Cu2+对青蛤的胁迫效应

为研究青蛤(Cyclina sinensis)对重金属Cu~(2+)的蓄积作用及免疫机能的影响,开展了Cu~(2+)对青蛤的急性毒性实验,观察青蛤在96 h Cu~(2+)半致死浓度和安全浓度胁迫下,不同组织的蓄积趋势,及血淋巴液中SOD、CAT和ACP活性的变化。结果显示:Cu~(2+)的半致死浓度为0.807 mg/L,安全浓度为0.00807 mg/L。鳃和内脏团组织中蓄积的Cu~(2+)浓度与处理时间呈正相关;在半致死和安全浓度胁迫下,鳃组织中Cu~(2+)蓄积速度均快于内脏团;在半致死浓度胁迫下血淋巴液中SOD、CAT和ACP活性呈现先诱导再抑制的趋势,安全浓度下无明显变化,但均高于对照组水平。     

不同盐度对施氏獭蛤浮游期幼虫存活与生长的影响

为提高施氏獭蛤(Lutraria sieboldii)育苗成活率,作者采用单因子实验设计,研究了不同海水盐度对北部湾海域施氏獭蛤浮游期幼虫存活与生长的影响。结果表明,施氏獭蛤浮游期幼虫的临界存活盐度为22.84~33.12、适宜存活盐度为24.54~31.54、较适宜存活盐度为25.83~30.17、最适宜存活盐度为26.8~29.4;临界生长盐度为~35.67、适宜生长盐度为22.51~31.66、较适宜生长盐度为27.51~31.37、最适宜生长盐度为29.4;综合盐度对存活率和生长率的影响,施氏獭蛤浮游期幼虫最佳的培育盐度为29.4。研究结果为施氏獭蛤育苗场的选址及人工育苗提供了参考。     

桑沟湾长牡蛎生物沉积物对环境底质影响的同位素证据

贝类通过生物沉积作用加速了养殖海区水体中的颗粒物质向海底的输送。在桑沟湾中筏式养殖的长牡蛎(Crassostrea gigas),将大量的有机物以生物沉积物(真粪和假粪)的形式排向养殖区海底。为完成对桑沟湾筏式养殖长牡蛎生物沉积物对环境底质影响的量化研究,作者通过在桑沟湾内不同的海区设置采样点(5个养殖区,3个对照点),对采样点SG 2与SG 6两个点的长牡蛎生物性沉积物与海区悬浮颗粒物进行了稳定同位测定及有机物来源分析。实验结果表明:选取的采样点沉积物稳定碳氮同位素丰度集中于δ~(13)C–22.82‰~–21.62‰,δ~(15)N 4.73‰~6.21‰。在SG 2点的悬浮颗粒物中,长牡蛎生物性沉积物贡献有机物占9.95%,对照区沉积物与SG 2区沉积物贡献分别为54.19%和35.86%。在典型的采样点,稳定同位素法能较准确地量化出各有机物来源的贡献比例。以SG C点为对照,其余7个采样点长牡蛎生物性沉积物有机物贡献在4.06%~28.64%,平均贡献率为13.96%±8.62%,牡蛎养殖已经对桑沟湾底质造成了一定的影响。     

辽宁沿海菲律宾蛤仔不同地理群体形态差异研究

利用多变量形态度量学方法,对辽宁沿海菲律宾蛤仔(Ruditapes philippinarum)长兴岛(CXD)、旅顺(LS)、营口(YK)、盘锦(PJ)、锦州(JZH)、海洋岛(HYD)、黑石礁(HSJ)以及金州(JZ)8个野生群体进行形态学比较分析。结果表明:主成分分析得到了3个主成分,贡献率分别为40.21%,19.98%和11.57%,累积贡献率为71.75%。聚类分析结果显示,旅顺群体和锦州群体形态最为接近,而与黑石礁群体差异较大。营口群体的趋异程度最大,长兴岛群体、金州群体和海洋岛群体的趋异程度居中。长兴岛群体壳型最扁,贝壳较厚且重;营口群体软体部最肥;金州群体壳型"凸"型最明显,且质量最大,而黑石礁群体贝壳最薄。这些明显特征揭示了不同群体的形态差异。研究结果为菲律宾蛤仔的地理群体识别、种质资源保护与恢复提供了重要依据。     

基于海温遥感资料的海洋锋检测方法

介绍了海洋锋的特点和本文选用的资料源,详细研究了海洋锋检测算法,给出了梯度和锋线检测结果,最后分析了东海黑潮锋季节变化规律,为基于海温遥感资料的海洋锋检测方法业务化应用提供参考。     

海底管道EDIS应用平台研发与示范工程

文章首先介绍了海底管道工程数字化信息系统(engineering digital information system,EDIS)工程信息数字化应用平台的开发背景和意义,然后针对中国海洋石油总公司(以下简称中海油)已颁布的《EDIS海管规范》和《新建海管工程项目完工数字化移交规范》要求,分析指出了海底管道工程信息数字化应用平台研发的关键难点问题;接着,着重介绍本文研发示范工程——锦州25-1南油田群海底管道EDIS应用平台的系统开发架构和海管全生命周期工程数据管理组织架构与逻辑关联,并详述了研发平台对应海管工程文档库、工程数据库、工程模型库以及三维管道地理信息系统(geography information system,GIS)应用系统等各模块具体功能;最后,笔者在分析平台研发技术特点和应用价值基础之上,论述了海底管道EDIS应用平台的开发价值和推广应用前景。     

Estimating the Turbulence Characteristics in the Bottom Boundary Layer of Monterey Canyon

From April 24 to October 25, 2011, an Acoustic Doppler Velocimeter(ADV) continually running for 185 d was mounted on the smooth ridge at the edge of Monterey Canyon to observe turbulence in the bottom boundary layer. The ADV was set at 1.4 m above the bed bottom, continuously run for 1 min with a 2-minute interval with sampling frequency 64 Hz. The long-time continual observation is significant to reveal variations of turbulent characteristics and show some differences from the classic traditional turbulent theory. Eliminating the noise by the ‘Phase-Space Thresholding Method', rotating the coordinate and low-pass filtering the velocity were applied for data processing. This paper was mainly to estimate the turbulent kinetic energy dissipation rate by the inertial dissipation method, friction velocity, drag coefficient and significant periods of the turbulent characteristics with the ADV data. The results show that there is a strong, rotating bottom flow up to 0.398 m s-1 with predominantly semidiurnal period and less significantly diurnal and semilunar period. The turbulent kinetic energy dissipation rate ranges from 1.09×10-8 W kg-1 to 6.62×10-5 Wkg-1, which can vary with 2 or 3 orders of magnitude in one day. The daily averaged variations of friction velocity and drag coefficient are 6.50×10-3–2.32×10-2 m s-1 and 6.30×10-3–4.36×10-2, respectively. All the characteristics have a remarkable semidiurnal period. In the bottom boundary layer with a rotating tide, the parameterized coefficients to describe ε-u* and ε-Et relationships are much smaller than the traditional value.     

Research of Marine Sensor Web Based on SOA and EDA

A great deal of ocean sensor observation data exists, for a wide range of marine disciplines, derived from in situ and remote observing platforms, in real-time, near-real-time and delayed mode. Ocean monitoring is routinely completed using sensors and instruments. Standardization is the key requirement for exchanging information about ocean sensors and sensor data and for comparing and combining information from different sensor networks. One or more sensors are often physically integrated into a single ocean ‘instrument' device, which often brings in many challenges related to diverse sensor data formats, parameters units, different spatiotemporal resolution, application domains, data quality and sensors protocols. To face these challenges requires the standardization efforts aiming at facilitating the so-called Sensor Web, which making it easy to provide public access to sensor data and metadata information. In this paper, a Marine Sensor Web, based on SOA and EDA and integrating the MBARI's PUCK protocol, IEEE 1451 and OGC SWE 2.0, is illustrated with a five-layer architecture. The Web Service layer and Event Process layer are illustrated in detail with an actual example. The demo study has demonstrated that a standard-based system can be built to access sensors and marine instruments distributed globally using common Web browsers for monitoring the environment and oceanic conditions besides marine sensor data on the Web, this framework of Marine Sensor Web can also play an important role in many other domains' information integration.     

卵形鲳鲹PPARα基因cDNA序列的克隆、组织表达及生物信息学分析

采用RACE-PCR克隆卵形鲳鲹(Trachinotus ovatus)过氧化物酶体增殖物激活受体(peroxisome proliferator activated receptors-α,PPARα)基因的c DNA序列全长,并应用生物信息学方法分析其编码蛋白质的理化性质和结构特征。结果表明:卵形鲳鲹PPARα基因(Gen Bank登录号KP893147)c DNA全长1 930 bp,开放阅读框(ORF)为1 425 bp,共编码474个氨基酸,其编码的蛋白质为不稳定蛋白,无信号肽和跨膜结构,二级结构由α螺旋、β转角、伸展片段和无规则卷曲组成,且α螺旋占较大比例;预测显示,该蛋白有PPARs基因家族典型的DNA结合区(DBD)和配体结合区(LBD);序列对比表明,卵形鲳鲹PPARα基因与尼罗罗非鱼(Oreochromis niloticus)、花鲈(Lateolabrax japonicas)、大黄鱼(Larimichthys crocea)、金头鲷(Sparus aurata)、军曹鱼(Rachycentron canadum)等有较高的同源性(81%~89%);蛋白系统进化树分析显示,在人(Homo sapiens)、鼠(Mus musculus)、鸭(Gallus gallus)、花鲈、大黄鱼、军曹鱼等动物中,卵形鲳鲹的PPARα蛋白与军曹鱼的进化关系最为密切(94%),与人(68%)、鼠(68%)、鸭(67%)等的同源性较低。荧光定量分析显示,卵形鲳鲹PPARαm RNA在脑、肾脏、肠、脾脏等组织表达水平较高,其次是皮肤、肌肉,在心脏、肝脏中表达量较低。     

结合张量与互信息的混合模型多模态图像配准方法

多模态图像之间存在显著的非线性强度差异,并且图像会因为噪声而退化,因此,多模态图像自动配准是一项具有挑战性的任务.为了解决这两个问题,本文提出一种多模态图像自动配准方法,该方法分为预配准和精配准两个阶段.在预配准阶段,通过改进SIFT算法来大致对齐多模态图像.在精配准阶段,首先,利用块Harri s检测器在预配准后的参考图上提取均匀分布的特征点.然后,通过各向异性结构张量捕捉多模态图像中的结构信息来构建特征描述符,该特征描述符对噪声具有稳健性.更进一步,本文结合张量方向平行度和梯度互信息提出了一种相似度准则(tensor orientation and mutual information,TOMI).最后,本文用多种模态图像(包括Optical,LiDAR,SAR和Map)来评估提出的方法.试验结果表明,本文提出的方法对非线性强度变化和噪声具有较好的稳健性,并且匹配效果优越.