Simultaneous qualitative and quantitative analysis of Tangkening granule using thin layer chromatography (TLC) and high performance liquid chromatography (HPLC)

This study was designed to establish the quality standard of Tangkening granule in order to effectively control the quality of this new Chinese traditional patent medicine in the process of production, in addition to ensure the good clinical application. Fructus gardenia, Herba gynostemmatis, Dioscorea batatas, and Polygonatum odoratum in Tangkening granule were identified by thin layer chromatography (TLC), and the content of geniposide was determined by high performance liquid chromatography (HPLC). A comprehensive validation of the method that included sensitivity, linearity, repeatability and recovery was conducted. The results show that this analytical method was simple and suitable for the original identification and quality control of this new Chinese traditional patent medicine.Key words: Tangkening granule, geniposide, quality standard, thin layer chromatography, high performance liquid chromatography

Calorimetric Evidence of Strong-Coupling Multiband Superconductivity in Fe(Te0.57Se0.43) Single Crystal

We have investigated the specific heat of optimally-doped iron chalcogenide superconductor Fe(Te0.57Se0.43) with a high-quality single crystal sample. The electronic specific heat Ce of this sample has been successfully separated from the phonon contribution using the specific heat of a non-superconducting sample (Fe0.90Cu0.10)(Te0.57Se0.43) as a reference. The normal state Sommerfeld coefficient gamma_n of the superconducting sample is found to be ~ 26.6 mJ/mol K^2, indicating intermediate electronic correlation. The temperature dependence of Ce in the superconducting state can be best fitted using a double-gap model with 2Delta_s(0)/kBTc = 3.92 and 2Delta_l(0)/kBTc = 5.84. The large gap magnitudes derived from fitting, as well as the large specific heat jump of Delta_Ce(Tc)/gamma_n*Tc ~ 2.11, indicate strong-coupling superconductivity. Furthermore, the magnetic field dependence of specific heat shows strong evidence for multiband superconductivity

Principal Graph and Structure Learning Based on Reversed Graph Embedding

© 2017 IEEE. Many scientific datasets are of high dimension, and the analysis usually requires retaining the most important structures of data. Principal curve is a widely used approach for this purpose. However, many existing methods work only for data with structures that are mathematically formulated by curves, which is quite restrictive for real applications. A few methods can overcome the above problem, but they either require complicated human-made rules for a specific task with lack of adaption flexibility to different tasks, or cannot obtain explicit structures of data. To address these issues, we develop a novel principal graph and structure learning framework that captures the local information of the underlying graph structure based on reversed graph embedding. As showcases, models that can learn a spanning tree or a weighted undirected ℓ1 graph are proposed, and a new learning algorithm is developed that learns a set of principal points and a graph structure from data, simultaneously. The new algorithm is simple with guaranteed convergence. We then extend the proposed framework to deal with large-scale data. Experimental results on various synthetic and six real world datasets show that the proposed method compares favorably with baselines and can uncover the underlying structure correctly

Emergence of intrinsic superconductivity below 1.178 K in the topologically non-trivial semimetal state of CaSn3

Topological materials which are also superconducting are of great current interest, since they may exhibit a non-trivial topologically-mediated superconducting phase. Although there have been many reports of pressure-tuned or chemical-doping-induced superconductivity in a variety of topological materials, there have been few examples of intrinsic, ambient pressure superconductivity in a topological system having a stoichiometric composition. Here, we report that the pure intermetallic CaSn3 not only exhibits topological fermion properties but also has a superconducting phase at 1.178 K under ambient pressure. The topological fermion properties, including the nearly zero quasi-particle mass and the non-trivial Berry phase accumulated in cyclotron motions, were revealed from the de Haas-van Alphen (dHvA) quantum oscillation studies of this material. Although CaSn3 was previously reported to be superconducting at 4.2K, our studies show that the superconductivity at 4.2K is extrinsic and caused by Sn on the degraded surface, whereas its intrinsic bulk superconducting transition occurs at 1.178 K. These findings make CaSn3 a promising candidate for exploring new exotic states arising from the interplay between non-trivial band topology and superconductivity, e.g. topological superconductivityComment: 20 pages,4 figure

A Least Squares Collocation Method for Accuracy Improvement of Mobile LiDAR Systems

In environments that are hostile to Global Navigation Satellites Systems (GNSS), the precision achieved by a mobile light detection and ranging (LiDAR) system (MLS) can deteriorate into the sub-meter or even the meter range due to errors in the positioning and orientation system (POS). This paper proposes a novel least squares collocation (LSC)-based method to improve the accuracy of the MLS in these hostile environments. Through a thorough consideration of the characteristics of POS errors, the proposed LSC-based method effectively corrects these errors using LiDAR control points, thereby improving the accuracy of the MLS. This method is also applied to the calibration of misalignment between the laser scanner and the POS. Several datasets from different scenarios have been adopted in order to evaluate the effectiveness of the proposed method. The results from experiments indicate that this method would represent a significant improvement in terms of the accuracy of the MLS in environments that are essentially hostile to GNSS and is also effective regarding the calibration of misalignment

Lattice dynamics and electron-phonon coupling in Sr2RuO4

The lattice dynamics in Sr$_2$RuO$_4$ has been studied by inelastic neutron scattering combined with shell-model calculations. The in-plane bond-stretching modes in Sr$_2$RuO$_4$ exhibit a normal dispersion in contrast to all electronically doped perovskites studied so far. Evidence for strong electron phonon coupling is found for c-polarized phonons suggesting a close connection with the anomalous c-axis charge transport in Sr$_2$RuO$_4$.Comment: 11 pages, 8 figures 2 table

Interference Minimization in 5G Heterogeneous Networks

© 2015, Springer Science+Business Media New York. In this paper, we focus on one of the representative 5G network scenarios, namely multi-tier heterogeneous cellular networks. User association is investigated in order to reduce the down-link co-channel interference. Firstly, in order to analyze the multi-tier heterogeneous cellular networks where the base stations in different tiers usually adopt different transmission powers, we propose a Transmission Power Normalization Model (TPNM), which is able to convert a multi-tier cellular network into a single-tier network, such that all base stations have the same normalized transmission power. Then using TPNM, the signal and interference received at any point in the complex multi-tier environment can be analyzed by considering the same point in the equivalent single-tier cellular network model, thus significantly simplifying the analysis. On this basis, we propose a new user association scheme in heterogeneous cellular networks, where the base station that leads to the smallest interference to other co-channel mobile stations is chosen from a set of candidate base stations that satisfy the quality-of-service (QoS) constraint for an intended mobile station. Numerical results show that the proposed user association scheme is able to significantly reduce the down-link interference compared with existing schemes while maintaining a reasonably good QoS

Orbital-dependent metamagnetic response in Sr4Ru3O10

We show that the metamagnetic transition in Sr$_4$Ru$_3$O$_{10}$ bifurcates into two transitions as the field is rotated away from the conducting planes. This two-step process comprises partial or total alignment of moments in ferromagnetic bands followed by an itinerant metamagnetic transition whose critical field increases with rotation. Evidence for itinerant metamagnetism is provided by the Shubnikov-de Hass effect which shows a non-trivial evolution of the geometry of the Fermi surface and an enhancement of the quasiparticles effective-mass across the transition. The metamagnetic response of Sr$_4$Ru$_3$O$_{10}$ is orbital-dependent and involves ferromagnetic and metamagnetic bands.Comment: Physical Review B (in press

Multi-view urban scene reconstruction in non-uniform volume

This paper presents a new fully automatic approach for multi-view urban scene reconstruction. Our algorithm is based on the Manhattan-World assumption, which can provide compact models while preserving fidelity of synthetic architectures. Starting from a dense point cloud, we extract its main axes by global optimization, and construct a nonuniform volume based on them. A graph model is created from volume facets rather than voxels. Appropriate edge weights are defined to ensure the validity and quality of the surface reconstruction. Compared with the common pointcloud- to-model methods, the proposed methodology exploits image information to unveil the real structures of holes in the point cloud. Experiments demonstrate the encouraging performance of the algorithm. © 2013 SPIE