海带磷酸甘露糖变位酶(PMM)基因的克隆与表达分析

磷酸甘露糖变位酶(PMM)是褐藻胶和岩藻聚糖合成过程中的关键酶之一。本研究利用c DNA末端快速克隆(RACE)技术,获得2条海带PMM基因(Sjpmm1,Sjpmm2)序列。其中,Sjpmm1的开放阅读框(ORF)长759 bp,其编码的Sj PMM1为卤酸脱卤酶(HAD)超家族成员,含252个氨基酸,分子量约为28.51 k Da;而Sjpmm2的ORF长1866 bp,其编码的Sj PMM2属于磷酸己糖变位酶超家族的成员,含621个氨基酸,分子量约为66.49 k Da。海带PMM的二级结构均以?-螺旋为主。进化分析表明,Sjpmm1来自于原始真核生物,而Sjpmm2来源于质体的第一次内共生作用。实时定量PCR分析发现,海带受到高温或低温胁迫时,Sjpmm1和Sjpmm2转录水平上升,以合成岩藻聚糖抵抗环境影响。此外,利用p MAL-c5X载体对Sj PMM1进行体外表达,得到高浓度的可溶性融合蛋白,为后续的Sj PMM功能分析提供基础。     

Improved regional groundwater flow modeling using drainage features: a case study of the central northern karst aquifer system of Puerto Rico (USA)

In northern Puerto Rico (USA), subsurface conduit networks with unknown characteristics, and surface features such as springs, rivers, lagoons and wetlands, drain the coastal karst aquifers. In this study, drain lines connecting sinkholes and springs are used to improve the developed regional model by simulating the drainage effects of conduit networks. Implemented in an equivalent porous media (EPM) approach, the model with drains is able to roughly reproduce the spring discharge hydrographs in response to rainfall. Hydraulic conductivities are found to be scale dependent and significantly increase with higher test radius, indicating scale dependency of the EPM approach. Similar to other karst regions in the world, hydraulic gradients are steeper where the transmissivity is lower approaching the coastline. This study enhances current understanding of the complex flow patterns in karst aquifers and suggests that using a drainage feature improves modeling results where available data on conduit characteristics are minimal.     

Quantities and Fluxes of Dissolved and Particulate Black Carbon in the Changjiang and Huanghe Rivers,China

Recent studies have suggested that large rivers play important roles in mobilizing and transporting black carbon (BC) from land to the ocean. However, the influence of the Changjiang and Huanghe, the two largest rivers in China, on the fate of BC has not been determined. In this paper, we present measurements of BC in both the dissolved and particulate phases in the Changjiang and Huanghe Rivers and in the coastal waters of the East China Sea (ECS). Our results show that dissolved black carbon (DBC) accounted for 3.0 ± 0.4 % and 4.8 ± 3.6 % of the total DOC pool in the Changjiang and Huanghe Rivers and 3.4 ± 0.6 % of the DOC pool in the coast of the ECS. In addition, particulate black carbon (PBC) accounted for 13 ± 0.9 % and 22 ± 11 % of the POC pool in the Changjiang and Huanghe Rivers, respectively. We calculate that the Changjiang and Huanghe transported 4.7 × 10¹⁰ gC and 1.7 × 10⁹ gC of DBC, and 2.0 × 10¹¹ gC and 1.2 × 10¹⁰ gC of PBC to the ECS and Bohai Sea in 2015. The large amounts of BC transported by the two rivers represent a major sink of anthropogenically derived organic carbon and could have a significant impact on the ecosystem and carbon cycling in China’s marginal seas.     

海洋产业结构与海域承载力的匹配关系探讨——以辽宁省为例

海洋产业结构和海域承载力之间存在多种耦合匹配关系,其匹配程度是影响海洋经济健康持续发展的重要因素,而准确地定量化评价这种匹配关系是准确把握海洋产业结构是否失衡的关键环节。文章将海域承载力引入海洋产业结构问题研究中,首先对海洋产业结构水平和海域承载力定量化测算,在此基础上运用基于数列的匹配度计算方法测度辽宁省海域承载状况与海洋产业结构水平的匹配度,探讨海洋产业结构与海域承载力之间的匹配关系。结果表明:辽宁省海域承载力与海洋产业结构水平匹配度数值较高,二者之间存在较匹配的关系。     

国外海洋调查船发展历史和趋势以及对我国的启示

海洋调查船是专门进行海洋调查研究的工具,涉及船舶设计、建造、海洋调查技术、航海管理和海洋调查实验管理等领域,是我国海洋强国战略和"一带一路"战略构想顺利实施的重要保障。文章梳理欧美自大航海时代以来海洋调查船的发展历程,选取各时期具有代表性的船舶,总结其特点和最新发展趋势,以期为我国海洋调查船的设计建造思路提供启示。     

基于地理格网分级法提取的中国传统村落空间分布

中国传统村落真实地记录了建筑、民俗民风和较原始的民居空间形态,是千百年来人类与自然和谐共存的生活基础。随着城市化进程加快,传统村落的存续受到了很大的挑战,为了更好地保护利用传统村落,对其进行多视角的研究尤为重要,除了微观层面的具体保护措施外,还应加强宏观层面的空间分布研究。地理格网是表达复杂地理现象、综合分析自然与人文数据、模拟地理系统功能与行为的基本方法。本文从百度影像地图提取村落坐标,并截取遥感影像作为村落点数据的判断补充,在此基础上,运用地理格网的分级法,对国家公布的三批中国传统村落(2555个)数据进行空间格局分析,结果表明：这些村落主要分布在中国东南部,如落在一级格网Ⅰ18、Ⅰ19就分别有586、781个村落,占三批传统村落总数的96.6%。通过对二级和三级格网的村落分布离散性进行分析,使传统村落的空间分布数据结构更加系统和清晰有序,为合理构建其数据库提供了框架基础。     

Bias estimation and correction for triangle-based surface area calculations

The calculation of surface area is meaningful for a variety of space-filling phenomena, e.g., the packing of plants or animals within an area of land. With Digital Elevation Model (DEM) data we can calculate the surface area by using a continuous surface model, such as by the Triangulated Irregular Network (TIN). However, just as the triangle-based surface area discussed in this paper, the surface area is generally biased because it is a nonlinear mapping about the DEM data which contain measurement errors. To reduce the bias in the surface area, we propose a second-order bias correction by applying nonlinear error propagation to the triangle-based surface area. This process reveals that the random errors in the DEM data result in a bias in the triangle-based surface area while the systematic errors in the DEM data can be reduced by using the height differences. The bias is theoretically given by a probability integral which can be approximated by numerical approaches including the numerical integral and the Monte Carlo method; but these approaches need a theoretical distribution assumption about the DEM measurement errors, and have a very high computational cost. In most cases, we only have variance information on the measurement errors; thus, a bias estimation based on nonlinear error propagation is proposed. Based on the second-order bias estimation proposed, the variance of the surface area can be improved immediately by removing the bias from the original variance estimation. The main results are verified by the Monte Carlo method and by the numerical integral. They show that an unbiased surface area can be obtained by removing the proposed bias estimation from the triangle-based surface area originally calculated from the DEM data.     

Optimal routing for waste collection: a case study in Singapore

ABSTRACT

To collect and dispose growing amounts of municipal solid waste (MSW) changed to be a hot topic along with the rapid urbanization in past decades. Cities are more and more dependent on the incineration instead of landfilling due to the cost-efficiency and environmental concerns. Considering the limited number of incineration plants and complicated situation of transportation in both spatial and temporal dimensions in different cities, the optimal routing for waste collection turns to be meaningful research topic. In this research, the ant colony optimization (ACO)-based multi-objective routing model coupled with min-max model and Dijkstra’s algorithm is proposed to address the question of which route to take from these waste-generating points to the target incineration plant(s) considering travel time, accident probability (black spots), and population exposure, so as to support the routing decision-making. The model is successfully implemented in Singapore and the effectiveness of the model has also been justified. Besides, few limitations of this research have also been discussed, some of which would also be the future directions of our research, especially the design and integration of a web-based routing decision-making support system.