基于经验模态分解和小波分解估算海气通量涡相关计算中的截断时间尺度

基于时长38天的海表风场实测数据,应用经验模态分解(EmpiricalModeDecomposition,EMD)和小波分解(Wavelet Decomposition, WD)这两种数据处理方法首先对涡相关法中的截断时间尺度(CutoffTimescale,CTS)进行估算,结果显示:基于EMD与WD方法估算出的CTS一般都在40秒左右(EMD的结果略小),远远小于传统涡相关法中CTS的取值(固定为10分钟),且EMD和WD的使用使得每一段数据都能够根据自身的湍流特点而获得合适的CTS; EMD方法和WD方法有效的去除了计算结果中的非湍部分,且对通量传输方向的刻画也更加合理,极大提高了通量的计算精度,所得通量与传统方法计算的通量偏差平均值高达45%;研究还对EMD和WD的优缺点进行了对比分析,结果表明EMD相比于WD有更高的自主性,而WD对信号的分离程度则更高。     

连云港近海紫菜养殖区遥感识别、空间变异和驱动分析

为了科学有效地掌握海域使用信息、管理海域权属,为海域资源调查、管理、规划、保护、合理利用提供服务,为违法、违规、违章用海项目得到有效遏制,减少用海矛盾,有必要开展海域使用动态监测,作者以连云港近海为研究区,利用4个时相Landsat遥感影像(2002、2008、2013、2016年)通过面向对象算法提取弱水背景下的紫菜养殖区信息,揭示空间分异规律,并分析其驱动原因。研究结果表明:4期影像提取连云港近海紫菜养殖区信息的精度分别是87.5%、92%、91.7%和94.6%。紫菜养殖区空间分布的变化规律为紫菜养殖面积不断增加且整体向深海方向推进。赣榆港口航运区和田湾核电站特殊利用区存在少量紫菜养殖区,项目用海不符合连云港市海洋功能区划(2016～2020年)。连云港近海紫菜养殖区空间分异的驱动因子主要是自然条件、养殖技术、海洋经济和社会发展四大因素。     

虾夷扇贝天然苗种筛选装置的研究与应用

随着贝类底播增养殖产业的迅猛发展,为保证底播贝苗的成活率,养殖企业对天然苗种更加重视。天然苗种采用中间育成方法,需要对苗种进行筛选作业,但目前筛选作业仍以人工作业为主,存在作业效率低、劳动强度大等问题。作者通过对大连地区虾夷扇贝(Patinopecten yessoensis)天然苗种筛选作业调研的基础上,设计了满足生产实际需求的扇贝苗种筛选装置,可实现3种规格贝苗的筛选作业。试验分2阶段进行,第1阶段对影响筛选准确性的因素进行正交分析于验证,确定了最佳工艺参数;第2阶段在大连旅顺进行的生产性对比试验得出,机械筛选的平均准确率为91.33%,误差率低于10%,且5组筛选结果无显著性差异(P0.05);同时机械筛选的平均作业效率为80g/(人/min),约为人工筛选作业效率的8倍。由此说明扇贝苗种筛选装置具有较高的准确性、稳定性和高效性,具有推广应用价值。     

Establishment and application of an intelligent treating method for oil spill identification

In the identifying process of an oil spill accident, manual integral and artificial visual comparison are commonly used at present to determine the oil spill sources, these methods are time-consuming and easily affected by human factors. Therefore, it is difficult to achieve the purpose of rapid identification of an oil spill accident. In this paper, an intelligent method of automatic recognition, integration and calculation of diagnostic ratio of Gas Chromatography-Mass Spectrometer (GC/MS) spectrum are established. Firstly, four hundreds of samples collected around the world were analyzed using a standard method and Retention time locking technology (RTL) was applied to reduce the change of retention time of GC/MS spectrum. Secondly, the automatic identification, integration of n-alkanes, biomarker compounds, polycyclic aromatic hydrocarbons and calculation of the diagnostic ratios were realized by MATLAB software. Finally, a database of oil fingerprints were established and applied successfully in a spill oil accident. Based on the new method and database, we could acquire the diagnostic ratios of an oil sample and find out the suspected oil within a few minutes. This method and database can improve the efficiency in spilled oil identification.     

Enhanced a novel β-agarase production in recombinant Escherichia coli BL21(DE3) through induction mode optimization and glycerol feeding strategy

Agarases are hydrolytic enzymes that act on the hydrolysis of agar and have a broad range of applications in food,cosmetics and pharmaceutical industries. In this study, a glycerol feeding strategy based on induction mode optimization for high cell density and β-agarase production was established, which could effectively control acetate yield. First, exponential feeding strategy of glycerol with different overall specific growth rates(μ) was applied in the pre-induction phase. The results showed that the low μ(μ=0.2) was suggested to be the optimal for cell growth and β-agarase production. Second, the effects of induction temperature and the inducer concentration on cell growth and β-agarase production were investigated in the post-induction phase. When induced by isopropyl-β-d-thiogalactoside(IPTG), the strategy of 0.8 mmol/L IPTG induction at 20℃ was found to be optimal for β-agarase production. When cultivation was induced by continuous lactose feeding strategy of 1.0 g/(L·h), the β-agarase activity reached 112.5 U/mL, which represented the highest β-agarase production to date.Furthermore, the β-agarase was capable of degrading G. lemaneiformis powder directly to produce neoagarooligosaccharide, and the hydrolysates were neoagarotetraose(NA4) and neoagarohexaose(NA6). The overall research may be useful for the industrial production and application of β-agarase.     

多极化SAR溢油探测影响因素分析研究

Polarimetric synthetic aperture radar(SAR) oil spill detection parameters conformity coefficient(μ), Muller matrix parameters(|C|, B_0), the eigenvalues of simplified coherency matrix(λ_(nos)) and the influence of SAR observing parameters, ocean environment and noise level are investigated. Radarsat-2 data are used to make systematic analysis of polarimetric parameters for different incidences, wind speeds, noise levels and the ocean phenomena(oil slick and look likes). The influence of the SAR observing parameters, the ocean environment and the noise level on the typical polarimetric SAR parameter conformity coefficient has been analyzed. The results indicate that conformity coefficient cannot be simply used for oil spill detection, which represents the image signal to the noise level to some extent. When the signals are below the noise level for the oil slick and the look likes, the conformity coefficients are negative; while the signals above the noise level corresponds to positive conformity coefficients. For dark patches(low wind and biogenic slick) with the signal below the noise,polarization features such as conformity coefficient cannot separate them with oil slick. For the signal above the noise, the oil slick, the look likes(low wind and biogenic slick) and clean sea all have positive conformity coefficients, among which, the oil slick has the smallest conformity coefficient, the look likes the second, and the clean sea the largest value. For polarimetric SAR data oil spill detection, the noise plays a significant role. So the polarimetric SAR data oil spill detection should be carried out on the basis of noise consideration.     

热带西太平洋砂壳纤毛虫的多样性

为了探明热带西太平洋海区砂壳纤毛虫的多样性、垂直分布及纬向变化,我们于2012年11-12月在该海区四个断面采集了0-200 m的水样。共检出砂壳纤毛虫39属124种,多数种类喜好生活在表层和次表层。砂壳纤毛虫种丰富度、丰度以及多样性指数的高值主要出现在比叶绿素浓度最大值稍浅的位置,与温度和叶绿素浓度显著正相关,与盐度和采样深度显著负相关。多数优势种与环境因子间的相关性不显著。热带西太平洋海区砂壳纤毛虫多样性极高,各站种丰富度在25-52之间。在从表层至75 m处的多数采样点香农指数均大于3。该海区砂壳纤毛虫冗余种的比例很高,占砂壳纤毛虫总种类数的87.90%,贡献了砂壳纤毛虫60.38%的丰度,表明热带西太平洋海区砂壳纤毛虫群落对饵料组成和摄食压力改变的应对能力很强,稳定性很高。     

太平洋深海沉积物来源的菌株Tenacibaculum sp.HMG1对孔雀石绿降解特性的研究

本文在太平洋深海沉积物中分离得到一株孔雀石绿降解菌株,鉴定命名为Tenacibaculum sp.HMG1。通过菌株生长实验和高效液相色谱的研究表明, HMG1菌株可以在20 mg/L的孔雀石绿中维持较快的生长速率,并且在12 h内可降解98.8%的孔雀石绿,这证明该菌株具有很高的孔雀石绿耐受能力和降解活性。通过基因组测序在HMG1菌株发现一条过氧化物酶基因可能参与了孔雀石绿的降解,随后利用原核表达获得了相应的重组蛋白。实验表明,该重组过氧化物酶具有极强的活性,可在1000 mg/L的孔雀石绿中发挥降解功能。本文利用液相色谱-质谱联用（LC-MS）技术对孔雀石绿的菌株降解产物和重组酶降解产物进行鉴定,并基于鉴定结果推测了两种降解途径。结果发现两种降解方式存在共同的降解途径。此外,孔雀石绿降解条件的实验结果证明重组过氧化物酶可以在低温（20℃）、复杂的pH值（6.0–9.0）、高盐度（100 mmol/L）、金属离子和EDTA等反应条件下依旧维持很高的孔雀石绿降解活性。以上实验结果表明,HMG1菌株和重组过氧化物酶均在孔雀石绿污染生物修复方面具有很大潜力。     

基于GNSS的LEO卫星TRAIM可用性算法及分析

详细研究了基于GNSS的LEO卫星接收机授时自主完好性（TRAIM）故障检测数学模型以及可用性算法。以GPS和BDS组合为例,分别对500 km、650 km、800 km和1 400 km等几种典型轨道高度的卫星,开展基于GNSS的LEO卫星TRAIM可用性仿真分析。结果表明,在告警阈值100 ns时,基于GPS+BDS组合系统的TRAIM检测可用概率达到99.1%以上,基本满足LEO卫星TRIAM检测可用性需求。     

InSAR滑坡探测技术研究——以金沙江乌东德水电站段为例

采用3类InSAR产品和DEM数据开展金沙江流域乌东德水电站段的潜在滑坡探测,成功识别出多处已知和未知的滑坡点,并探测出滑坡体的形态及稳定性,提供了一种高效的大范围滑坡探测技术。同时采用小基线集InSAR技术对金坪子滑坡进行监测,不仅获得该滑坡的空间分区特征,也获取重点滑坡区的时间序列结果,并且与地面监测结果比较,精度达1.8 cm。展示了不同InSAR技术在不同尺度滑坡调查与监测中的应用特点。