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"Hu, Bin"
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Development of China's financial supervision and regulation
China's financial regulatory system is crucial to the global economy, but is little understood. This book surveys and explicates the current status, the development, and planned reform of the Chinese financial supervision and regulatory system in a systematic way. From the shadow banking system to commercial banking, securities and the foreign exchange regime, the authors shed light on the different moving parts of the system; meanwhile, they show how reforms have changed the system in recent years, whether in free-trade zones, the Shanghai-Hong Kong stock market connection, or in the registration mechanisms required for new IPOs. The editors and authors are from the Chinese Academy of Social Sciences, the China Banking Regulatory Committee, the China Securities Regulatory Committee and other leading academic and policy organizations.
Book
A facile synthesis of bismuth oxychloride-graphene oxide composite for visible light photocatalysis of aqueous diclofenac sodium
In this study, bismuth oxychloride/graphene oxide (BiOCl-GO) composite was fabricated by facile one pot hydrothermal method. The pure BiOCl and BiOCl-GO composite was characterized by X-ray diffraction, Transmission electron microscopy X-ray photoelectron spectroscopy and UV–Vis diffuse reflectance spectroscopy. The synthesized composite was then assessed for photocatalytic degradation of diclofenac sodium (DCF) in visible as well as direct solar light and UV irradiation. Results indicated that the photocatalytic removal efficiency of DCF was significantly affected by dose of catalysts, pH value and source of light. The results reveled that degradation efficiency of BiOCl-GO for DCF reduced from 100 to 34.4% with the increases in DCF initial concentration from 5 mg L
−1
to 25 mg L
−1
. The solar light degradation of DCF using BiOCl-GO was achieved with apparent rate constant 0.0037 min
−1
. The effect of scavengers study revealed that superoxide ions and holes were mainly responsible for DCF degradation. The regeneration study indicates that BiOCl-GO composite can be successfully recycled up to the five cycles. The study revealed the effectiveness of one pot hydrothermal method for the fabrication of BiOCl-GO composite.
Journal Article
A Framework for Agricultural Pest and Disease Monitoring Based on Internet-of-Things and Unmanned Aerial Vehicles
With the development of information technology, Internet-of-Things (IoT) and low-altitude remote-sensing technology represented by Unmanned Aerial Vehicles (UAVs) are widely used in environmental monitoring fields. In agricultural modernization, IoT and UAV can monitor the incidence of crop diseases and pests from the ground micro and air macro perspectives, respectively. IoT technology can collect real-time weather parameters of the crop growth by means of numerous inexpensive sensor nodes. While depending on spectral camera technology, UAVs can capture the images of farmland, and these images can be utilize for analyzing the occurrence of pests and diseases of crops. In this work, we attempt to design an agriculture framework for providing profound insights into the specific relationship between the occurrence of pests/diseases and weather parameters. Firstly, considering that most farms are usually located in remote areas and far away from infrastructure, making it hard to deploy agricultural IoT devices due to limited energy supplement, a sun tracker device is designed to adjust the angle automatically between the solar panel and the sunlight for improving the energy-harvesting rate. Secondly, for resolving the problem of short flight time of UAV, a flight mode is introduced to ensure the maximum utilization of wind force and prolong the fight time. Thirdly, the images captured by UAV are transmitted to the cloud data center for analyzing the degree of damage of pests and diseases based on spectrum analysis technology. Finally, the agriculture framework is deployed in the Yangtze River Zone of China and the results demonstrate that wheat is susceptible to disease when the temperature is between 14 °C and 16 °C, and high rainfall decreases the spread of wheat powdery mildew.
Journal Article
N6-methyladenosine (m6A) RNA modification in gastrointestinal tract cancers: roles, mechanisms, and applications
Analogous to DNA methylation and histone modification, RNA modification, as another epigenetic layer, plays an important role in many diseases, especially in tumours. As the most common form of RNA modification, m
6
A methylation has attracted increasing research interest in recent years. m
6
A is catalysed by RNA methyltransferases METTL3, METTL14 and WTAP (writers), m
6
A is removed by the demethylases FTO and ALKBH5 (erasers) and interacts with m6A-binding proteins, such as YT521-B homology (YTH) domain-containing proteins. This article reviews recent studies on methylation modification of m
6
A in gastrointestinal tract cancers.
Journal Article
Spin-sate reconfiguration induced by alternating magnetic field for efficient oxygen evolution reaction
Oxygen evolution reaction (OER) plays a determining role in electrochemical energy conversion devices, but challenges remain due to the lack of effective low-cost electrocatalysts and insufficient understanding about sluggish reaction kinetics. Distinguish from complex nano-structuring, this work focuses on the spin-related charge transfer and orbital interaction between catalysts and intermediates to accelerate catalytic reaction kinetics. Herein, we propose a simple magnetic-stimulation approach to rearrange spin electron occupation in noble-metal-free metal-organic frameworks (MOFs) with a feature of thermal-differentiated superlattice, in which the localized magnetic heating in periodic spatial distribution makes the spin flip occur at particular active sites, demonstrating a spin-dependent reaction pathway. As a result, the spin-rearranged Co
Mn
MOF displays mass activities of 3514.7 A g
with an overpotential of ~0.27 V, which is 21.1 times that of pristine MOF. Our findings provide a new paradigm for designing spin electrocatalysis and steering reaction kinetics.
Journal Article
Genome-wide screening of NEAT1 regulators reveals cross-regulation between paraspeckles and mitochondria
The long noncoding RNA
NEAT1
(nuclear enriched abundant transcript 1) nucleates the formation of paraspeckles, which constitute a type of nuclear body with multiple roles in gene expression. Here we identify
NEAT1
regulators using an endogenous
NEAT1
promoter-driven enhanced green fluorescent protein reporter in human cells coupled with genome-wide RNAi screens. The screens unexpectedly yield gene candidates involved in mitochondrial functions as essential regulators of
NEAT1
expression and paraspeckle formation. Depletion of mitochondrial proteins and treatment of mitochondrial stressors both lead to aberrant
NEAT1
expression via ATF2 as well as altered morphology and numbers of paraspeckles. These changes result in enhanced retention of mRNAs of nuclear-encoded mitochondrial proteins (mito-mRNAs) in paraspeckles. Correspondingly,
NEAT1
depletion has profound effects on mitochondrial dynamics and function by altering the sequestration of mito-mRNAs in paraspeckles. Overall, our data provide a rich resource for understanding
NEAT1
and paraspeckle regulation, and reveal a cross-regulation between paraspeckles and mitochondria.
Wang et al. show that mitochondrial stress alters paraspeckle number and morphology through regulating the transcription and processing of lncRNA
NEAT1
, retaining mRNAs of mitochondrial proteins in paraspeckles.
Journal Article
Deep Learning Image Feature Recognition Algorithm for Judgment on the Rationality of Landscape Planning and Design
This paper uses an improved deep learning algorithm to judge the rationality of the design of landscape image feature recognition. The preprocessing of the image is proposed to enhance the data. The deficiencies in landscape feature extraction are further addressed based on the new model. Then, the two-stage training method of the model is used to solve the problems of long training time and convergence difficulties in deep learning. Innovative methods for zoning and segmentation training of landscape pattern features are proposed, which makes model training faster and generates more creative landscape patterns. Because of the impact of too many types of landscape elements in landscape images, traditional convolutional neural networks can no longer effectively solve this problem. On this basis, a fully convolutional neural network model is designed to perform semantic segmentation of landscape elements in landscape images. Through the method of deconvolution, the pixel-level semantic segmentation is realized. Compared with the 65% accuracy rate of the convolutional neural network, the fully convolutional neural network has an accuracy rate of 90.3% for the recognition of landscape elements. The method is effective, accurate, and intelligent for the classification of landscape element design, which better improves the accuracy of classification, greatly reduces the cost of landscape element design classification, and ensures that the technical method is feasible. This paper classifies landscape behavior based on this model for full convolutional neural network landscape images and demonstrates the effectiveness of using the model. In terms of landscape image processing, the image evaluation provides a certain basis.
Journal Article
Traffic Experiment Reveals the Nature of Car-Following
As a typical self-driven many-particle system far from equilibrium, traffic flow exhibits diverse fascinating non-equilibrium phenomena, most of which are closely related to traffic flow stability and specifically the growth/dissipation pattern of disturbances. However, the traffic theories have been controversial due to a lack of precise traffic data. We have studied traffic flow from a new perspective by carrying out large-scale car-following experiment on an open road section, which overcomes the intrinsic deficiency of empirical observations. The experiment has shown clearly the nature of car-following, which runs against the traditional traffic flow theory. Simulations show that by removing the fundamental notion in the traditional car-following models and allowing the traffic state to span a two-dimensional region in velocity-spacing plane, the growth pattern of disturbances has changed qualitatively and becomes qualitatively or even quantitatively in consistent with that observed in the experiment.
Journal Article
What Is the Optimal Value of the g-Ratio for Myelinated Fibers in the Rat CNS? A Theoretical Approach
The biological process underlying axonal myelination is complex and often prone to injury and disease. The ratio of the inner axonal diameter to the total outer diameter or g-ratio is widely utilized as a functional and structural index of optimal axonal myelination. Based on the speed of fiber conduction, Rushton was the first to derive a theoretical estimate of the optimal g-ratio of 0.6 [1]. This theoretical limit nicely explains the experimental data for myelinated axons obtained for some peripheral fibers but appears significantly lower than that found for CNS fibers. This is, however, hardly surprising given that in the CNS, axonal myelination must achieve multiple goals including reducing conduction delays, promoting conduction fidelity, lowering energy costs, and saving space.
In this study we explore the notion that a balanced set-point can be achieved at a functional level as the micro-structure of individual axons becomes optimized, particularly for the central system where axons tend to be smaller and their myelin sheath thinner. We used an intuitive yet novel theoretical approach based on the fundamental biophysical properties describing axonal structure and function to show that an optimal g-ratio can be defined for the central nervous system (approximately 0.77). Furthermore, by reducing the influence of volume constraints on structural design by about 40%, this approach can also predict the g-ratio observed in some peripheral fibers (approximately 0.6).
These results support the notion of optimization theory in nervous system design and construction and may also help explain why the central and peripheral systems have evolved different g-ratios as a result of volume constraints.
Journal Article