Since December 2019, an epidemic caused by novel coronavirus (2019-nCoV) infection has occurred unexpectedly in China. As of 8 pm, 31 January 2020, more than 20 pediatric cases have been reported in ...China. Of these cases, ten patients were identified in Zhejiang Province, with an age of onset ranging from 112 days to 17 years. Following the latest
National recommendations for diagnosis and treatment of pneumonia caused by 2019-nCoV
(the 4th edition) and current status of clinical practice in Zhejiang Province, recommendations for the diagnosis and treatment of respiratory infection caused by 2019-nCoV for children were drafted by the National Clinical Research Center for Child Health, the National Children’s Regional Medical Center, Children’s Hospital, Zhejiang University School of Medicine to further standardize the protocol for diagnosis and treatment of respiratory infection in children caused by 2019-nCoV.
Silicon has been developed as the exceptionally desirable anode candidate for lithium-ion batteries (LIBs), attributing to its highest theoretical capacity, low working potential, and abundant ...resource. However, large volume expansion and poor conductivity hinder its practical application. Herein, we fabricate flexible, freestanding, and binder-free silicon/MXene composite papers directly as anodes for LIBs. The Silicon/MXene composite papers are synthesized via covalently anchoring silicon nanospheres on the highly conductive networks based on MXene sheets by vacuum filtration. This unique architecture can accommodate large volume expansion, enhance conductivity of composites, prevent restacking of MXene sheets, offer additional active sites, and facilitate efficient ion transport, which exhibits superior electrochemical performance with a high capacity of 2118 mAh·g–1 at 200 mA·g–1 current density after 100 cycles, a steady cycling ability of 1672 mAh·g–1 at 1000 mA·g–1 after 200 cycles, and a rate performance of 890 mAh·g–1 at 5000 mA·g–1. This work may shed lights on the development of silicon-based anodes for LIBs.
•Mass loss increased with increase of coal particle size during pyrolysis in TGA.•Effect of coal particle size and heating rate on the characteristic parameters of coal pyrolysis was ...distinguished.•Tin, Tmax and Tf displayed the logistic distribution along with heating rate up to 1000K/min.•The yields of all the gas species at maximum releasing rate enhanced with increasing the heating rate.•A mechanism corresponding to metaplast forming was proposed to explain the experimental results reasonably.
In this work, thermal behavior of five different coal particle fractions were investigated using thermogravimetric analyzer (TGA) under various heating rates with the maximum of 1000K/min. An on–line Fourier Transform Infrared Spectrometry (FTIR) was employed to evaluate the evolution characteristics of the gaseous products. The results showed that the coal particle size remarkably affected the mass loss and the ash amount. The larger the particle size was, the higher mass loss and the more ash could be, which revealed its high pyrolysis reactivity. In addition, with increasing the particle size, the initial devolatilization temperature (Tin) and devolatilization index (Di) increased, whereas, the final devolatilization temperature (Tf) decreased. This phenomenon was explained by a proposed mechanism of the obstacle escaping of volatiles from the interparticles corresponding to forming large block unit of metaplast. The heating rate has significant effect on the performance of devolatilization profiles and gaseous products releasing. Tin, Tmax and Tf displayed the logistic distribution along with heating rate up to 1000K/min, whereas, Rmax and the heating rate were highly linear correlated with different particle fractions. The enhanced yield at maximum releasing rate for all the gas species were observed with increasing the heating rate. Moreover, the peak of maximum releasing rate on the evolving profiles of gaseous products became narrower and sharper, and releasing time of the gaseous products reduced extremely with increasing the heating rate. These findings can provide fundamental data for practical applications, plant designing, handling, and modeling of integrated coal fluidized bed gasification system as well as other coal fluidized bed pyrolysis/gasification process.
This paper examines and compares two policies (investment cost subsidy and tax rate reduction) for the host government to attract FDI. Taking into consideration the firm's indifferent FDI option ...value between the two policies, the government trades off the immediate and certain lump-sum cost of the subsidy against the future random flow of tax rate reduction. We demonstrate that the optimal policy for attracting FDI depends on the growth rate and the volatility of the profit as well as the discount rate. There exists a critical level in each of the three parameters. The tax rate reduction (or investment cost subsidy) is preferable when the growth rate and the volatility of the profit is higher (or lower), and when the discount rate is lower (or higher). These results are consistent with the empirical findings, which found that governments are more likely to adopt tax rate reduction for firms with high risk and high return.
We have developed a nickel‐catalyzed desymmetric reductive cyclization/coupling of 1,6‐dienes. The reaction provides an efficient method for constructing a chiral tertiary alcohol and a quaternary ...stereocenter by a single operation. The method has excellent diastereoselectivity and high enantioselectivity, a broad substrate scope, as well as good tolerance of functional groups. Preliminary mechanism studies show that alkyl nickel(I) species are involved in the reaction.
A nickel‐catalyzed desymmetric reductive cyclization/coupling reaction of 1,6‐dienes and alkyl bromides is reported. A chiral tertiary alcohol and a quaternary stereocenter are constructed by a single operation with excellent diastereoselectivity and high enantioselectivity.
Convolutional neural networks (CNNs) have been widely used in image classification and recognition due to their effectiveness; however, CNNs use a large volume of weight data that is difficult to ...store in on-chip memory of embedded designs. Pruning can compress the CNN model at a small accuracy loss; however, a pruned CNN model operates slower when implemented on a parallel architecture. In this paper, a hardware-oriented CNN compression strategy is proposed; a deep neural network (DNN) model is divided into "no-pruning layers (<inline-formula> <tex-math notation="LaTeX">NP </tex-math></inline-formula>-layers)" and "pruning layers (<inline-formula> <tex-math notation="LaTeX">P </tex-math></inline-formula>-layers)". A <inline-formula> <tex-math notation="LaTeX">NP </tex-math></inline-formula>-layer has a regular weights distribution for parallel computing and high performance. A <inline-formula> <tex-math notation="LaTeX">P </tex-math></inline-formula>-layer is irregular due to pruning, but it generates a high compression ratio. Uniform and incremental quantization schemes are used to achieve a tradeoff between compression ratio and processing efficiency at a small loss in accuracy. A distributed convolutional architecture with several parallel finite impulse response (FIR) filters is further proposed for the regular model in the <inline-formula> <tex-math notation="LaTeX">NP </tex-math></inline-formula>-layers. A shift-accumulator based processing element with an activation-driven data flow (ADF) is proposed for the irregular sparse model in the <inline-formula> <tex-math notation="LaTeX">P </tex-math></inline-formula>-layers. Based on the proposed compression strategy and hardware architecture, a hardware/algorithm co-optimization (HACO) approach is proposed for implementing a <inline-formula> <tex-math notation="LaTeX">NP-P </tex-math></inline-formula> hybrid compressed CNN model on FPGAs. For a hardware accelerator on a single FPGA chip without the use of off-chip memory, a <inline-formula> <tex-math notation="LaTeX">27.5\times </tex-math></inline-formula> compression ratio is achieved with 0.44% top-5 accuracy loss for VGG-16. The implementation of the compressed VGG-16 model on a Xilinx VCU118 evaluation board processes 83.0 frames per second (FPS) for image applications, this is <inline-formula> <tex-math notation="LaTeX">1.8\times </tex-math></inline-formula> superior than the state-of-the-art design found in the technical literature.
Topological insulators with unique edge states have revolutionized the understanding of solid-state materials. Recently, higher-order topological insulators (HOTIs), which host both gapped edge ...states and in-gap corner/hinge states, protected concurrently by band topology, were predicted and observed in experiments, unveiling a new horizon beyond the conventional bulk-edge correspondence. However, the control and manifestation of band topology in a hierarchy of dimensions, which is at the heart of HOTIs, have not yet been witnessed. Here, we propose theoretically and observe experimentally that tunable two-dimensional sonic crystals can be versatile systems to visualize and harness higher-order topology. In our systems, the two-dimensional acoustic bands mimic the quantum spin Hall effect, while the resultant one-dimensional helical edge states are gapped due to broken space-symmetry and carry quantized Zak phases, which then lead to zero-dimensional topological corner states. We demonstrate that topological transitions in the bulk and edges can be triggered independently by tuning the geometry of the sonic crystals. With complementary experiments and theories, our study reveals rich physics in HOTIs, opening a new route towards tunable topological metamaterials where novel applications, such as the topological transfer of acoustic energy among two-, one- and zero-dimensional modes, can be achieved.By tuning the geometry of a two-dimensional sonic crystal, its one-dimensional helical edge states become gapped and zero-dimensional topological corner states emerge. The band topology is thus manifested in a hierarchy of dimensions.
A new kind of nitrogen‐doped graphene/carbon nanotube nanocomposite can be synthesized by a facile hydrothermal process under mild conditions, which exhibits synergistically enhanced electrochemical ...activity for the oxygen reduction reaction. This research provides a new route to access a metal‐free electrocatalyst with high activity under mild conditions.
Music emotion representation learning forms the foundation of user emotion recognition, addressing the challenges posed by the vast volume of digital music data and the scarcity of emotion annotation ...data. This article introduces a novel music emotion representation model, leveraging the nonnegative matrix factorization algorithm (NMF) to derive emotional embeddings of music by utilizing user-generated listening lists and emotional labels. This approach facilitates emotion recognition by positioning music within the emotional space. Furthermore, a dedicated music emotion recognition algorithm is formulated, alongside the proposal of a user emotion recognition model, which employs similarity-weighted calculations to obtain user emotion representations. Experimental findings demonstrate the method’s convergence after a mere 400 iterations, yielding a remarkable 47.62% increase in F1 value across all emotion classes. In practical testing scenarios, the comprehensive accuracy rate of user emotion recognition attains an impressive 52.7%, effectively discerning emotions within seven emotion categories and accurately identifying users’ emotional states.
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