海底孔内水合物观测系统与钻井实施

通过耦合布设海底表面和孔内水合物观测系统获取物理、化学、微生物等数据是了解掌握海洋水合物环境动态变化、碳循环规律和资源开发技术的有效手段,据此初步提出了一套海底孔内水合物观测系统,并指出了系统的关键技术难点。而在钻井布设该孔内观测系统时,要注意防止井内安全事故的发生,充分评估安放位置处含水合物地层的地质力学稳定性并采取适当的钻井和完井方式稳定或强化含水合物地层以支撑孔内观察仪器,实现孔内长期监测。最后讨论了在我国南海实施孔内水合物观测系统的必要性,并提出了初步想法。     

基于ArcSDE的人防数据入库的应用研究

空间数据引擎是实现空间数据库的核心。简要介绍了ESRI公司的空间数据库引擎（spatial database engine）,它能将空间数据和属性数据集成在数据库中。进一步分析了空间数据的存储模式,并以人防工程为例构建了人防的Geodatabase数据模型,最后对实现人防工程数据的入库方法进行了探讨。     

3维地形环境仿真中点阵文本技术研究

在3维地形环境仿真中,经常需要输出大量文本信息.通常的做法是用位图方式进行渲染,但在某些情况下(如嵌入式操作系统)无法实现这一功能.针对某些3维地形环境仿真中位图方式渲染文本的局限性,研究如何用点阵方式渲染文本.研究内客包括点阵字库的创建和点阵文本的渲染,并根据实时渲染中不同类型文本的特点,将点阵文本的渲染分为缓存和非缓存两种方式.最后在基于VxWorks嵌入式系统的3维地形环境中实现了点阵文本的渲染.     

GIS-based landslide susceptibility mapping using hybrid integration approaches of fractal dimension with index of entropy and support vector machine

The loess area in the northern part of Baoji City, Shaanxi Province, China is a region with frequently landslide occurrences. The main aim of this study is to quantitatively predict the extent of landslides using the index of entropy model(IOE), the support vector machine model(SVM) and two hybrid models namely the F-IOE model and the F-SVM model constructed by fractal dimension. First, a total of 179 landslides were identified and landslide inventory map was produced, with 70%(125) of the landslides which was optimized by 10-fold crossvalidation being used for training purpose and the remaining 30%(54) of landslides being used for validation purpose. Subsequently, slope angle, slope aspect, altitude, rainfall, plan curvature, distance to rivers, land use, distance to roads, distance to faults, normalized difference vegetation index(NDVI), lithology, and profile curvature were considered as landslide conditioning factors and all factor layers were resampled to a uniform resolution. Then the information gain ratio of each conditioning factors was evaluated. Next, the fractal dimension for each conditioning factors was calculated and the training dataset was used to build four landslide susceptibility models. In the end, the receiver operating characteristic(ROC) curves and three statistical indexes involving positive predictive rate(PPR), negative predictive rate(NPR) and accuracy(ACC) were applied to validate and compare the performance of these four models. The results showed that the F-SVM model had the highest PPR, NPR, ACC and AUC values for training and validation datasets, respectively, followed by the F-IOE model.Finally, it is concluded that the F-SVM model performed best in all models, the hybrid model built by fractal dimension has advantages than original model, and can provide reference for local landslide prevention and decision making.     

Detecting and attributing vegetation changes in Taihang Mountain,China

Attributing vegetation changes provide fundamental information for ecosystem management,especially in mountainous areas which has vulnerable ecosystems. Based on the Normalized Difference Vegetation Index(NDVI) data, the spatial-temporal change of vegetation was detected in Taihang Mountain(THM) from 2000 to 2014. The topographical factors were introduced to interpret the response of vegetation variation to climate change and human activities. Results showed that the avegaged NDVI during growing season showed a single-peak curve distribution, with the largest value(0.628) among 1600-1800 m. A significant greening trend was detected in THM, with the largest increasing rate(0.0078 yr~(-1)) among the elevation of1600-1800 m and slope gradient between 3~5°. The partial correlation and multiple correlation analyses indicated that vegetation variation in more than81.8% pixels of the THM was mainly impacted by human activities. In the low elevation zones less than1000 m, increasing precipitation is the principle factor promoting vegetation restoration, whereas in the high elevation zones of THM, temperature is the restricted factors impacting vegetation variation.Considering the dramatic climate change in the future,further studies should be conducted to explore inherent mechanism of vegetation growth to dynamic environment changes.     

Isolation of protein from Chlorella sorokiniana CY1 using liquid biphasic flotation assisted with sonication through sugaring-out effect

Microalgae, a sustainable source of multi beneficial components has been discovered and could be utilised in pharmaceutical, bioenergy and food applications. This study aims to investigate the sugaring-out effect on the recovery of protein from wet green microalga, Chlorella sorokiniana CY1 which was assisted with sonication. A comparison of monosaccharides and disaccharides as one of the phaseforming constituents shows that the monosaccharides, glucose was the most suitable sugar in forming the phases with acetonitrile to enhance the production of protein(52% of protein). The protein productivity of microalgae was found to be significantly influenced by the volume ratio of both phases, as the yield of protein increased to 77%. The interval time between the sonication as well as the sonication modes were influencing the protein productivity as well. The optimum protein productivity was obtained with 10 s of resting time in between sonication. Pulse mode of sonication was suitable to break down the cell wall of microalgae compared to continuous mode as a lower protein yield was obtained with the application of continuous mode. The optimum condition for protein extraction were found as followed: 200 g/L glucose as bottom phase with volume ratio of I:1.25, 10 s of resting time for ultrasonication, 5 s of ultrasonication in pulse mode and 0.25 g of biomass weight. The high yield of protein about 81% could be obtained from microalgae which demonstrates the potential of this source and expected to play an important role in the future.     

Responding to Global Warming: Mitigation Policies and Actions of Stakeholders in China’s Tourism Industry

China’s tourism industry has witnessed rapid progress in recent years, and is now an important part of global tourism in dealing with climate change. Within a framework of Pressure-State-Response (PSR), this paper focuses on the emission reduction pressure, carbon emission status, and responses of stakeholders in China’s tourism industry. Findings include: 1) The central government’s strategy and rapid growth of the industry scale exert rising pressure on China’s tourism to reduce carbon emissions. 2) Carbon emissions of China's tourism account for 13%-14.6% of global tourism, and about 3% of China’s emissions overall. Chinese tourists’ per capita carbon emission is lower than half of the global level. 3) The Chinese government attaches great importance to energy-saving and carbon emission reduction. In the tourism industry, documents, standards and other regulative measures have been issued to ensure that business practitioners set up green operational and managerial systems. In the field of tourism transportation, China's high-speed rail, new energy vehicles, and urban shared bicycles, have developed very rapidly in recent years, and they have effectively reduced the carbon emissions in traveling. Furthermore, this paper finds that Chinese tourists already have awareness and willingness for low-carbon tourism.     

经济海藻病害及防控技术的研究进展

经济海藻的病害一直是海藻人工栽培的一大障碍,往往造成严重的经济损失。目前对藻类病害的研究大多集中于病原鉴定,而病原的多样性和复杂的海区微环境增加了病原分离和鉴定的难度。本文综述了经济海藻病害发生的原因、病原的多样性和致病机制、病原的鉴定、检测和防治方法,并对未来我国海藻病害研究方向进行了展望,以期对藻类病害的防控提供参考。     

基于转录组测序对两种氮素营养条件下多形微眼藻氮代谢途径的解析

探究微藻的氮代谢通路对了解其对不同氮源利用的分子机制具有重要意义。本研究利用Illumina高通量测序技术对两种氮素营养条件下(硝酸氮和尿素)多形微眼藻的转录组进行分析,通过基因功能注释及数字基因表达谱分析,研究了多形微眼藻细胞内氮代谢的调控机制。结果检测出15种参与氮代谢的酶,对应76个编码基因,构建了多形微眼藻的氮代谢通路图。其中10个酶编码基因在两种不同氮素营养条件下存在差异表达,最显著的是谷氨酸合成酶、谷氨酸脱氢酶和谷氨酰胺合成酶相关基因。有机氮源(尿素)实验组中,多形微眼藻细胞内的硝酸盐还原酶、亚硝酸盐还原酶等基因的差异表达明显高于无机氮源(硝酸钠)实验组,表明当环境中的氮源为尿素时,会对多形微眼藻细胞内硝酸盐的转化和利用有一定影响。本研究初步阐述了硝酸盐、尿素的吸收转运对多形微眼藻细胞内氮代谢的影响机制,可为硅藻在不同氮素营养条件下的吸收利用机制及氮代谢响应研究提供依据。     

中国东海陆架海域柱状沉积物对磷的吸附行为

通过研究磷在海洋柱状沉积物上的吸附动力学曲线和吸附等温线,并结合沉积物表面电荷性质以及磷形态分析,考察了我国东部陆架海域沉积物对磷的吸附特征。结果表明,所研究海域沉积物对磷的吸附过程明显分为快慢两段,48h后吸附可达到平衡;吸附后的磷主要为可交换态磷,吸附过程以物理作用为主;吸附等温线可用Langmuir交叉型模式描述,在磷初始浓度较低时,沉积物对磷存在解吸现象;沉积物对磷吸附参数的垂直分布较为复杂,受自身性质影响较大;盐度增大,沉积物对磷的吸附能力呈下降趋势。