Effect of Poly(methacrylic acid) on the Cytokine Level in an In Vivo Tumor Model

Cancer is a leading cause of mortality globally. Despite remarkable improvements in cancer-treatment approaches, disease recurrence and progression remain major obstacles to therapy. While chemotherapy is still a first-line treatment for a variety of cancers, the focus has shifted to the development and application of new approaches to therapy. Nevertheless, the relationship between immune response, neoplastic diseases and treatment efficiency is not fully understood. Therefore, the aim of the study was to investigate the immunopharmacological effects of methacrylic acid homopolymer in an in vivo tumor model. Materials and methods: Monomeric methacrylic acid was used to synthesize polymers. Methacrylic acid was polymerized in dioxane in the presence of 4-Cyano-4-[(dodecylsulfanylthiocarbonyl)sulfanyl]pentanoic acid. To study the molecular weight characteristics of PMAA by GPC, carboxyl groups were preliminarily methylated with diazomethane. An experimental cancer model was obtained by grafting RMK1 breast cancer cells. The serum levels of IL-6, IL-10, IL-17, transforming growth factor β1 (TGF-β1), and tumor necrosis factor α (TNF-α) were measured by ELISA. Results: The effect of PMAA on the serum concentrations of several cytokines was studied upon its single administration to laboratory animals in early neoplastic process. The IL-6, IL-17 and TGF-β1 concentrations were found to change significantly and reach the level observed in intact rats. The IL-10 concentration tended to normalize. Conclusion: The positive results obtained are the basis for further studies on the effect of methacrylic-acid polymers with different molecular-weight characteristics on the neoplastic process.     

Intelligent Fault Diagnosis of Industrial Robot Based on Multiclass Mahalanobis-Taguchi System for Imbalanced Data

One of the biggest challenges for the fault diagnosis research of industrial robots is that the normal data is far more than the fault data; that is, the data is imbalanced. The traditional diagnosis approaches of industrial robots are more biased toward the majority categories, which makes the diagnosis accuracy of the minority categories decrease. To solve the imbalanced problem, the traditional algorithm is improved by using cost-sensitive learning, single-class learning and other approaches. However, these algorithms also have a series of problems. For instance, it is difficult to estimate the true misclassification cost, overfitting, and long computation time. Therefore, a fault diagnosis approach for industrial robots, based on the Multiclass Mahalanobis-Taguchi system (MMTS), is proposed in this article. It can be classified the categories by measuring the deviation degree from the sample to the reference space, which is more suitable for classifying imbalanced data. The accuracy, G-mean and F-measure are used to verify the effectiveness of the proposed approach on an industrial robot platform. The experimental results show that the proposed approach’s accuracy, F-measure and G-mean improves by an average of 20.74%, 12.85% and 21.68%, compared with the other five traditional approaches when the imbalance ratio is 9. With the increase in the imbalance ratio, the proposed approach has better stability than the traditional algorithms.     

Review of Fluorescence Spectroscopy in Environmental Quality Applications

Fluorescence spectroscopy is an optical spectroscopic method that has been applied for the assessment of environmental quality extensively during the last 20 years. Most of the earlier works have used conventional light sources in spectrofluorometers to assess quality. Many recent works have used laser sources of light for the same purpose. The improvement of the energy sources and of the higher resolution spectrometers has led to a tremendous increase in applications. The motivation for the present review study is the increasing use of laser sources in environmental applications. The review is divided in two parts. The fundamental principles of fluorescence spectroscopy are described in the first part. The environmental applications are described in the second part.     

多旋翼无人机任务系统

随着我国科学技术的不断完善,无人飞行载具,也受到了广泛的重视和应用,目前以应用到航空摄影、灾情监视、交通巡逻、治安监控等领域,随着市场应用趋势不断的发展,对于无人机的自动控制技术,提出了更多的要求,对此本文就无人多旋翼任务系统,结合其无人机定义,以及技术创新点等进行分析,希望对于我国多旋翼无人机市场的稳定发展,奠定良好的基础。     

A signal theory approach to the space and frequency variant filtering performed by the human visual system

A mathematical representation is given of the processing performed by the peripheral nervous cells of the human visual system. This representation consists essentially of a set of shift-variant convolutions, implying non-uniform resolutions in both the space and frequency domains. A remarkable property of such “convolutions” is the form-invariance of their outputs with respect to (size) linear scalings of the inputs. It is shown that this latter property is a necessary support of the hypothesis according to which the visual system translates linear scalings of the (retinal) inputs into shifts of the (cortical) outputs.     

基于红外辐射特性的单波段红外图像被动测距

以单波段红外图像被动测距为研究背景,首先分析了凝视型红外探测系统的工作原理,将其工作过程分为入瞳前和入瞳后两个不同的阶段,其中第一阶段与目标距离相关,而第二阶段则决定于红外探测系统本身的传递函数,而后对图像像素灰度与入瞳处辐亮度之间的关系进行了表述;然后针对点目标与面目标的成像特点,分别计算了相应的目标与背景的入瞳处幅亮度差,得出:两者的红外辐射特性存在一致性.基于短时间内目标近似匀速运动的假设,推导了单波段红外图像被动测距方法.最后利用外场实测中长波红外图像对该算法进行了验证,并对测距结果和测距误差进行了详细分析.     

可编程直接序列扩频通信系统的数字化实现

本文讨论了利用ASIC芯片和CPU实现直接序列扩频系统数字化的方法,阐述了各部分电路的设计思路,给出了系统总体框图及实验系统的信号波形。     

基于DF-OFDM多中继系统功率分配的梯度算法

DF-OFDM技术必将成为现代移动通信的核心技术,但是合理地进行功率分配是必须要解决的问题之一。传统的二分法,大多在精确度和计算量之间很难取舍。在移动通信系统抗信道衰落和提高信道容量方面,协作通信是一种很好的解决方案。针对改进型的多中继DF-OFDM系统,对一种降低计算量的梯度算法进行了简单的介绍与分析,并与二分法进行了比较。仿真结果表明,在功率约束的条件下,梯度法要优于二分法。     

湍流大气中光强闪烁对光通信链路的影响

给出了用大气传输通信设备进行传输距离 3.4 km外场试验光强闪烁对光通信链路影响的实验结果 ,并简要分析了光强闪烁对信号检测的影响和误码原因     

高层长途电信枢纽楼几种典型结构体系技术经济比较

通过对信息产业部设计院及北京邮电设计院近几年设计完成的几种长途电信枢纽楼结构设计进行分析、研究、归纳出几种典型结构体系在不同高度、不同地震设防烈度情况下的技术性能及经济指标。指出了可供电信枢纽楼结构体系选择时参考的倾向性意见。