Establishment of the Luoping Biota National Geopark in Yunnan, China

Geoparks in China have been a great success story, with 284 national geoparks and 41 of them accorded UNESCO international status, the highest number for any country in the world. We track the progress of one of the geoparks, Luoping Biota National Geopark in Yunnan Province, from initial plans after its discovery as a key site for the exceptional preservation of Middle Triassic marine fossils in 2007, to acceptance as a National Geopark in 2011. Geoparks combine great scientific importance with accessibility and attraction for tourists. The scientific importance of Luoping is in the fossils, thousands of specimens of marine invertebrates, fishes and reptiles, together with rare elements from land (e.g. insects, plants), representing an important phase in the Mesozoic Marine Revolution, when life was recovering from devastation at the end of the Permian, and 8 million years later, had developed stable ecosystems with a new structure, dominated by predatory fishes and reptiles. The touristic importance of the Luoping Biota Geopark has already been demonstrated by rapid development of facilities and high visitor numbers

A new millipede (Diplopoda, Helminthomorpha) from the Middle Triassic Luoping biota of Yunnan, Southwest China

AbstractA new helminthomorph millipede,Sinosoma luopingensenew genus new species, from the Triassic Luoping biota of China, has 39 body segments, metazonites with lateral swellings that bear a pair of posterolateral pits (?insertion pits for spine bases), and sternites that are unfused to the pleurotergites. This millipede shares a number of characters with nematophoran diplopods, but lacks the prominent dorsal suture characteristic of that order. Other “millipede” material from the biota is more problematic. Millipedes are a rare part of the Luoping biota, which is composed mainly of marine and near-shore organisms. Occurrences of fossil millipedes are exceedingly rare in Triassic rocks worldwide, comprising specimens from Europe, Asia, and Africa, and consisting of juliform millipedes and millipedes that are either nematophorans or forms very similar to nematophorans.</jats:p

Exceptional appendage and soft-tissue preservation in a Middle Triassic horseshoe crab from SW China

Abstract Horseshoe crabs are classic “living fossils”, supposedly slowly evolving, conservative taxa, with a long fossil record back to the Ordovician. The evolution of their exoskeleton is well documented by fossils, but appendage and soft-tissue preservation is extremely rare. Here we analyse details of appendage and soft-tissue preservation in Yunnanolimulus luopingensis, a Middle Triassic (ca. 244 million years old) horseshoe crab from Yunnan Province, SW China. The remarkable preservation of anatomical details including the chelicerae, five pairs of walking appendages, opisthosomal appendages with book gills, muscles, and fine setae permits comparison with extant horseshoe crabs. The close anatomical similarity between the Middle Triassic horseshoe crabs and their recent analogues documents anatomical conservatism for over 240 million years, suggesting persistence of lifestyle. The occurrence of Carcinoscorpius-type claspers on the first and second walking legs in male individuals of Y. luopingensis indicates that simple chelate claspers in males are plesiomorphic for horseshoe crabs, and the bulbous claspers in Tachypleus and Limulus are derived

Operation Analysis of a SAG Mill under Different Conditions Based on DEM and Breakage Energy Method

As one of the machines widely used in mining, a semi-autogenous grinding (SAG) mill can significantly improve the roughing efficiency of rock. But the SAG mill still faces the obstacles of significant energy consumption and empirical operation parameters. In order to obtain the optimal operation parameters of a SAG mill, in this paper, the discrete element method (DEM) is used to simulate the breakage process of the particles by controlling three parameters, i.e., the mill speed ratio, the mill fill level ratio, and the steel ball ratio. This method simulates the particles size, mill power, and qualified particles quality of crushed particle, which reveal the grinding strength and energy consumption of the SAG mill. In this paper, the grinding changes of a SAG mill under different parameter conditions are explored. Firstly, an experiment on the influence of a single parameter change on the mill&rsquo;s operation is set up, and then the influence of three parameter changes on the mill&rsquo;s operation is analyzed. These changes are characterized by particle size and mill power. Simulation results under the &empty;5250 &times; 500 mm mill model show that the mill operates with the optimal effect when the mill is under the condition of 80% critical speed and 15% fill level; the power of the mill does not increase linearly with an increase in the mill speed ratio, but will decrease after 85% of the critical speed, and finally increase again; the optimal steel ball ratio in the SAG mill depends on the simulation time (mill actual working time) and the limitation of the rated power. The mill speed, fill level ratio, and steel ball ratio can significantly affect mill operation, and our conclusions can provide a reference for an actual situation

Cost-Sensitive Support Vector Machine Using Randomized Dual Coordinate Descent Method for Big Class-Imbalanced Data Classification

Cost-sensitive support vector machine is one of the most popular tools to deal with class-imbalanced problem such as fault diagnosis. However, such data appear with a huge number of examples as well as features. Aiming at class-imbalanced problem on big data, a cost-sensitive support vector machine using randomized dual coordinate descent method (CSVM-RDCD) is proposed in this paper. The solution of concerned subproblem at each iteration is derived in closed form and the computational cost is decreased through the accelerating strategy and cheap computation. The four constrained conditions of CSVM-RDCD are derived. Experimental results illustrate that the proposed method increases recognition rates of positive class and reduces average misclassification costs on real big class-imbalanced data

An Improved Adaptive Iterative Extended Kalman Filter Based on Variational Bayesian

The presence of unknown heavy-tailed noise can lead to inaccuracies in measurements and processes, resulting in instability in nonlinear systems. Various estimation methods for heavy-tailed noise exist. However, these methods often trade estimation accuracy for algorithm complexity and parameter sensitivity. To tackle this challenge, we introduced an improved variational Bayesian (VB)-based adaptive iterative extended Kalman filter. In this VB framework, the inverse Wishart distributionis used as the prior for the state prediction covariance matrix. The system state and noise parameter posterior distributions are then iteratively updated for adaptive estimation. Furthermore, we make adaptive adjustments to the IEKF filter parameters to enhance sensitivity and filtering accuracy, thus ensuring robust prediction estimation. A two-dimensional target tracking and nonlinear numerical UNGM simulation validated our algorithm. Compared to existing algorithms RKF-ML and GA-VB, our method showed significant improvements in RMSEpos and RMSEvel, with increases of 21.81% and 22.11% respectively, and a 49.04% faster convergence speed. These results highlight the method’s reliability and adaptability

On-Orbit Radiometric Calibration for a Space-Borne Multi-Camera Mosaic Imaging Sensor

As the core and foundational technology, on-orbit radiometric calibration of a space-borne sensor is of great importance for quantitative remote sensing applications. As for the space-borne multi-camera mosaic imaging sensor, however, the currently available on-orbit radiometric calibration method cannot carry out the integrated processing of on-orbit absolute radiometric calibration and relative radiometric correction simultaneously between cameras, influencing the accuracy of quantitative applications. Therefore, taking the GaoFen-1 (GF-1) wide-field-of-view (WFV) sensor as an example in this research, an innovative on-orbit radiometric calibration method is proposed to overcome this bottleneck. Firstly, according to the principle of the cross-calibration approach, we retrieve valid MODIS and GF-1 WFV image pairs over the Dunhuang radiometric calibration sites (DRCS) in China by using a set of criteria and extract the radiometric control points (RCPs) connecting in both images. Secondly, the DEM-aided block adjustment of the rational function model is applied to eliminate the geometrical misalignment of GF-1 WFV images at the same orbit. Then, the average digital numbers of spectral and spatial homogeneous surfaces are calculated and chosen as the radiometric tie points (RTPs) extracted from the overlapping region of the adjacent WFV cameras. Thirdly, the radiometric block adjustment (RBA) algorithm is introduced into on-orbit radiometric calibration of the space-borne multi-camera mosaic imaging sensor. Finally, the radiometric calibration coefficients are solved by the least square method. The validation results indicate that our proposed method can acquire high absolute radiometric calibration accuracy and achieve relative radiometric correction between cameras. Compared with the results using the cross-calibration method to calibrate each WFV camera independently, the advantages of RBA are presented. In addition, the uncertainties caused by RCPs’ distribution are discussed, which is beneficial to further optimize the calibration program

Radiometric cross-calibration of GF-4 satellite PMS sensor considering the characteristics of multiple integration times

Integrating the five integration times characteristics of GF-4 satellite PMS sensor,a radiometric cross-calibration method based on the radiometric block adjustment is proposed. Taking Dunhuang radiometric calibration sites (DRCS) in China as the radiometric transfer platform. Firstly, collecting the valid time-series MODIS images over DRCS to build the BRDF model. Secondly, considering the SBAF and BRDF, the radiometric control points (RCPs) are extracted from the image pairs of Landsat-8 OLI and PMS over DRCS. Thirdly, after setting the restrictive conditions of DN and CV, the radiometric tie points (RTPs) are extracted from PMS images in different integration times under the stare imaging condition. Finally, the radiometric cross-calibration coefficients of five integration times are solved based on the proposed method. The validation results show that the average absolute calibration relative errors of five integration times are all less than 5.18% and the relative radiometric correction errors of five integration times reduce up to 36.64%. Meanwhile, the influences of the RCPs distribution, the restrictive conditions in the process of RTPs extraction, SBAF and BRDF on the calibration results are discussed, which is beneficial to further optimize the radiometric cross-calibration program of PMS