Review of pre-processing technologies for ice cores

High-resolution ice core records covering long time spans enable reconstruction of the past climatic and environmental conditions allowing the investigation of the earth system’s evolution. Preprocessing of ice cores has direct impacts on the data quality control for further analysis since the conventional ice core processing is time-consuming, produces qualitative data, leads to ice mass loss, and leads to risks of potential secondary pollution. However, over the past several decades, preprocessing of ice cores has received less attention than the improvement of ice drilling, the analytical methodology of various indices, and the researches on the climatic and environmental significance of ice core records. Therefore, this papers reviews the development of the processing for ice cores including framework, design as well as materials, analyzes the technical advantages and disadvantages of the different systems. In the past, continuous flow analysis (CFA) has been successfully applied to process the polar ice cores. However, it is not suitable for ice cores outside polar region because of high level of particles, the memory effect between samples, and the filtration before injection. Ice core processing is a subtle and professional operation due to the fragility of the nonmetallic materials and the random distribution of particles and air bubbles in ice cores, which aggravates uncertainty in the measurements. The future developments of CFA are discussed in preprocessing, memory effect, challenge for brittle ice, coupling with real-time analysis and optimization of CFA in the field. Furthermore, non-polluting cutters with many different configurations could be designed to cut and scrape in multiple directions and to separate inner and outer portions of the core. This system also needs to be coupled with streamlined operation of packaging, coding, and stacking that can be implemented at high resolution and rate, avoiding manual intervention. At the same time, information of the longitudinal sections could be scanned and identified, and then classified to obtain quantitative data. In addition, irregular ice volume and weight can also be obtained accurately. These improvements are recorded automatically via user-friendly interfaces. These innovations may be applied to other paleomedias with similar features and needs.     

两株南极枝孢霉属真菌Cladosporium sp.NJF4和NJF6的次级代谢产物研究

南极因其独特的自然环境成为潜在、重要的微生物资源库,是产生新型生物活性物质和先导化合物菌株的潜在种源地,南极微生物正在成为创新药物研究新的重要资源。虽然近年来对南极微生物次级代谢产物的研究逐渐增加,但与温带和热带微生物研究相比仍处于初级阶段。对从南极普里兹湾海洋沉积物中获得的两株枝孢霉属真菌Cladosporium sp. NJF4和NJF6进行次级代谢产物分离及结构鉴定,获得20个化合物。化合物结构类型包括甾醇(1)、倍半萜类(7—8)、生物碱类(9—14)、二酮哌嗪(2—5、15—17)、芳香酸(6、18—19)等,其中倍半萜类(7—8)为首次从枝孢霉属真菌中分离得到,以上研究将为丰富南极微生物次级代谢产物库奠定一定的研究基础。     

Fe3O4/Mg(OH)2复合材料的制备及形貌控制

通过种子沉积法制备出Fe_3O_4/Mg(OH)_2复合材料并进行XRD、SEM测试分析。探究了氨水的浓度与加入速度、搅拌速度及等因素对磁性复合材料形貌的影响。氨水浓度与注入速度的降低,对氢氧化镁基体形貌的影响是相同的,但要使合成磁性复合材料形貌和四氧化三铁粒子在氢氧化镁中分散性均匀,应控制氨水浓度(ω=2.5%)或加入速度在一个合理的较低值。     

A machine learning approach for predicting computational intensity and domain decomposition in parallel geoprocessing

ABSTRACT

High performance computing is required for fast geoprocessing of geospatial big data. Using spatial domains to represent computational intensity (CIT) and domain decomposition for parallelism are prominent strategies when designing parallel geoprocessing applications. Traditional domain decomposition is limited in evaluating the computational intensity, which often results in load imbalance and poor parallel performance. From the data science perspective, machine learning from Artificial Intelligence (AI) shows promise for better CIT evaluation. This paper proposes a machine learning approach for predicting computational intensity, followed by an optimized domain decomposition, which divides the spatial domain into balanced subdivisions based on the predicted CIT to achieve better parallel performance. The approach provides a reference framework on how various machine learning methods including feature selection and model training can be used in predicting computational intensity and optimizing parallel geoprocessing against different cases. Some comparative experiments between the approach and traditional methods were performed using the two cases, DEM generation from point clouds and spatial intersection on vector data. The results not only demonstrate the advantage of the approach, but also provide hints on how traditional GIS computation can be improved by the AI machine learning.     

乡村空间重构的理论研究进展与理论框架构建

在新时代城乡融合发展、乡村地域人地关系日益复杂的背景下，乡村空间重构成为乡村地理学研究的重要课题。西方“后生产主义”语境下，乡村空间研究开始出现消费转向、社会-文化转向和后现代转向，多功能、全球化乡村转型与空间重构研究成为西方乡村空间研究的热点；国内研究主要基于乡村地理学人地关系地域系统理论展开乡村空间重构过程—机理—调控研究以及微观视角下农户经济空间行为研究；当前，中国乡村空间重构呈现自上而下的政治经济学转型特征，具有中国特色的农村集体组织与政府、企业、个人等其他主体之间的空间-权力关系成为乡村空间重构的重要视角。政治经济地理学及“社会-空间”二元辩证法为乡村空间重构研究提供了很好的研究范式与研究方法，乡村空间重构研究应系统整合空间生产、主体能动性、土地资本化、社会关系网络、人地关系地域系统和农户地理等政治经济学、地理学理论，强化自然、经济、社会和文化等多要素相互作用及其空间响应机制研究，重点开展多要素多维度的乡村空间格局形成及演变规律研究、乡村社会空间再生产研究、能动性视角下乡村劳动力空间生产研究、政府政策制度与城乡空间治理体系创新研究。     

Post-earthquake economic resilience and recovery efficiency in the border areas of the Tibetan Plateau: A case study of areas affected by the Wenchuan Ms 8.0 Earthquake in Sichuan,China in 2008

Journal of Geographical Sciences - The border areas of the Tibetan Plateau and the neighboring mountainous areas have a high incidence of earthquakes with a magnitude greater than Ms 5.0, as well...     

气候变化下基于物种与植物耦联机制的小白额雁(Anser erythropus)潜在生境及适宜性研究--以长江流域中下游为例

气候变化和人类活动通过改变物种生境而影响物种多样性。小白额雁是长江流域中下游的一种具有较高生态价值的食草型濒危候鸟,受气候变化和人类活动威胁。本文以小白额雁为代表性物种,定量分析了气候变化对长江流域中下游候鸟潜在生境及适宜性空间分布格局的影响。采用Maxent模型模拟了当前情景和全球环流模型(GCMs)气候场景下小白额雁潜在生境及其适宜性分布。研究结果表明,小白额雁分布特征与其栖息地周边植物分布呈显著相关关系;运用Maxent模型模拟小白额雁六种主要食源植物的分布特征,并将其结果作为环境变量,将显著改善小白额雁潜在生境及其适宜性模型的模拟性能;在两种典型浓度情景(RCP 2.6和RCP8.5)下,2070年小白额雁潜在生境适宜性面积将下降。为应对气候变化对小白额雁的影响,应采取更加合理的管理措施和保护政策,包括调整保护区的大小、形状和用途。     

广西土壤有机质空间变异特征及其影响因素研究

基于广西第二次土壤普查的270个土壤剖面资料,结合1∶50万数字化土壤类型图、土地利用类型图和气象监测数据等资料,利用地统计学和逐步回归分析等方法对广西表层土壤有机质空间变异特征及其影响因素进行了探究。结果表明：广西表层土壤有机质平均含量为3.11±2.19%,变异系数为70.72%,空间分布呈北高南低的趋势。广西表层土壤有机质空间分布受到自然和人为因素的共同影响,土壤类型、成土母质、海拔、土地利用、气候和坡度6个环境因子对全区土壤有机质含量变异的综合解释能力为47.9%。其中,土壤类型是最重要的影响因素,能独立解释其变异的36.0%,海拔和成土母质分别能独立解释28.5%和15.8%。气温对广西土壤有机质空间分布的影响比降水量更加显著,从而造成了广西土壤有机质整体呈南低北高的趋势。同时,土壤有机质对气温的敏感性在一定程度上受到降雨量的制约。此外,研究区农业耕作管理等因素对土壤有机质的影响也不容忽视。     

三元插层材料的合成及其在聚丙烯老化中的应用

以FeCl3?6H2O、NiCl2?6H2O、MgCl2?6H2O为原料，以NaOH为沉淀剂采用水热法合成了镁镍铁水滑石 (MgNiFe-LDH)，通过X射线衍射 (XRD)、傅里叶变换红外光谱 (FTIR) 和扫描电镜 (SEM) 分析了MgNiFe-LDH结构及形貌，探讨了不同陈化时间和水热温度对MgNiFe-LDH合成的影响。将制得的MgNiFe-LDH添加至聚丙烯 (PP) 中，制备MgNiFe-LDH/PP复合材料，通过对材料的加速老化测其力学性能，研究了添加MgNiFe-LDH前后材料力学性能的差异。研究结果表明，当Mg2+:Ni2+:Fe3+=2:1:1，反应温度为140℃、陈化时间为24 h时，合成的MgNiFe-LDH为片状，形貌较为规整，颗粒粒径约为2μm；经加速老化后，填充MgNiFe-LDH 复合材料的抗老化性能优于纯PP，当MgNiFe-LDH的填充量为6 wt% 复合材料拉伸强度不变，可明显提高PP的抗老化性能。     

EFFECTS OF FISH OIL,DHA OIL AND LECITIHIN IN MICROPARTICULATE DIETS ON STRESS TOLERANCE OF LARVAL GILTHEAD SEABREAM（SPARUS AURATA）

The effects of natural fish oil,DHA oil and soybean lecithin in microparticulate diets on stress tolerance of larval gilthead seabream(Sparus aurata)were investigated after 15 days feeding trials.The tolerance of larval gilthead seabream to various stress factors such as exposure to air(lack of dissolved oxygen),changes in water temperature(low)and salinity(high) were determined.This study showed that microparticulate diet with natural fish oil and soybean lecithin was the most effective for in-creasing the tolerance of larval gilthead seabream to various stresses,and that microparticulate diet with natural fish oil and palmitic acid(16:0)was more effective than microparticulate diet with DHA oil and soybean lecithin.