A novel facile and scalable strategy is developed to prepare freestanding carbon nanofiber/graphene nanosheet composites using a scalable membrane–liquid interface culture method followed by ...carbonization. The carbon nanofibers (CNFs) and graphene nanosheets (GNs) are uniformly dispersed in a three‐dimensional (3D) conductive architecture. Robust mechanical properties are demonstrated with fine flexibility, good structure stability, and high specific surface area. As supercapacitor electrodes, the 3D nanocomposite delivers good electrochemical performance with a high capacitance of 215 F g−1 at 1 A g−1 and extraordinary cycling stability with no capacitance degradation after 5000 cycles, which are among the best carbon electrodes in supercapacitors. The energy density is as high as 20 Wh kg−1 at a power density of 900 W kg−1, superior to other CNF‐based electrode materials. The superb electrochemical performance of the 3D nanocomposite electrode is ascribed to the unique structure: 3D conductive network, uniform dispersion of carbon nanofibers and graphene nanosheets, robust mechanical property, and large specific surface area. The combination of facile fabrication method, good performance, and robust mechanical property makes the 3D nanocomposites very promising as a new type of superior supercapacitor electrodes.
Large‐area freestanding carbon nanofiber/graphene nanosheet composite electrodes are prepared using a facile and scalable membrane–liquid interface biological culture method and demonstrate a high reversible capacity and extraordinary cycling stability with no capacitance degradation after 5000 cycles. The energy density is as high as 20 Wh kg−1 at a power density of 900 W kg−1.
In this paper, we consider the problem of direction of arrival (DOA) estimation in the presence of sensor gain-phase errors. Under some mild assumptions, we propose a new DOA estimation method based ...on the eigendecomposition of a covariance matrix which is constructed by the dot product of the array output vector and its conjugate. By combining the new DOA estimation with the conventional gain-phase error estimation, a method is proposed to simultaneously estimate the DOA and gain-phase errors without joint iteration. Theoretical analysis shows that the proposed method performs independently of phase errors and thus behaves well regardless of phase errors. However, the resolution capability of the proposed method is lower than that of the method in A. J. Weiss and B. Friedlander, "Eigenstructure methods for direction finding with sensor gain and phase uncertainties," Circuits Systems Signal Process., vol. 9, no. 3, pp. 271-300, 1990, named as the WF method. In order to improve the resolution capability and maintain phase error independence, a combined strategy is developed using the proposed and WF methods. The advantage of the proposed methods is that they are independent of phase errors, leading to the cancellation of phase error calibration during the operation life of an array. Moreover, the proposed methods avoid the problem of suboptimal convergence which occurs in the WF method. The drawbacks of the proposed methods are their high computational complexity and their requirement for the condition that at least two signals are spatially far from each other, and they are not applicable to a linear array. Simulation results verify the effectiveness of the proposed methods.
In face of the everlasting battle toward COVID-19 and the rapid evolution of SARS-CoV-2, no specific and effective drugs for treating this disease have been reported until today. ...Angiotensin-converting enzyme 2 (ACE2), a receptor of SARS-CoV-2, mediates the virus infection by binding to spike protein. Although ACE2 is expressed in the lung, kidney, and intestine, its expressing levels are rather low, especially in the lung. Considering the great infectivity of COVID-19, we speculate that SARS-CoV-2 may depend on other routes to facilitate its infection. Here, we first discover an interaction between host cell receptor CD147 and SARS-CoV-2 spike protein. The loss of CD147 or blocking CD147 in Vero E6 and BEAS-2B cell lines by anti-CD147 antibody, Meplazumab, inhibits SARS-CoV-2 amplification. Expression of human CD147 allows virus entry into non-susceptible BHK-21 cells, which can be neutralized by CD147 extracellular fragment. Viral loads are detectable in the lungs of human CD147 (hCD147) mice infected with SARS-CoV-2, but not in those of virus-infected wild type mice. Interestingly, virions are observed in lymphocytes of lung tissue from a COVID-19 patient. Human T cells with a property of ACE2 natural deficiency can be infected with SARS-CoV-2 pseudovirus in a dose-dependent manner, which is specifically inhibited by Meplazumab. Furthermore, CD147 mediates virus entering host cells by endocytosis. Together, our study reveals a novel virus entry route, CD147-spike protein, which provides an important target for developing specific and effective drug against COVID-19.
•Natural cities (NCs) were used to understand urban expansion.•TFV and TE FP were used to represent the thermal environment.•Quantifying the effect of urban expansion on thermal environment inside ...the region.•Quantifying the effect of urban expansion on thermal environment outside the region.•Factor affecting the mean TFV and TE FP of the NC was confirmed.
Urban expansion is an important factor affecting the urban thermal environment. Moreover, understanding how urban expansion affects the thermal environment, both inside and outside the region, can be effectively applied to urban planning and management. Therefore, we conducted a quantitative study on how urban expansion affects the thermal environment. We compared the changes in Natural cities (NCs) to understand urban expansion and used the thermal field value (TFV) (for assessing the thermal environment inside the region) and the thermal environment (TE FP) (for assessing the thermal environment outside the region) to represent the thermal environment. We found that urban expansion has a positive effect on the thermal environment both inside and outside NC. In addition, we confirmed that there was no correlation between the NC area and the mean TFV or the TE FP of the NC. Further, we found that in all 2020-NCs composed of a 2015-NC (O-NC) and a new expansion NC (E-NC), the mean TFV of the O-NC is higher than that of the E-NC. That is, there is a difference in the mean TFVs of the O-NC and the E-NC. Finally, we confirmed the proportion of the O-NC area as a factor affecting the mean TFV and TE FP of the NC.
With the development of artificial intelligence, the ability to capture the background characteristics of hyperspectral imagery (HSI) has improved, showing promising performance in hyperspectral ...anomaly detection (HAD) tasks. However, existing methods proposed in recent years still suffer from certain limitations: (1) Constraints are lacking in the deep feature learning process in terms of the issue of the absence of prior background and anomaly information. (2) Hyperspectral anomaly detectors with traditional self-supervised deep learning methods fail to ensure prioritized reconstruction of the background. (3) The architecture of fully connected deep networks in hyperspectral anomaly detectors leads to low utilization of spatial information and the destruction of the original spatial relationship in hyperspectral imagery and disregards the spectral correlation between adjacent pixels. (4) Hypotheses or assumptions for background and anomaly distributions restrict the performance of many hyperspectral anomaly detectors because the distributions of background land covers are usually complex and not assumable in real-world hyperspectral imagery. In consideration of the above problems, in this paper, we propose a novel fully convolutional auto-encoder based on dual clustering and latent feature adversarial consistency (FCAE-DCAC) for HAD, which is carried out with self-supervised learning-based processing. Firstly, density-based spatial clustering of applications with a noise algorithm and connected component analysis are utilized for successive spectral and spatial clustering to obtain more precise prior background and anomaly information, which facilitates the separation between background and anomaly samples during the training of our method. Subsequently, a novel fully convolutional auto-encoder (FCAE) integrated with a spatial–spectral joint attention (SSJA) mechanism is proposed to enhance the utilization of spatial information and augment feature expression. In addition, a latent feature adversarial consistency network with the ability to learn actual background distribution in hyperspectral imagery is proposed to achieve pure background reconstruction. Finally, a triplet loss is introduced to enhance the separability between background and anomaly, and the reconstruction residual serves as the anomaly detection result. We evaluate the proposed method based on seven groups of real-world hyperspectral datasets, and the experimental results confirm the effectiveness and superior performance of the proposed method versus nine state-of-the-art methods.
In China, a large amount of wind power is abandoned due to the difficulty of integrating fluctuating wind power into electricity grid systems. Advanced adiabatic compressed air energy storage ...(AA-CAES) is regarded as a promising emission-free technology to facilitate the wind power integration, but its high capital cost has hindered its wide commercialization. In the present work, a novel hybrid system was proposed on the basis of AA-CAES. It can reduce abandoned wind power and improve the financial return per capital cost of the system by increasing power output. In the new system, which is called hybrid thermal-compressed air energy storage (HTCAES), thermal energy storage (TES) units absorb the heat released from air compression and also the thermal energy converted from reluctant wind power using electrical heaters. Theoretical thermodynamic analyses show that the HTCAES system can absorb much more wind power than an AA-CAES system with the same scale of compressors, turbines, and TES units do. And recovery efficiency of this additional wind power is about 41–47%, depending on the final storage temperature of the TES. The power output ratio of the HTCAES system to the AA-CAES system increases with the maximum TES storage temperature and decreases with the operating pressure.
•A novel concept of adiabatic compressed air energy storage is proposed.•Heat TES using electricity heaters after TES absorbs heat from air.•Power storage capacity of the new system can be greatly increased.•Recovery efficiency of the wind power used for electric heating is about 41–47%.•Power output increase is about 19–125% depending on the TES storage temperature.
Two chiral carboxylic acid functionalized micro‐ and mesoporous metal–organic frameworks (MOFs) are constructed by the stepwise assembly of triple‐stranded heptametallic helicates with six carboxylic ...acid groups. The mesoporous MOF with permanent porosity functions as a host for encapsulation of an enantiopure organic amine catalyst by combining carboxylic acids and chiral amines in situ through acid–base interactions. The organocatalyst‐loaded framework is shown to be an efficient and recyclable heterogeneous catalyst for the asymmetric direct aldol reactions with significantly enhanced stereoselectivity in relative to the homogeneous organocatalyst.
Two chiral carboxylic acid functionalized micro‐ and mesoporous metal–organic frameworks (MOFs) are constructed. The mesoporous MOF functions as a host for encapsulation of an enantiopure organic amine by acid–base interactions. The organocatalyst‐loaded MOF is an efficient and recyclable heterogeneous catalyst for asymmetric direct aldol reactions, with significantly enhanced stereoselectivity relative to the homogeneous organocatalyst.
Aggregation-induced emission (AIE) nanoparticles have been widely applied in photodynamic therapy (PDT) over the past few years. However, amorphous nanoaggregates usually occur in their preparation, ...resulting in loose packing with disordered molecular structures. This still allows free intramolecular motions, thus leading to limited brightness and PDT efficiency. Herein, we report deep-red AIE nanocrystals (NCs) of DTPA-BS-F by following the facile method of nanoprecipitation. It is observed that DTPA-BS-F NCs possess not only a high photoluminescence quantum yield value of 8% in the deep-red region (600–850 nm) but also an impressive reactive oxygen species (ROS) generation efficiency of up to 69%. Moreover, DTPA-BS-F NCs targeting dual-organelles of lysosomes and nucleus to generate ROS are also achieved, thus boosting the PDT effect in cancer therapy both in vitro and in vivo. This work provides high-performance AIE NCs to simultaneously target two organelles for efficient photodynamic therapy, indicating their promising application in all-in-one theranostic platforms.
Alzheimer's disease and Type 2 diabetes are two epidemiologically linked diseases which are closely associated with the misfolding and aggregation of amyloid proteins amyloid-β (Aβ) and human islet ...amyloid polypeptide (hIAPP), respectively. The co-aggregation of the two amyloid proteins is regarded as the fundamental molecular mechanism underlying their pathological association. The green tea extract epigallocatechin-3-gallate (EGCG) has been extensively demonstrated to inhibit the amyloid aggregation of Aβ and hIAPP proteins. However, its potential role in amyloid co-aggregation has not been thoroughly investigated. In this study, we employed the enhanced-sampling replica exchange molecular dynamics simulation (REMD) method to investigate the effect of EGCG on the co-aggregation of Aβ and hIAPP. We found that EGCG molecules substantially diminish the β-sheet structures within the amyloid core regions of Aβ and hIAPP in their co-aggregates. Through hydrogen-bond, π-π and cation-π interactions targeting polar and aromatic residues of Aβ and hIAPP, EGCG effectively attenuates both inter-chain and intra-chain interactions within the co-aggregates. All these findings indicated that EGCG can effectively inhibit the co-aggregation of Aβ and hIAPP. Our study expands the potential applications of EGCG as an anti-amyloidosis agent and provides therapeutic options for the pathological association of amyloid misfolding disorders.
In synthetic aperture radar (SAR) imaging of a ground moving target, long-time coherent integration may effectively improve the imaging quality, whereas the imaging performance may severely degrade ...due to the range migration and the Doppler frequency migration. In this paper, a novel motion parameter estimation method named second-order Wigner-Ville distribution (SoWVD) transform is proposed, and then, a new SAR imaging method based on the SoWVD for a ground moving target is developed. As a modified Wigner-Ville distribution method, the SoWVD method can estimate the motion parameter without the search procedure, which achieves motion parameter estimation by Fourier transform operations in the 2-D frequency plane with respect to the slow time and the delay time. In addition, it can effectively recognize the cross terms based on multiple symmetrical properties of the peaks in the 2-D frequency domain. Both simulated and real data processing results are presented to validate the proposed imaging method.
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