Filtered adaptive constrained sampled-data control for uncertain multivariable nonlinear systems

A filtered adaptive constrained sampled-data controller for uncertain multivariable nonlinear systems in the presence of various constraints is synthesized in this paper. A piecewise constant adaptive law drives that estimation error dynamics to zero at each sampling time instant yields adaptive parameters. The filtered control scheme consists of two components. Based on an estimation/cancellation strategy, a disturbance rejection control law is designed to compensate the nonlinear uncertainties within the bandwidth of low-pass filters, whereas a constraint violation avoidance control law is designed to solve an online constrained optimization problem. Although a reduced sampling time helps to minimize the estimation error caused by the neglect of unknowns, the resulting aggressive signals put more restrictions on the control law. Greater sacrifice of tracking performance is required to satisfy the constraints. The constraints violation avoidance control law is in favor of a larger sampling time. Sufficient conditions are given to guarantee the stability of the closed-loop system with the sampled-data controller, where the input/output signals are held constant over the sampling period. Numerical examples are provided to validate the theoretical results, comparisons between the constrained sampled-data controller and unconstrained adaptive controller with the implementation of different sampling times are carried out.     

Three‐dimensional color prediction modeling of single‐ and double‐layered woven fabrics

In this research, the three‐dimensional structural and colorimetric modeling of three‐dimensional woven fabrics was conducted for accurate color predictions. One‐hundred forty single‐ and double‐layered woven samples in a wide range of colors were produced. With the consideration of their three‐dimensional structural parameters, three‐dimensional color prediction models, K/S‐, R‐, and L*a*b*‐based models, were developed through the optimization of previous two‐dimensional models which have been reported to be the three most accurate models for single‐layered woven structures. The accuracy of the new three‐dimensional models was evaluated by calculating the color differences ΔL*, ΔC*, Δh°, and ΔE_CMC(2:1) between the measured and the predicted colors of the samples, and then the error values were compared to those of the two‐dimensional models. As a result, there has been an overall improvement in color predictions of all models with a decrease in ΔE_CMC(2:1) from 10.30 to 5.25 units on average after the three‐dimensional modeling.     

我国治疗新冠肺炎药物临床研究现状浅析

目的：分析疫情期间我国开展的新型冠状病毒肺炎（以下简称“新冠肺炎”）治疗药物临床试验的特点，提出防治新冠肺炎药物研发的建议。方法：在中国临床试验注册中心网站检索关于新冠肺炎的药物临床试验项目，对药物类别、研究目标、方案设计等进行分析。结果：截至2020年7月1日，与药物相关的临床试验项目共有271项。注册进行临床试验的药物主要是已上市药物，包括化学药、中药及生物制品，有些是药物联合应用。这些研究主要采取了随机或非随机平行对照试验设计，另外还有些是单臂、连续入组、析因分组等。结论：疫情期间应急开展药物临床试验、尽快发现有效的防治药物是应对疫情的重要措施，但同时本次新冠肺炎药物临床试验也暴露出在试验设计、实施及监管等方面存在的一些不足和短板，建议采取加强候选药物的科学性评价、规范研究者发起药物临床研究、建立由多学科组成的国家级抗病毒药物研发平台及协同创新攻关机制等措施，提升我国抗病毒药物的研发能力和水平。     

生物质源多孔碳制备及其对废水中药物吸附研究进展

城市现代化与工业化的快速发展给环境造成的污染日趋严重，尤其以水体污染最为明显。近年来，工业废水中药物的含量逐年上升，污染程度已经不容忽视。因此，开发新型多孔材料用于废水中药物分子的吸附分离，已经成为了当前的研究热点。综述了近年来生物质源多孔碳（生物炭）在废水中污染物吸附分离方面的研究，首先简单介绍了废水中污染物的治理方法，在此基础上重点探讨了生物炭的制备与修饰，并结合碳材料表面化学性质与孔道结构，总结并展望了生物炭对药物的吸附性能。     

四川某稀土矿选矿试验研究

针对四川某稀土矿选矿工艺存在的稀土回收率低的问题，开展了一系列选矿试验研究。试验结果表明，在矿浆质量浓度为30%，粗选NaOH用量为600g/t，水玻璃用量为3000g/t，EF1106用量为3500g/t，起泡剂用量为60g/t情况下，采用一粗、三精、两扫、中矿按顺序返回的选矿流程，可获得稀土REO的品位和回收率分别为66.32%和79.88%的稀土浮选精矿。与该选厂的生产指标相比，稀土回收率提高了13.93%。     

Analysis of Phytochemical Composition of Camellia oleifera Oil and Evaluation of its Anti-Inflammatory Effect in Lipopolysaccharide-Stimulated RAW 264.7 Macrophages

In China, Camellia oleifera oil (COO) is not only a common edible oil but also a traditional remedy widely applied to ameliorate a variety of illnesses associated with inflammation, such as mouth ulcers, thrush, eczema, etc. However, there has been a lack of relevant biological research on the anti-inflammatory capacity of COO, and the specific bioactive lipid phytochemicals contributing to the anti-inflammatory effect need further research. In this study, the RAW 264.7 macrophages model was used to investigate the anti-inflammatory capacity of COO. Our data showed that 33–200 μg/mL COO markedly inhibited the lipopolysaccharide lipopolysaccharide (LPS)-stimulated nitric oxide (NO.) secretion via the suppression of Nos2 and Cox-2 expression. The enzyme immunoassay confirmed that COO also exhibited a strong suppressive effect on the expression of proinflammatory cytokines such as Tnf-α and Il-6. To further explore the correlation between the anti-inflammatory effects and the lipid phytochemicals in COO, 10 samples were collected and screened for their chemical compositions. It was interestingly demonstrated that the polyphenol extracts of COO play a vital role in its anti-inflammatory properties. In addition, an oil-in-water (O/W) emulsion-based system was also developed to deliver the liposoluble COO into the cells, and the feasibility of this system was confirmed. Our research confirms the anti-inflammatory potential of COO and highlights that the main functional ingredient is polyphenol extracts. This may provide a scientific basis for the comprehensive utilization and development of COO and related functional foods.