Retrieving volume FeO and TiO_2 abundances of lunar regolith with CE-2 CELMS data using BPNN method

The volume FeO and TiO_2 abundances(FTAs) of lunar regolith can be more important for understanding the geological evolution of the Moon compared to the optical and gamma-ray results. In this paper, the volume FTAs are retrieved with microwave sounder(CELMS) data from the Chang'E-2 satellite using the back propagation neural network(BPNN) method. Firstly, a three-layered BPNN network with five-dimensional input is constructed by taking nonlinearity into account. Then, the brightness temperature(TB) and surface slope are set as the inputs and the volume FTAs are set as the outputs of the BPNN network.Thereafter, the BPNN network is trained with the corresponding parameters collected from Apollo, Luna,and Surveyor missions. Finally, the volume FTAs are retrieved with the trained BPNN network using the four-channel TBderived from the CELMS data and the surface slope estimated from Lunar Orbiter Laser Altimeter(LOLA) data. The rationality of the retrieved FTAs is verified by comparing with the Clementine UV-VIS results and Lunar Prospector(LP) GRS results. The retrieved volume FTAs enable us to re-evaluate the geological features of the lunar surface. Several important results are as follows. Firstly, very-low-Ti(1.5 wt.%) basalts are the most spatially abundant, and the surfaces with TiO_2 5 wt.% constitute less than 10% of the maria. Also, two linear relationships occur between the FeO abundance(FA) and the TiO_2 abundance before and after the threshold, 16 wt.% for FA. Secondly, a new perspective on mare volcanism is derived with the volume FTAs in several important mare basins, although this conclusion should be verified with more sources of data. Thirdly, FTAs in the lunar regolith change with depth to the uppermost surface,and the change is complex over the lunar surface. Finally, the distribution of volume FTAs hints that the highlands crust is probably homogeneous, at least in terms of the microwave thermophysical parameters.     

Classification of stellar spectra with SVM based on within-class scatter and between-class scatter

Support Vector Machine (SVM) is a popular data mining technique, and it has been widely applied in astronomical tasks, especially in stellar spectra classification. Since SVM doesn’t take the data distribution into consideration, and therefore, its classification efficiencies can’t be greatly improved. Meanwhile, SVM ignores the internal information of the training dataset, such as the within-class structure and between-class structure. In view of this, we propose a new classification algorithm-SVM based on Within-Class Scatter and Between-Class Scatter (WBS-SVM) in this paper. WBS-SVM tries to find an optimal hyperplane to separate two classes. The difference is that it incorporates minimum within-class scatter and maximum between-class scatter in Linear Discriminant Analysis (LDA) into SVM. These two scatters represent the distributions of the training dataset, and the optimization of WBS-SVM ensures the samples in the same class are as close as possible and the samples in different classes are as far as possible. Experiments on the K-, F-, G-type stellar spectra from Sloan Digital Sky Survey (SDSS), Data Release 8 show that our proposed WBS-SVM can greatly improve the classification accuracies.     

Extreme Flood Events over the Past 300 Years Inferred from Lake Sedimentary Grain Sizes in the Altay Mountains,Northwestern China

Understanding the temporal variations of extreme floods that occur in response to climate change is essential to anticipate the trends in flood magnitude and frequency in the context of global warming. However, long-term records of paleofloods in arid regions are scarce, thus preventing a thorough understanding of such events. In this study, a reconstruction of paleofloods over the past 300 years was conducted through an analysis of grain sizes from the sediments of Kanas Lake in the Altay Mountains of northwestern China. Results showed that grain parameters and frequency distributions can be used to infer possible abrupt environmental events within the lake sedimentary sequence, and two extreme flood events corresponding to ca. 1736–1765 AD and ca. 1890 AD were further identified based on canonical discriminant analysis(CDA) and coarse percentile versus median grain size(C-M) pattern analysis, both of which occurred during warmer and wetter climate conditions by referring to tree-ring records. These two flood events are also evidenced by lake sedimentary records in the Altay and Tianshan mountains. Furthermore, through a comparison with other records, the flood event from ca. 1736–1765 AD in the study region seems to have occurred in both the arid central Asia and the Alps in Europe, and thus may have been associated with changes in the North Atlantic Oscillation(NAO) index.     

风和径流量对长江口缺氧影响的数值模拟

受自然和人类活动的影响，海洋缺氧现象日益严重，威胁着海洋生态环境，海洋缺氧问题已经引起了人们的广泛关注。本文应用区域海洋模式并耦合生态模式，对东海的生态系统进行了数值模拟和分析研究。与观测数据比较显示，该模型能较好地模拟长江口外生态变量的分布趋势。另外本文通过设置不同敏感性实验，探讨风和径流量对长江口底层缺氧现象的影响，结果分析表明，风和径流量对长江口外缺氧区的形成有显著的影响。径流量变化虽然对长江口外缺氧区的季节变化影响并不显著，但是对缺氧区域面积却存在显著的影响。径流量增加，水体层化增强，表层叶绿素浓度增加，最终导致缺氧区域范围扩展；径流量减小，水体层化减弱，表层叶绿素浓度减小，缺氧区域范围缩小。风向和风速的改变不仅影响长江口外缺氧区的季节变化，还影响缺氧区域面积。     

Soil and Vegetation Spectral Coupling Difference (SVSCD) for Minerals Extraction from Hyperion Data in Vegetation Covered Area

Remote sensing data have been widely applied to extract minerals in geologic exploration, however, in areas covered by vegetation, extracted mineral information has mostly been small targets bearing little information. In this paper, we present a new method for mineral extraction aimed at solving the difficulty of mineral identification in vegetation covered areas. The method selected six sets of spectral difference coupling between soil and plant (SVSCD). These sets have the same vegetation spectra reflectance and a maximum different reflectance of soil and mineral spectra from Hyperion image based on spectral reflectance characteristics of measured spectra. The central wavelengths of the six, selected band pairs were 2314 and 701 nm, 1699 and 721 nm, 1336 and 742 nm, 2203 and 681 nm, 2183 and 671 nm, and 2072 and 548 nm. Each data set’s reflectance was used to calculate the difference value. After band difference calculation, vegetation information was suppressed and mineral abnormal information was enhanced compared to the scatter plot of original band. Six spectral difference couplings, after vegetation inhibition, were arranged in a new data set that requires two components that have the largest eigenvalue difference from principal component analysis (PCA). The spatial geometric structure features of PC1 and PC2 was used to identify altered minerals by spectral feature fitting (SFF). The collecting rocks from the 10 points that were selected in the concentration of mineral extraction were analyzed under a high-resolution microscope to identify metal minerals and nonmetallic minerals. Results indicated that the extracted minerals were well matched with the verified samples, especially with the sample 2, 4, 5 and 8. It demonstrated that the method can effectively detect altered minerals in vegetation covered area in Hyperion image.     

Prediction of Blast-Induced Rock Movement During Bench Blasting: Use of Gray Wolf Optimizer and Support Vector Regression

Natural Resources Research - A large ore loss and dilution can be expected when using a pre-blast ore boundary for shovel guidance because of the movement and re-distribution of ore in the muck...     

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...     

Fast genetic mapping in barley: case studies of cuticle mutants using RNA-sequencing

Barley(Hordeum vulgare L.) is one of the earliest domesticated crop species and ranked as the fourth largest cereal production worldwide. Forward genetic studies in barley have greatly advanced plant genetics during the last century; however, most genes are identified by the conventional mapping method. Array genotyping and exome-capture sequencing have also been successfully used to target the causal mutation in barley populations, but these techniques are not widely adopted because of associated costs and partly due to the huge genome size of barley. This review summarizes three mapping cases of barley cuticle mutants in our laboratory with the help of RNA-sequencing. The causal mutations have been successfully identified for two of them and the target genes are located in the pericentromeric regions. Detailed information on the mapping-by-sequencing, mapping-and-sequencing, and RNA-sequencing assisted linkage mapping are presented and some limitations and challenges on the mapping assisted by RNA sequencing are also discussed. The alternative and elegant methods presented in this review may greatly accelerate forward genetics of barley mapping, especially for laboratories without large funding.     

青藏高原隆升的非线性动态有限元仿真研究

根据青藏高原的地质特征建立分析模型，采用3维动态有限元方法，在计算仿真板块速度场的基础上，计算在青藏高原的隆升过程中该地区地壳岩石的等效应力和位移随时间的变化，计算仿真得到的速度场与1998年GPS观测的速度场吻合良好；与过去一贯的假设相反，计算结果反映出地壳应力场不是静态的，而是此起彼伏，不断变化的，应力值最大且变化最剧烈的地区在克什米尔地区、鄂尔多斯地区和鲜水河－小江断裂带，与地震多发区域吻合。     

Discovery of 13 New Variable Stars in the Field of the Open Cluster NGC 2168 （M35）

A wide-field time-series CCD photometric survey of variable stars in the field of the open cluster NGC 2168 was carried out using the BATC Schmidt telescope. In total 13 new variable stars are discovered with three W UMa systems, one EA type and two EB type eclipsing binaries (one of them could be a W UMa system), and seven pulsating stars including three candidates of δScuti stars.