大肠癌导致急性肠梗阻的患者98例,随机分为观察组和对照组各49例,观察组患者植入内支架,一周后行一期吻合切除术,对照组行急诊切除手术。观察和比较两者患者一期切除率、治疗效果和并发症的情况。结果:观察组一期切除率为95.7%(47例)较对照组分71.4%(35例)高;两组比较差异均有统计学意义(x2=22.9,P0.05);实验组症状缓解48例(缓解率98%),对照组症状缓解33例(缓解率67.3%),两组临床疗效比较有显著性差异(x2=33.3,P0.001),实验组术后并发症发生率(10.2%)要明显小于对照组(26.5%)(x2=9.6,P0.01)。结论:大肠癌急性梗阻术前植入内支架能有效提高患者的一期手术吻合率和治疗效果,降低术后并发症,值得在临床推广。     

髋臼粉碎性骨折治疗方法的选择与预后探讨

目的:研究髋臼粉碎性骨折采用骨牵引与手术治疗的疗效的比较。方法:将118例髋臼粉碎骨折患者分为骨牵引组(74例)和手术组(44例),分别进行比较。结果:骨牵引组解剖复位10例(13.5%)、满意复位26例(35.1%),自我感觉优8例(10.8%)、良24例(32.4%);手术组解剖复位9例(40.9%)、满意复位12例(54.5%),自我感觉优7例(31.8%))、良9例(40.9%)。结论:手术治疗髋臼粉碎性骨折疗效明显优于骨牵引。     

Hybrid physics-based and data-driven modeling for bioprocess online simulation and optimization

Model-based online optimization has not been widely applied to bioprocesses due to the challenges of modeling complex biological behaviors, low-quality industrial measurements, and lack of visualization techniques for ongoing processes. This study proposes an innovative hybrid modeling framework which takes advantages of both physics-based and data-driven modeling for bioprocess online monitoring, prediction, and optimization. The framework initially generates high-quality data by correcting raw process measurements via a physics-based noise filter (a generally available simple kinetic model with high fitting but low predictive performance); then constructs a predictive data-driven model to identify optimal control actions and predict discrete future bioprocess behaviors. Continuous future process trajectories are subsequently visualized by re-fitting the simple kinetic model (soft sensor) using the data-driven model predicted discrete future data points, enabling the accurate monitoring of ongoing processes at any operating time. This framework was tested to maximize fed-batch microalgal lutein production by combining with different online optimization schemes and compared against the conventional open-loop optimization technique. The optimal results using the proposed framework were found to be comparable to the theoretically best production, demonstrating its high predictive and flexible capabilities as well as its potential for industrial application.