基于短时傅里叶变换的干扰信号识别方法

目的提高无线电引信识别欺骗式干扰的能力。方法根据炮弹弹体自旋的特点,使得采用连续波线极化天线的无线电引信所收到的干扰信号呈现出有别于地面回波的周期性幅度调制特征,通过对此特征进行短时傅里叶变换后进行识别,可以作为无线电引信是否受到欺骗式干扰的判断依据。结果通过仿真和试验对方法的可行性进行了验证,表明该识别方法可以很好地提高连续波无线电引信的识别欺骗式干扰的能力。结论基于短时傅里叶变换检测旋转调制的对地旋转弹无线电引信欺骗干扰识别的方法可以对干扰信号特征进行识别,算法处理时间短,能够作为引信是否受到干扰的一种判断依据。     

福州乌鸦咀泉水电导率幅频谱分析初探

地震观测数据受各种周期性因素影响，其动态曲线表现为周期性变化特征，是大小不同的周期和非周期因素相互作用的结果。利用MATLAB工具包，编程幅频分析和滤波程序，以福州乌鸦咀泉水电导率的模拟观测数据为例，对其幅频谱特征和震例进行初步探讨。     

DPIV技术测量流冰速度应用研究

基于数字信号分析原理,对连续两幅图像进行互相关分析,寻找互相关函数的峰值;应用数字粒子图像测速(digital particle image velocimetry)技术,并通过计算机VC编程,解决了用于雷达测量单点流冰速度的不足;为大范围区域内流冰场瞬时速度的计算,实时雷达测量辽东湾海上流冰速度场提供了有应用价值的方法.     

元磨高速公路边坡生物防护技术研究

对云南元磨高速公路的边坡生物防护的植物筛选技术和施工工艺进行了研究。试验探索了湿法喷播中草灌的比例问题，发现了短萼灰叶(山毛豆)是适宜的灌木种，并提出了“两步施工法”。     

生活中的“风险”

生活中的“风险”,随处都有。 头号“风险”,当数癌症。据有关资料显示,在我国,每年有160万人患癌,每年有130万人死于癌症,并且每年癌症患者以3％的速度在递增。在上海,目前癌症发病率约占全市人口的千分之二至三。据统计,上海男性每年死亡人数中近三分之一死于恶性肿瘤;女性每年死亡人数中近四分之一死于恶性肿瘤。按这两个数据计算,100对死亡夫妻中,可能有5对夫妻同时患     

中国盾叶薯蓣资源现状及保护对策

论述了我国盾叶薯蓣的野生资源现状、人工种植生产现状、资源濒危原因及应采取的保护对策.指出:我国现有盾叶薯蓣野生资源蕴藏量估计在200万kg左右,资源数量已大为下降,然而年需求量却高达2亿kg以上,供需矛盾十分突出.造成资源濒危的主要原因是利用过度、生境及种质资源被破坏、家种者皂素含量低且质量差而不能大批量用于皂素生产.建议在采取有效保护野生资源的同时,尽快建立全国性良种繁育基地,按GAP要求建立我国现代化、规模化、规范化的高产优质药材原料生产基地,从根本上解决当前盾叶薯蓣资源保护与利用的矛盾.     

植物叶表大气降尘的采集和定量分析方法研究

随着工业化和城市化的快速发展,大气颗粒物污染形势严峻,对人体健康和生态环境都造成危害,其中危害植物的典型形式就是叶表降尘。虽然植被具有净化空气的滞尘能力,但是大气降尘也会在植物叶片表面长期积累进而通过影响光合作用、阻塞气孔等对植物的正常生长或作物产量造成不利影响。因此,作物叶表降尘的采集方法和降尘特征研究具有十分重要的现实环境意义,然而由于叶表降尘的"微量"特点,目前可行的能准确收集全部叶表降尘并进行定量的方法非常少,而且通常不能获得降尘样品供后续分析使用。该方法利用针筒与针头过滤器组合将降尘直接洗入针筒并通过微孔滤膜截留,再用叶面积仪确定单位叶面积降尘量,避免了降尘损失和称量误差,且能完整定量收集降尘样品供重金属污染物成分等物理化学分析,在环境科学和生态保护领域具有广泛的应用前景。     

基于OP-FTIR技术的炼油装置VOCs排放量监测

随着挥发性有机物排污收费政策的逐步实施,快速准确地监测企业VOCs排放量已成为环保部门和企业共同面对的难题。介绍了开路式傅里叶变换红外光谱技术原理及优势,研究了质量通量模式VOCs排放量计算方法,并以300 m×300 m某装置区域为例,完成了现场红外光谱测量、气象数据采集、数据有效性分析和VOCs排放量计算。研究结果表明,开路红外光谱技术极大提高了VOCs排放数据采集效率和准确性,进一步计算得出该装置区域VOCs年排放量平均值为98.7 t,为企业开展VOCs排放量核算提供了参考。     

Degradation of direct azo dye by Cucurbita pepo free and immobilized peroxidase

Enzymatic decolourization of the azo dye, Direct Yellow (DY106) by Cucurbita pepo (courgette) peroxidase (CP) is a complex process, which is greatly affected by pH, temperature, enzyme activity and the concentrations of H₂O₂ and dye. Courgette peroxidase was extracted and its performance was evaluated by using the free-CP (FCP) and immobilized-CP (ICP) forms in the decolourization of DY106. Immobilization of peroxidase in calcium alginate beads was performed according to a strategy aiming to minimize enzyme leakage and keep its activity at a maximum value by optimizing sodium alginate content, enzyme loading and calcium chloride concentration. The initial conditions at which the highest DY106 decolourization yield was obtained were found at pH 2, temperature 20℃, H₂O₂ dose 1 mmol/L (FCP) and 100 mmol/L (ICP). The highest decolourization rates were obtained for dye concentrations 50 mg/L (FCP) and 80 mg/L (ICP). Under optimal conditions, the FCP was able to decolorize more than 87% of the dye within 2 min. While with ICP, the decolourization yield was 75% within 15 min. The decolourization and removal of DY106 was proved by UV-Vis analysis. Fourier transform infrared (FT-IR) spectroscopy analysis was also performed on DY106 and enzymatic treatment precipitated byproduct.     

Fe2O3 particles as superior catalysts for low temperature selective catalytic reduction of NO with NH3

Fe203 particle catalysts were experimentally studied in the low temperature selective catalytic reduction （SCR） of NO with NH3. The effects of reaction temperature, oxygen concentration, [NH3]/[NO] molar ratio and residence time on SCR activity were studied. It was found that Fe203 catalysts had high activity for the SCR of NO with NH3 in a broad temperature range of 150-270℃, and more than 95% NO conversion was obtained at 180℃ when the molar ratio [NH3]/[NO] = 1, the residence time was 0.48 seconds and 02 volume fraction was 3%. In addition, the effect of SO2 on SCR catalytic activity was also investigated at the temperature of 180℃. The results showed that deactivation of the Fe2O3 particles occurred due to the presence of SO2 and the NO conversion decreased from 99.2% to 58% in 240 min, since SO2 gradually decreased the catalytic activity of the catalysts. In addition, X-ray diffraction, Thermogravimetric analysis and Fourier transform infrared spectroscopy were used to characterize the fresh and deactivated Fe2O3 catalysts. The results showed that the deactivation caused by SO2 was due to the formation of metal sulfates and ammonium sulfates on the catalyst surface during the de-NO reaction, which could cause pore plugging and result in suppression of the catalytic activity.