基于GF-3的不同极化方式SAR图像海面油膜识别的比较 ——以"桑吉"轮事故为例

基于我国自主研发的首颗分辨率达到1m的C频段多极化合成孔径雷达高分三号卫星(GF-3),通过典型溢油案例定性和定量地比较了双极化与单极化图像预处理性能,分析了不同的极化组合对海面油膜识别结果的影响。得出结论:同向极化与异向极化成像差异明显,VV极化明显比VH极化回波强度高,并且油膜识别度较高;相反,双极化VHVV方式与单极化VH方式图像效果区别不大,双极化方式并不能绝对性地提高地物识别度。     

和田玉的鉴定与评估

新疆和田玉是世界软玉品种中最好的一种,有“玉王”之称。该文对和田玉的矿物组成、化学成分及物理性质进行了鉴定分析,提出了和田玉原料及玉器的评估方法。     

Vision-based tracking with projective mapping for parameter identification of remotely operated vehicles

Parameter identification of a remotely operated vehicle (ROV) is often based on the dynamic responses collected by its onboard sensors. However, for commercial ROVs, the required data for identification may not be available due to the absence of suitable sensors or limitations in accessing onboard sensor data. Therefore, this study proposes a vision-based tracking system to measure the dynamic response of an ROV. The tracking system is independent of the ROV, and is able to localize an ROV to a high degree of precision by means of projective mapping. The validity of the proposed tracking system is demonstrated through identification of a commercial ROV. A simplified nonlinear ROV dynamic model with six degrees of freedom (DOF) is used for identification. Uncoupled motions, including surge, sway, and yaw, are obtained from the ROV dynamic model, and the corresponding experiments are carried out for each DOF. Hydrodynamic parameters are then estimated with numerical optimizations by comparing the measured ROV responses with the output of the mathematical model. The experimental results show that the vision-based tracking system can accurately measure the transient and steady-state responses of an ROV. Additionally, the simulations of the ROV dynamic model, with the optimal parameter estimates, give results in agreement with the measured data.     

System identification for nonlinear maneuvering of large tankers using artificial neural network

This paper deals with the application of nonparametric system identification to a nonlinear maneuvering model for large tankers using artificial neural network method. The three coupled maneuvering equations in this model for large tankers contain linear and nonlinear terms and instead of attempting to determine the parameters (i.e. hydrodynamic derivatives) associated with nonlinear terms, all nonlinear terms are clubbed together to form one unknown time function per equation which are sought to be represented by the neural network coefficients. The time series used in training the network are obtained from simulated data of zigzag maneuvers and the proposed method has been applied to these data. The neural network scheme adopted in this work has one middle or hidden layer of neurons and it employs the Levenberg–Marquardt algorithm. Using the best choices for the number of hidden layer neurons, length of training data, convergence tolerance etc., the performance of the proposed neural network model has been investigated and conclusions drawn.     

养殖大菱鲆细菌性红体病病原菌的分离与鉴定

从患有红体病的养殖大菱鲆(Scophthalmus maximus)的肌肉中分离得到一株优势菌并记为H1.经人工注射感染证实H1即为引起养殖大菱鲆红体病的病原菌,其半致死量LD50为2.82×105CFU/mL,而低浓度(1.41×103 CFU/mL)没有造成死亡,但注射部位有脓肿现象,注射相同体积1.5%无菌生理盐水的对照组没有明显的症状,注射部位也无异常.革兰氏染色显示该菌为革兰氏阴性,菌体呈杆状,周生鞭毛.综合该菌的形态、常规生理生化特征和API32E鉴定结果,发现H1与迟钝爱德华氏菌的表性特征非常相似,相似率迭到99.9%.在分子水平上对其16SRNA基因序列的测定,同源性分析,结果表明H1与迟钝爱德华氏菌的亲缘关系最近,相似度达到99%.综合上述研究结果,将该菌株初步鉴定为迟钝爱德华氏茵(Edwardsiella tarda).     

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冬季刺参养殖环境与肠道内细菌菌群的研究

运用传统细菌分离培养与分子生物学技术相结合的方法,对2008年11月至2009年1月冬季刺参(Apostichopus japonicus Liao)养殖池塘环境(养殖水、底泥、附着基)及刺参肠道内的细菌菌群进行了分析。应用平板稀释涂布培养计数法测得刺参养殖池塘水体、底泥、附着基和肠道细菌数量分别为0.75×102～1.4×104cfu/mL、8.7×104～8.1×105cfu/g、3.8×105～2.8×106cfu/g、7.1×105～1.5×107cfu/g;根据形态学差异从培养所得的细菌中筛选得到22株菌,用限制性内切酶Rsa I和Msp I对所分离菌株进行ARDRA(Amplified rDNA Restriction Analysis)分析,这22株菌被分为8种不同的分类单元(Operational Taxonomic Unit,OTU),其中OTU2与OTU3所包含的菌株分别占分离菌株种数的30%和20%;此外,作者对不同环境培养所得的优势度最高的细菌进行分子鉴定分析。结果表明:水环境中优势菌为施氏假单胞菌(Pseudomonas stutzeri)、门多萨假单胞菌(Pseudomonas mendocina)及巨大芽孢杆菌(Bacillus megaterium),沉积物中优势菌为巨大芽孢杆菌(B.megaterium)、施氏假单胞菌(P.stutzeri)、苏云金芽孢杆菌(Bacillus thuringiensis),附着基中优势菌为巨大芽孢杆菌(B.megaterium)、苏云金芽孢杆菌(B.thuringiensis),灿烂弧菌(Vibrio splendidus),肠道中优势菌为巨大芽孢杆菌(B.megaterium)、苏云金芽孢杆菌(B.thuringiensis),灿烂弧菌(V.splendidus)、施氏假单胞菌(P.stutzeri)。通过对冬季刺参池塘细菌菌群多样性分析和优势菌鉴定,为筛选低温益生菌和防治刺参疾病提供了有益参考。     

长江口表层沉积物矿物磁性分区特征及其沉积环境指示意义

本研究旨在揭示现代长江口不同沉积环境铁磁性矿物的分布差异,寻找有效识别河口-陆架沉积环境的磁学指标,以便更好地将环境磁学应用于河口古环境研究。在长江口及邻近陆架的6个沉积环境:汊道、拦门沙、三角洲前缘斜坡、前三角洲、前三角洲-陆架过渡区和残留砂区,采集表层沉积物样品,进行粒度和磁性测量。结果显示,χ和SIRM在汊道和拦门沙呈现显著高值,HIRM、χfd%、χARM、χARM/χ和χARM/SIRM在前三角洲和前缘斜坡呈现显著高值,反映了陆源物质输运距离和河口沉积动力对磁性矿物分布的控制作用。因此,参数组合HIRM、χARM、χARM/χ和χARM/SIRM可用于识别全新世地层前缘斜坡和前三角洲-陆架;参数组合χ、SIRM和S-20mT可尝试用于识别汊道和拦门沙环境。     

基于角质颚长度的头足类种类判别

本文根据2013 年8 月于舟山市沈家门东河菜场采集的5 种近海常见经济头足类(剑尖枪乌 贼、杜氏枪乌贼、金乌贼、曼氏无针乌贼和短蛸), 利用逐步判别和主成分分析法对其上、下角质颚 的各5 种长度指标(喙长、头盖长、脊突长、侧壁长、翼长)进行分析。结果显示, 这5 种头足类角质 颚长度差异显著(ANOVA: P<0.001), 其中以金乌贼的角质颚尺寸最大, 短蛸的角质颚尺寸最小。判 别分析显示, 角质颚长度适合用来划分头足类的种类, 综合判别成功率为96.2%, 其中以上颚侧壁 长、上颚头盖长和下颚脊突长对判定的贡献率最高。然而, 与之相比, 标准化后的角质颚长度则更适 合用来划分头足类的种类, 综合判别成功率达到100%, 其中以标准化下颚喙长和标准化下颚翼长对 判定的贡献率最高。主成分分析显示, 角质颚长度及标准化后角质颚长度对枪乌贼类和乌贼类的判 定成功率均达到100%.本文建立了一种基于角质颚长度判别分析法的头足类种类判定的新方法, 丰 富了头足类种类鉴定的技术手段, 为我国学者在相关领域的研究提供了基础。