It has been proposed that anoxic and iron-rich (ferruginous) marine conditions were common through most of Earth history. This view represents a major shift in our understanding of the evolution of marine chemistry. However, thus far, evidence for ferruginous conditions comes predominantly from Fe-speciation data. Given debate over these records, new evidence for Fe-rich marine conditions is a requisite if we are to shift our view regarding evolution of the marine redox landscape. Here we present strong evidence for ferruginous conditions by describing a suite of Fe-rich chemical sedimentary rocks—banded iron formation (BIF)—-deposited during the Early Cambrian in western China. Specifically, we provide new U-Pb geochronological data that confirm a depositional age of ca. 527 Ma for this unit, as well as rare earth element (REE) data are consistent with anoxic deposition. Similar to many Algoma-type Precambrian iron formations, these Early Cambrian sediments precipitated in a back-arc rift basin setting, where hydrothermally sourced iron drove the deposition of a BIF-like protolith, the youngest ever reported of regional extent without direct links to volcanogenic massive sulphide (VMS) deposits. Their presence indicates that marine environments were still characterized by chemical- and redox-stratification, thus supporting the view that—despite a dearth of modern marine analogues—ferruginous conditions continued to locally be a feature of early Phanerozoic seawater.
Most algorithms for the high-dimensional data clustering are not intuitive and the clustering results are difficult to explain. To solve these problems, a new method based on the interactive visualization technology was proposed in this paper. First, the entropy-weight was adopted to determine the main attributes and how to arrange them. Every data was described in an improved radar chart in which polar radius stood by attribute values and polar angles stood by the attribute weights. Then the points in the radar chart were clustered through applying an improved k-means algorithm. The number of clusters was not given before. And initial centers were optimized according to the point density and their distance. Finally, the experiment showed that the improved radar chart reflected the distribution of the data better and that the improved k-means algorithm was more efficient and accuracy.
An aircraft cable fault location method based on detection model is proposed to solve the problem of being difficult to inspect the fault for the civil aviation maintenance. In response to the condition of the experimental installation, the reference signal is designed. The fault of the cable can be located according to the reflected waveform. An aircraft cable fault location system is designed and the experimental results show that the method is rational and effective.
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