A Study of Third-party Online Payment: Risk Control and Supervision Analysis

In recent years, with the continuous development of E-commerce, the third-party online payment pattern is gaining increasingly popularity among users. Characterized by its convenience, high-credibility and safety, it has become the mainstream pattern of online payment. With its rapid development, the third-party online payment has drawn more and more attention among people from all circles. And the focus of the attention is on the risks of using this platform. In this paper, the author introduces the present development status of the third-party online payment. On the basis of that, the paper focuses on the risk analysis and supervision in the process of operation by employing scenario analysis and list technique. In order to prevent and control risks in the third-party online payment, we should study the third-party online payment market thoroughly and take all aspects into consideration. It will shape a healthy and stable development trend only when all parties related work cooperatively

Insufficient ER-stress response causes selective mouse cerebellar granule cell degeneration resembling that seen in congenital disorders of glycosylation

BACKGROUND: Congenital disorders of glycosylation (CDGs) are inherited diseases caused by glycosylation defects. Incorrectly glycosylated proteins induce protein misfolding and endoplasmic reticulum (ER) stress. The most common form of CDG, PMM2-CDG, is caused by deficiency in the cytosolic enzyme phosphomannomutase 2 (PMM2). Patients with PMM2-CDG exhibit a significantly reduced number of cerebellar Purkinje cells and granule cells. The molecular mechanism underlying the specific cerebellar neurodegeneration in PMM2-CDG, however, remains elusive. RESULTS: Herein, we report that cerebellar granule cells (CGCs) are more sensitive to tunicamycin (TM)-induced inhibition of total N-glycan synthesis than cortical neurons (CNs). When glycan synthesis was inhibited to a comparable degree, CGCs exhibited more cell death than CNs. Furthermore, downregulation of PMM2 caused more CGCs to die than CNs. Importantly, we found that upon PMM2 downregulation or TM treatment, ER-stress response proteins were elevated less significantly in CGCs than in CNs, with the GRP78/BiP level showing the most significant difference. We further demonstrate that overexpression of GRP78/BiP rescues the death of CGCs resulting from either TM-treatment or PMM2 downregulation. CONCLUSIONS: Our results indicate that the selective susceptibility of cerebellar neurons to N-glycosylation defects is due to these neurons’ inefficient response to ER stress, providing important insight into the mechanisms of selective neurodegeneration observed in CDG patients

Learning to Learn Kernels with Variational Random Features

In this work, we introduce kernels with random Fourier features in the meta-learning framework to leverage their strong few-shot learning ability. We propose meta variational random features (MetaVRF) to learn adaptive kernels for the base-learner, which is developed in a latent variable model by treating the random feature basis as the latent variable. We formulate the optimization of MetaVRF as a variational inference problem by deriving an evidence lower bound under the meta-learning framework. To incorporate shared knowledge from related tasks, we propose a context inference of the posterior, which is established by an LSTM architecture. The LSTM-based inference network can effectively integrate the context information of previous tasks with task-specific information, generating informative and adaptive features. The learned MetaVRF can produce kernels of high representational power with a relatively low spectral sampling rate and also enables fast adaptation to new tasks. Experimental results on a variety of few-shot regression and classification tasks demonstrate that MetaVRF delivers much better, or at least competitive, performance compared to existing meta-learning alternatives.Comment: ICML'2020; code is available in: https://github.com/Yingjun-Du/MetaVR

Optimization of Minimum Negative Current BCM Synchronous Buck Converter

Non-isolated DC-DC converters are widely used in renewable energy applications, such as the hybrid energy storage system (HESS), charging and discharging system of batteries and supercapacitors and the photovoltaic power generation. With the advantages of achieving zero-voltage-switching (ZVS), high efficiency and power density, low cost, and fast dynamic response, the converters operating in boundary current mode (BCM) have caught researchers' eyes recently. Taking the synchronous buck converters as an example, this paper briefly introduces the working principle and advantages of BCM converter realize soft switching. Firstly, it is pointed out that the phenomenon of circulating energy exists in the BCM converter. Then, the relationship between circulating energy and negative current is analyzed, and an optimal control strategy of negative current minimization is proposed to reduce the circulating energy. In the condition of realizing ZVS, negative current minimization not only improves the efficiency of the converter, but also reduces the ripple of inductor current to a certain extent. Finally, the experimental platform of 100 W synchronous buck converter is built. Experimental results validate that the optimal control of minimum negative current has good effect on improving efficiency of converter and reducing the ripple of inductor current

Multiple-relaxation-time lattice Boltzmann model for compressible fluids

We present an energy-conserving multiple-relaxation-time finite difference lattice Boltzmann model for compressible flows. This model is based on a 16-discrete-velocity model. The collision step is first calculated in the moment space and then mapped back to the velocity space. The moment space and corresponding transformation matrix are constructed according to the group representation theory. Equilibria of the nonconserved moments are chosen according to the need of recovering compressible Navier-Stokes equations through the Chapman-Enskog expansion. Numerical experiments showed that compressible flows with strong shocks can be well simulated by the present model. The used benchmark tests include (i) shock tubes, such as the Sod, Lax, Sjogreen, Colella explosion wave and collision of two strong shocks, (ii) regular and Mach shock reflections, and (iii) shock wave reaction on cylindrical bubble problems. The new model works for both low and high speeds compressible flows. It contains more physical information and has better numerical stability and accuracy than its single-relaxation-time version.Comment: 11 figures, Revte

Two-Dimensional Lattice Boltzmann Model For Compressible Flows With High Mach Number

In this paper we present an improved lattice Boltzmann model for compressible Navier-Stokes system with high Mach number. The model is composed of three components: (i) the discrete-velocity-model by Watari and Tsutahara [Phys Rev E \textbf{67},036306(2003)], (ii) a modified Lax-Wendroff finite difference scheme where reasonable dissipation and dispersion are naturally included, (iii) artificial viscosity. The improved model is convenient to compromise the high accuracy and stability. The included dispersion term can effectively reduce the numerical oscillation at discontinuity. The added artificial viscosity helps the scheme to satisfy the von Neumann stability condition. Shock tubes and shock reflections are used to validate the new scheme. In our numerical tests the Mach numbers are successfully increased up to 20 or higher. The flexibility of the new model makes it suitable for tracking shock waves with high accuracy and for investigating nonlinear nonequilibrium complex systems

In situ correction of various β-thalassemia mutations in human hematopoietic stem cells

β-thalassemia (β-thal) is the most common monogenic disorder caused by various mutations in the human hemoglobin β (HBB) gene and affecting millions of people worldwide. Electroporation of Cas9 and single-guide RNA (sgRNA)–ribonucleoprotein (RNP) complex-mediated gene targeting in patient-derived hematopoietic stem cells (HSCs), followed by autologous transplantation, holds the promise to cure patients lacking a compatible bone marrow donor. In this study, a universal gene correction method was devised to achieve in situ correction of most types of HBB mutations by using validated CRISPR/sgRNA–RNP complexes and recombinant adeno-associated viral 6 (rAAV6) donor-mediated homology-directed repair (HDR) in HSCs. The gene-edited HSCs exhibited multi-lineage formation abilities, and the expression of β-globin transcripts was restored in differentiated erythroid cells. The method was applied to efficiently correct different mutations in β-thal patient-derived HSCs, and the edited HSCs retained the ability to engraft into the bone marrow of immunodeficient NOD-scid-IL2Rg−/− (NSI) mice. This study provides an efficient and safe approach for targeting HSCs by HDR at the HBB locus, which provides a potential therapeutic approach for treating other types of monogenic diseases in patient-specific HSCs