Seasonal abundance and distribution of pelagic tunicates (Chordata: Thaliacea) in the central South China Sea

1IntroductionTunicates(Chordata:Thaliacea)are large pe-lagic gelatinous zooplankton.They can be used as in-dicator species for ocean currents and water bodies(Chen et al.,1980;Chen et al.,1988;Lin,1988,1990;Lin and Zhang,1993;Thompson,1948).They also play…     

Exploring Spatially Non-stationary Relationships in the Determinants of Mineralization in 3D Geological Space

Exploring the spatial relationships between various geological features and mineralization is not only conducive to understanding the genesis of ore deposits but can also help to guide mineral exploration by providing predictive mineral maps. However, most current methods assume spatially constant determinants of mineralization and therefore have limited applicability to detecting possible spatially non-stationary relationships between the geological features and the mineralization. In this paper, the spatial variation between the distribution of mineralization and its determining factors is described for a case study in the Dingjiashan Pb–Zn deposit, China. A local regression modeling technique, geological weighted regression (GWR), was leveraged to study the spatial non-stationarity in the 3D geological space. First, ordinary least-squares (OLS) regression was applied, the redundancy and significance of the controlling factors were tested, and the spatial dependency in Zn and Pb ore grade measurements was confirmed. Second, GWR models with different kernel functions in 3D space were applied, and their results were compared to the OLS model. The results show a superior performance of GWR compared with OLS and a significant spatial non-stationarity in the determinants of ore grade. Third, a non-stationarity test was performed. The stationarity index and the Monte Carlo stationarity test demonstrate the non-stationarity of all the variables throughout the area. Finally, the influences of the degree of non-stationary of all controlling factors on mineralization are discussed. The existence of significant non-stationarity of mineral ore determinants in 3D space opens up an exciting avenue for research into the prediction of underground ore bodies.

     

A new pelagic Polyconchoecia Xiang, Chen and Du, 2018 (Ostracoda: Myodocopa: Halocyprididae) from the South China Sea

Halocyprid ostracods are appreciable part of ostracods floating through virtually everywhere in marine environment.In this study,we describe a new species of genus Polyconchoecia Xiang,Chen and Du,2018,tribe Conchoeciini Chavtur and Angel,2011,family Halocyprididae Dana,1853 from the middle of the South China Sea.Polyconchoecia chenii sp.nov.is very close to P.commixtus Xiang,Chen and Du,2018.But it differs from P.commixtus by the distinctions of locations of major glands of carapace and the characteristics of appendages:more posteriorly situated left asymmetric gland of carapace,no right asymmetric gland;segmented frontal organ;the endopod 2 of the first antenna with a very small seta;a-and c-setae of the first antenna with long end joint have long end joint,the b-and d-setae have no end joint,spinose e-seta without end joint;the e-seta of the second antenna is present;teeth side is distinctive;the setal counts of the mandible,maxilla,fifth limb,and sixth limb are individual.The locations of the major glands on carapace and the characteristics of the first antenna can be the key of the new species.This work is the second discovery of the genus Polyconchoecia from the world.     

基于自动探测方法的南海北部涡致海表温度锋面的特征研究

南海北部具有丰富的温度锋面和中尺度涡,它们调节着局地的热量和能量平衡。本文利用卫星海洋高度异常和海表温度数据,并基于自动探测方法,探究了2007年至2017年南海北部中尺度涡边缘的海表温度锋面（涡致锋面）特征。反气旋/气旋边缘出现锋面的概率可达20%。气旋涡在各个方向上出现锋面的概率比较均匀,反气旋涡的东北部和西南部出现锋面的概率大于西北部和东南部。中尺度涡致锋面的数量有明显的季节变化,而涡动能未表现出明显的季节变化。中尺度涡致锋区的总涡动能是中尺度涡内动能的3倍,并且反气旋涡致锋面的总涡动能明显强于气旋涡致锋面的总涡动能。中尺度涡致锋面的数量和涡动能的年际变化与厄尔尼诺南方涛动指数没有明显的相关性。本研究也讨论了中尺度涡致锋面的可能机制,但是中尺度涡对海表温度锋的贡献需要进一步定量研究。     

Influence Analysis and Vibration Restraint Solutions Research on the Underwater Acoustic Monitoring System

China Ocean Engineering - In order to reduce the hydrodynamic and structural influences on the detection accuracy especially in the very-low-frequency range, some vibration restraint methods are...     

闽三角红树林底栖软体动物共存格局及机制

以漳江口国家级红树林自然保护区、九龙江口省级红树林自然保护区和泉州湾省级湿地保护区3个红树林分布区作为研究对象,研究底栖软体动物在中等尺度下的共存格局及机制。利用非度量多维标度分析、基于蒙特卡洛的零模型和网络分析探讨底栖软体动物的共存格局,利用raup-crik零模型识别决定性过程和随机过程测定底栖软体动物的相对重要性。结果显示,漳江口、九龙江口和泉州湾湿地共发现37种底栖软体动物,底栖软体动物的平均密度、物种数及群落物种组成差异显著。软体动物的共存格局呈现非随机分散和模块化,这些格局同时受到决定性过程和随机过程的调控作用,其中,物种竞争起主导作用。     

A natural language processing and geospatial clustering framework for harvesting local place names from geotagged housing advertisements

Local place names are frequently used by residents living in a geographic region. Such place names may not be recorded in existing gazetteers, due to their vernacular nature, relative insignificance to a gazetteer covering a large area (e.g. the entire world), recent establishment (e.g. the name of a newly-opened shopping center) or other reasons. While not always recorded, local place names play important roles in many applications, from supporting public participation in urban planning to locating victims in disaster response. In this paper, we propose a computational framework for harvesting local place names from geotagged housing advertisements. We make use of those advertisements posted on local-oriented websites, such as Craigslist, where local place names are often mentioned. The proposed framework consists of two stages: natural language processing (NLP) and geospatial clustering. The NLP stage examines the textual content of housing advertisements and extracts place name candidates. The geospatial stage focuses on the coordinates associated with the extracted place name candidates and performs multiscale geospatial clustering to filter out the non-place names. We evaluate our framework by comparing its performance with those of six baselines. We also compare our result with four existing gazetteers to demonstrate the not-yet-recorded local place names discovered by our framework.     

An improved building detection approach using L-band POLSAR two-dimensional time-frequency decomposition over oriented built-up areas

The objective of this study is to efficiently extract detailed information about various man-made targets in oriented built-up areas using polarimetric synthetic aperture radar (POLSAR) images. This paper develops an improved approach for building detection by utilizing Two-Dimensional Time-Frequency (2-D TF) decomposition. This method performs outstandingly in distinguishing between man-made and natural targets based on the isotropic behaviors, frequency-sensitive responses, and scattering mechanisms of objects. The proposed method can preserve the spatial resolution and exploit the advantages of TF decomposition; specifically, the exact outlines of buildings can be effectively located, and more types of features (e.g., flat roofs, roads, and walls that are oblique to the radar illumination) can be distinguished from forests in complex built-up areas by 2-D TF decomposition. The coarser-resolution subaperture images that are produced in the azimuth direction, which correspond to different looking angles, are beneficial for detecting man-made structures with main scattering centers oriented at oblique angles with respect to the radar illumination. In the range direction, the obtained subaperture images, which correspond to various observation frequencies, can be helpful in distinguishing flat roofs and roads from forests. This method was successfully implemented to analyze both NASA/JPL L-band AIRSAR and L-band EMISAR data sets. The building detection results of the proposed method exhibit a significant improvement over those of other methods and reach an overall accuracy over 80%, with approximately 20% higher than the accuracies of K-means clustering and the entropy/alpha-Wishart classifier and approximately 10% higher than the accuracy of the support vector machine method. Moreover, building details can be precisely detected, obliquely oriented buildings can be identified, and the distinction between buildings and forests is significantly improved, as both visually and statistically indicated. This method is highly adaptable and has substantial application value.     

南黄海和东海毛颚类生态特征的研究Ⅱ.群落特征

在对南黄海和东海毛颚类生态特征的研究数量分布特征后的续篇.重点探讨调查区毛颚类群落性质和群落结构的特征及与海区环境因子的相关性.结果表明,本区共记录毛颚类28种,种类季节变化不明显,周年共有种达64.3%;但群落优势种则有季节差异与区域差异.毛颚类群落多样性指数(H')和均匀度(J')年均值分别为1.68和0.64.H'的平面分布表现出外部海区大于近岸海区的分布格局.在群落中存在4个生态类群,其中近海暖温带类群和广盐暖水类群可分别指示黄海水、浙江沿岸流和东海陆架混合水在南黄海和东海这两个海区的相互推移和消长过程.此外,从不同侧面的计算分析也表明,影响群落特征值(H')的主要因子是温度和盐度.群落性质是以近岸暖温带低盐种和暖水广布种为主,近岸暖水种和大洋暖水种占一定比例的暖温带-亚热带群落结构的特点.     

Detection of the end point temperature of thermal denatured protein in fish and chicken meat through SDS-PAGE electrophoresis

Sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) was applied in the detection of the end point temperature (EPT) of thermal denatured protein in fish and meat in this study. It was also used in studying the thermal denatured temperature range of proteins in salmon and chicken meat. The results show that the temperature ranges of denatured proteins were from 65 ℃ to 75 ℃ , and these temperature ranges were influenced by the processing methods. Through SDS-PAGE, the features of repeated he...