Characteristics of metabolism during prolonged water immersion

The effect on the organism of a 12-day stay in a water immersion medium (head on the water surface) was studied on 10 subjects. The condition of the metabolic processes in the subjects was judged from the investigation of the parameters of protein and carbohydrate metabolism, acid-base equilibrium, the activity of a number of enzymes and steroid hormones. The venous blood and diurnal urine served as the material for conducting the corresponding biochemical determinations. The stay in an immersion medium is accompanied by a significant increase in the content of residual nitrogen in the blood, by a reduction of the creatinine content in the blood and by an increase of the creatine content of the blood with the simultaneous increase of the excretion of creatinine and creatine with the urine, by a significant increase of the glucose and lactate content in the blood, by the development of acidosis of a respiratory and metabolic character, as well as by a significant increase of the activity of creatine phosphokinase and the isoenzyme fraction of lactate dehydrogenase3. In all the subjects, an expressed intensification of the glucocorticoid and androgenic functions of the adrenal cortex is noted during the experimental period.     

利用κ—ε湍流能量闭合方法对城市街渠内气流结构的模拟

利用非静力、能量闭合的大气边界层模式分别绎二维情况下不同高宽比的街渠内部的气流结构和三维情况下城市街渠在来流方向不同的条件下的内部气流结构进行了数值模拟。并且对三维情况下街渠的上风向建筑物顶部的风向与街渠中心近地面的风向之间的关系和街渠内部上层的风向与街渠中心近地面的风向之间的关系进行了模拟研究，将这些结果与G T Johnson等人的现场观测和模式模拟结果进行了比较，表明两者有较好的一致性。     

高精度展开锁定机构数字化装调技术研究

通过对展开锁定机构的轴系同轴度进行合理分解,得到三轴系之间的同轴度为0.073mm,同时展开重复精度提高了35%。设计合理的装配固定装置作为重复装配的基准,控制产品与装置之间间隙在0.02mm以内,提高装配效率和精度。通过选用合适部位作为测试基准,将参数进行量化处理,保证在重复拆装过程中轴系位置误差在0.015mm以内。     

一种自适应控制增稳方案的实时仿真研究

 本文介绍一种侧向自适应控制增稳方案的实时数模混合仿真研究工作。内容包括软件设计编制和系统试验分析。研究结果表明:系统软件设计合理,运算精度高,稳定可靠;自适应控制增稳方案具有良好的自适应功能;带有该系统的飞机飞行品质满足MIL-F-8785C和MIL-F-9490C的要求。文章在最后指出了今后研究工作的方向和应解决的问题。     

转动惯量测量研究的进展及展望

对转动惯量测量的研究情况作了综述,对三线摆法、扭摆法、落体法等转动惯量测量方法的测量原理及其优缺点进行了总结,介绍了针对以上缺点的一种新的测量方法,预测该方法将代表转动惯量测量的发展方向。     

基于时频域转换及雨流法的电子设备随机振动概率疲劳损伤预测

针对电子设备随机振动疲劳损伤存在高度的不确定性问题,提出了一种基于频时域转换及雨流法的概率疲劳损伤预测方法,用于预测某航空电子设备在特定随机振动载荷条件下的疲劳损伤分布。通过采用“等效单元谱”近似计算,本文提出的方法能够在短时间内给出电子设备的损伤概率分布,且计算得到的疲劳寿命均值与试验结果吻合较好。因此在开展复杂功率谱密度（Power spectral density, PSD）载荷谱作用下的随机振动疲劳损伤计算时,具有计算效率高、工程适应性强等优势。     

Application of the Mars Organic Analyzer to nucleobase and amine biomarker detection

The Mars Organic Analyzer (MOA), a portable microfabricated capillary electrophoresis instrument being developed for planetary exploration, is used to analyze a wide variety of fluorescamine-labeled amine-containing biomarker compounds, including amino acids, mono and diaminoalkanes, amino sugars, nucleobases, and nucleobase degradation products. The nucleobases cytosine and adenine, which contain an exocyclic primary amine, were effectively labeled, separated, and detected at concentrations <500 nM. To test the general applicability of the MOA for biomarker detection, amino acids and mono- and diamines were extracted from bacterial cells using both hydrolysis and sublimation followed by analysis. The extrapolated limit of detection provided by the valine biomarker was approximately 4 x 10(3) cells per sample. Products of an NH(4)CN polymerization that simulate a prebiotic synthesis were also successfully isolated via sublimation and analyzed. Adenine and alanine/serine were detected with no additional sample cleanup at 120 +/- 13 microM and 4.1 +/- 1 microM, respectively, corresponding to a reaction yield of 0.04% and 0.0003%, respectively. This study demonstrates that the MOA provides sensitive detection and analysis of low levels of a wide variety of amine-containing organic compounds from both biological and abiotic sources.     

交互多模型PHD滤波跟踪多目标方法

在机动多目标跟踪问题中,目标数未知或随时间而变化,概率假设密度（PHD）滤波可以在每一时间步估计多目标状态和目标数,但单模型方法不能给出精确的估计。提出了一种交互多模型PHD滤波方法,建立多模型描述多目标运动方式,利用PHD滤波结合多模型跟踪目标运动轨迹。同时,给出了多传感器交互多模型PHD滤波方法,以提高目标跟踪精度。     

固体火箭发动机卧式贮存状态界面应力数值分析

根据推进剂的材料特性及受载,用线粘弹性理论在ANSYS有限元软件中建立了某长期无翻转卧式贮存固体火箭发动机燃烧室筒段的有限元模型。计算了实际贮存、真空和高压三种典型状态下危险部位的界面应力。该方法对发动机的免维修和寿命预估有一定的参考价值。     

基于空谱融合特征主动学习的高光谱图像分类

针对高光谱图像分类过程中存在的样本量少和分类精度低的问题,提出一种基于空谱融合特征主动学习的高光谱图像分类方法。主要包括构造三通道图像,全卷积网络提取空间特征,空谱特征结合,主动学习方法选择训练样本几个部分。通过结合像素的光谱特性和相邻像素间的空间关联,提取出可以反映像素空谱联合特性的综合特征,提高了像素特征的表达能力。为克服高光谱图像标注数据少、缺乏训练样本的问题,应用主动学习算法,充分选择更具有代表性的样本进行训练,达到少样本情况下较高的分类正确率。通过在标准数据集上进行实验,结果表明:该方法可以达到在总样本数1%作训练样本的情况下,分类正确率达到99.79%,优于传统的高光谱分类算法。