An Early Cretaceous slab window beneath central Tibet,SW China: Evidence from OIB‐like alkaline gabbros in the Duolong area

The geodynamic mechanism of the late Early Cretaceous magmatic flare‐up in the collisional zone between the Lhasa and Qiangtang terranes in Tibet is controversial because of a scarcity of robust evidence. To address this problem, we report geochronological, geochemical and Hf isotopic data for the newly discovered Gufeng gabbros from the Duolong Cu–Au mineral district of the western Bangong–Nujiang Suture Zone (BNSZ). The gabbro samples, dated at 126.3 ± 1.8 Ma, show geochemical similarities to typical ocean island basalt (OIB) and have positive εHf(t) values of +3.3 to +6.9. The gabbros were generated by decompression melting of deep upwelling asthenosphere. This event is best explained by slab break‐off and the resultant development of a slab window beneath central Tibet.     

Assessment of alternative adsorption models and global sensitivity analysis to characterize hexavalent chromium loss from soil to surface runoff

We investigate our ability to assess transfer of hexavalent chromium, Cr(VI), from the soil to surface runoff by considering the effect of coupling diverse adsorption models with a two‐layer solute transfer model. Our analyses are grounded on a set of two experiments associated with soils characterized by diverse particle size distributions. Our study is motivated by the observation that Cr(VI) is receiving much attention for the assessment of environmental risks due to its high solubility, mobility, and toxicological significance. Adsorption of Cr(VI) is considered to be at equilibrium in the mixing layer under our experimental conditions. Four adsorption models, that is, the Langmuir, Freundlich, Temkin, and linear models, constitute our set of alternative (competing) mathematical formulations. Experimental results reveal that the soil samples characterized by the finest grain sizes are associated with the highest release of Cr(VI) to runoff. We compare the relative abilities of the four models to interpret experimental results through maximum likelihood model calibration and four model identification criteria (i.e., the Akaike information criteria [AIC and AIC_C] and the Bayesian and Kashyap information criteria). Our study results enable us to rank the tested models on the basis of a set of posterior weights assigned to each of them. A classical variance‐based global sensitivity analysis is then performed to assess the relative importance of the uncertain parameters associated with each of the models considered, within subregions of the parameter space. In this context, the modelling strategy resulting from coupling the Langmuir isotherm with a two‐layer solute transfer model is then evaluated as the most skilful for the overall interpretation of both sets of experiments. Our results document that (a) the depth of the mixing layer is the most influential factor for all models tested, with the exception of the Freundlich isotherm, and (b) the total sensitivity of the adsorption parameters varies in time, with a trend to increase as time progresses for all of the models. These results suggest that adsorption has a significant effect on the uncertainty associated with the release of Cr(VI) from the soil to the surface runoff component.     

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.     

LHRH-A和hCG对南方鲶血清促性腺激素水平的影响

运用放射免疫分析法测定了促黄体释放激素类似物 (LHRH A)和人绒毛膜促性腺激素(hCG)对南方鲶血清促性腺激素 (GTH)水平的影响 ,结果表明 :LHRH A和hCG都能提高南方鲶一龄幼鱼血清GTH水平 ,hCG与LHRH A结合注射后血清GTH水平显著高于单独注射hCG或LHRH A后的血清GTH水平。LHRH A和hCG结合注射可诱导性成熟南方鲶排卵 ,同时排卵过程中伴随着血清GTH水平的急剧上升 ,在排卵后迅速下降 ;注射同样剂量的药物而未排卵的血清GTH水平虽有升高 ,但升高的幅度不及排卵鱼。这种血清GTH水平的急剧增高对诱导南方鲶卵母细胞最后成熟和排卵具有重要作用。     

A STUDY ON LAND SYSTEM INNOVATIONS IN THE CONSTRUCTION OF SMALL TOWNS IN CHINA

The economic development in China and the rising of the living standard need to speed up the urbanisa-tion.The development of small towns is an important way to Chinese urbanization.Land use plays a very important role in the development of small towns.However there are many problems in the development of small towns,esp.in land use.The paper first discusses the land problems in the development of small towns.Such as much cultivated land lies idle,under-utilization and waste of land,increasing illegal use of land,unstable contractural relationship for land use.The relationship between the development of small towns and land use is also studied.Then the guidelines for the land system innovations of small towns are put forward.Namely the sustainability of social and economic development,the bal-ance between land reservation and land utilization,the provision of service to village ,agriculture and farmer,the manage-ment of land resource and land assets,the parsimonious andlegal use of land.The basic framework of land system innova-tions of small towns is put forward finally.It include the land replacement policy for small towns and the permanent tenan-cy of farmland,the overall plan for land uses and other plans in harmony,the establishment of a flexible system of land supplies,using land with payments ,the transfer of agricultural land and refining the land law related to the construction of small towns.     

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.     

ECOLOGICAL SERIES OF SOIL ANIMALS IN DARLIDAI MOUNTAIN

The ecological series of soil animals under the broad-leaved and pine mixed forest in Darlidai Mountainwas studied. Seven sample plots were selected according to different altitude gradients, which belong to different vegeta-tion types. By investigating and analyzing soil animals in every sample plot it is found that there are 45 groups and 1956individuals, which axe involved in 3 phylums, 7 classes, 16 orders, respectively. The altitude is a key factor which af-fects ecological series of soil animals. Both the groups and individuals of soil animals increase with altitude increasingunder certain conditions, which contrastes with ordinary cases, resulting from special micro-climate in studied area. Thegroups and individuls of soil animals are the most under the broad-leaved and pine forest on the top of the mountain, andthe least under Picea-Abies forest in the foot of the mountain.     

初轨计算中的病态分析

本文对现有初轨计算方法进行病态性分析与误差分析；研究结果表明：病态对现有初轨算法的影响，主要来源于法方程系数中包含观测误差．系数行列式愈大，定轨精度的损失愈多，当■被随机误差项△μ淹盖时，现有初轨算法将失效．此外，仿真结果还显示：■与△μ的大小还极大地依赖观测弧段的空间位置，当观测弧段包含近站点作为中点时，■最大，而■小，此时定轨精度较高；当观测弧段位于近站点的某一侧时，■小，而■大，此时定轨精度较低，观测弧段愈偏离近站点，病态影响愈大；因而在观测时，应尽量使观测弧段与近站点对称（此时μ值较大），这是提高短弧定轨的一种有效途径．