Coronavirus disease 2019 is a newly emerging infectious disease currently spreading across the world. It is caused by a novel coronavirus, severe acute respiratory syndrome coronavirus 2 ...(SARS-CoV-2). The spike (S) protein of SARS-CoV-2, which plays a key role in the receptor recognition and cell membrane fusion process, is composed of two subunits, S1 and S2. The S1 subunit contains a receptor-binding domain that recognizes and binds to the host receptor angiotensin-converting enzyme 2, while the S2 subunit mediates viral cell membrane fusion by forming a six-helical bundle via the two-heptad repeat domain. In this review, we highlight recent research advance in the structure, function and development of antivirus drugs targeting the S protein.
Polypyrrole (PPy) is a promising pseudocapacitive material for supercapacitor electrodes. However, its poor cycling stability is the major hurdle for its practical applications. Here a two‐prong ...strategy is demonstrated to stabilize PPy film by growing it on a functionalized partial‐exfoliated graphite (FEG) substrate and doping it with β‐naphthalene sulfonate anions (NS−). The PPy electrode achieves a remarkable capacitance retention rate of 97.5% after cycling between −0.8 and 0 V versus saturated calomel electrode for 10 000 cycles. Moreover, an asymmetric pseudocapacitor using the stabilized PPy film as anode also retains 97% of capacitance after 10 000 cycles, which is the best value reported for PPy‐based supercapacitors. The exceptional stability of PPy electrode can be attributed to two factors: 1) the flexible nature of FEG substrate accommodates large volumetric deformation and 2) the presence of immobile NS− dopants suppresses the counterion drain effect during charge–discharge cycling.
By a doping polypyrrole film supported on functionalized partial‐exfoliated graphite (FEG) substrate with β‐naphthalene sulfonate anions, the polypyrrole electrode achieves a remarkable capacitance retention rate of 97.5% after cycling between −0.8 and 0 V versus saturated calomel electrode for 10 000 cycles. An asymmetric pseudocapacitor using the stabilized PPy film as anode can also retain 97% of capacitance after 10 000 cycles.
This paper proposes adaptive iterative learning control (ILC) schemes for continuous-time parametric nonlinear systems with iteration lengths that randomly vary. As opposed to the existing ILC works ...that feature nonuniform trial lengths, this paper is applicable to nonlinear systems that do not satisfy the globally Lipschitz continuous condition. In addition, this paper introduces a novel composite energy function based on newly defined virtual tracking error information for proving the asymptotical convergence. Both an original update algorithm and a projection-based update algorithm for estimating the unknown parameters are proposed. Extensions to cases with unknown input gains, iteration-varying tracking references, nonparametric uncertainty, high-order nonlinear systems, and multi-input-multi-output systems are all elaborated upon. Illustrative simulations are provided to verify the theoretical results.
Economic dispatch problem (EDP) is an important class of optimization problems in the smart grid, which aims at minimizing the total cost when generating certain amount of power. In this work, a ...novel consensus based algorithm is proposed to solve EDP in a distributed fashion. The quadratic convex cost functions are assumed in the problem formulation, and the strongly connected communication topology is sufficient for the information exchange. Unlike centralized approaches, the proposed algorithm enables generators to collectively learn the mismatch between demand and total amount of power generation. The estimated mismatch is then used as a feedback mechanism to adjust current power generation by each generator. With a tactical initial setup, eventually, all generators can automatically minimize the total cost in a collective sense.
In this paper, we consider a flux-limited Keller–Segel model derived in
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,
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in a one-dimensional bounded domain and give a refined asymptotic result of the spiky steady state by using the Sturm ...oscillation theorem in a more meticulous way based on the existence result of spiky steady state in
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, showing a more accurate characterization of the cell aggregation phenomenon.
Abstract
In order to systematically study and verify the digital manufacturing archit ecture and its key technologies, to solve the problems that enterprises currently face in the process of ...transformation and upgrading of digital and network manufacturing, a lithium battery pilot production line was selected as the research object, using the virtual reality technology as the underlying foundation, integratedly tested and verified the technology contents of the production line including the virtual simulation technology, manufacturing execution construction, information acquisition, and equipment automated transformation required for the construction of a digital factory, tested and verified the inter-drive and mutual control of the pilot line digital twin with its physical entity. The results show that virtual reality technology can provide a virtual testing platform for digital manufacturing which improves the efficiency of automation transformation, digital production and network operation of the actual production lines. This can provide a useful reference for enterprises to achieve a higher degree of digital manufacturing and maintenance in the future.
In recent years, micrometer‐sized Si‐based anode materials have attracted intensive attention in the pursuit of energy‐storage systems with high energy and low cost. However, the significant volume ...variation during repeated electrochemical (de)alloying processes will seriously damage the bulk structure of SiOx microparticles, resulting in rapid performance fade. This work proposes to address the challenge by preparing in situ magnesium‐doped SiOx (SiMgyOx) microparticles with stable structural evolution against Li uptake/release. The homogeneous distribution of magnesium silicate in SiMgyOx contributes to building a bonding network inside the particle so that it raises the modulus of lithiated state and restrains the internal cracks due to electrochemical agglomeration of nano‐Si. The prepared micrometer‐sized SiMgyOx anode shows high reversible capacities, stable cycling performance, and low electrode expansion at high areal mass loading. A 21700 cylindrical‐type cell based on the SiMgyOx‐graphite anode and LiNi0.8Co0.15Al0.05O2 cathode demonstrates a 1000‐cycle operation life using industry‐recognized electrochemical test procedures, which meets the practical storage requirements for consumer electronics and electric vehicles. This work provides insights on the reasonable structural design of micrometer‐sized alloying anode materials toward realization of high‐performance Li‐ion batteries.
The in situ element doping approach developed in this research provides not only a promising material (SiMgyOx) as high‐performance Li‐ion battery anodes with superior properties and low industrialization cost for commercial applications, but also insights on the reasonable structural design of micrometer‐sized alloying anode materials for restraining internal cracks and improving electrochemical performance.
An effective method to control the rate of perovskite crystallization by incorporating rationally chosen additives into the perovskite precursor solutions is demonstrated. The processing additives ...simultaneously facilitate nucleation and modulate the kinetics of crystal growth during crystallization, leading to much smoother perovskite morphology with improved coverage area and crystal uniformity. As a result, it enables very high PCE (∼12%) planar‐heterojunction solar cells to be fabricated through the low‐temperature solution processes (under 150 °C). This study opens up a new direction for optimizing perovskite active layer properties to expand device performance ceilings.
Supervised cross-modal hashing has attracted much attention. However, there are still some challenges, e.g., how to effectively embed the label information into binary codes, how to avoid using a ...large similarity matrix and make a model scalable to large-scale datasets, how to efficiently solve the binary optimization problem. To address these challenges, in this paper, we present a novel supervised cross-modal hashing method, i.e., scalaBle Asymmetric discreTe Cross-modal Hashing, BATCH for short. It leverages collective matrix factorization to learn a common latent space for the labels and different modalities, and embeds the labels into binary codes by minimizing a distance-distance difference problem. Furthermore, it builds a connection between the common latent space and the hash codes by an asymmetric strategy. In the light of this, it can perform cross-modal retrieval and embed more similarity information into the binary codes. In addition, it introduces a quantization minimization term and orthogonal constraints into the optimization problem, and generates the binary codes discretely. Therefore, the quantization error and redundancy may be much reduced. Moreover, it is a two-step method, making the optimization simple and scalable to large-scale datasets. Extensive experimental results on three benchmark datasets demonstrate that BATCH outperforms some state-of-the-art cross-modal hashing methods in terms of accuracy and efficiency.
Convergence performance and parametric sensitivity are two issues that tend to be neglected when extending differential evolution (DE) to multiobjective optimization (MO). To fill this research gap, ...we develop two novel mutation operators and a new parameter adaptation mechanism. A multiobjective DE variant is obtained through integration of the proposed strategies. The main innovation of this paper is the simultaneous use of individuals across generations from an objective-based perspective. Good convergence-diversity tradeoff and satisfactory exploration-exploitation balance are achieved via the hybrid cross-generation mutation operation. Furthermore, the cross-generation adaptation mechanism enables the individuals to self-adapt their associated parameters not only optimization stage-wise but also objective-space-wise. Empirical results indicate the statistical superiority of the proposed algorithm over several state-of-the-art evolutionary algorithms in handling MO problems.
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