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61.
Yan  Jing  Zhu  Rongying  Wu  Fan  Zhao  Ziyin  Ye  Huan  Hou  Mengying  Liu  Yong  Yin  Lichen 《Nano Research》2020,13(10):2706-2715
Nano Research - Insufficient intratumoral penetration greatly hurdles the anticancer performance of nanomedicine. To realize highly efficient tumor penetration in a precisely and spatiotemporally...  相似文献   
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Chi  Yaxiong  Liu  Jing 《Natural computing》2019,18(2):301-312

Reconstructing gene regulatory networks (GRNs) plays an important role in identifying the complicated regulatory relationships, uncovering regulatory patterns in cells, and gaining a systematic view for biological processes. In order to reconstruct large-scale GRNs accurately, in this paper, we first use fuzzy cognitive maps (FCMs), which are a kind of cognition fuzzy influence graphs based on fuzzy logic and neural networks, to model GRNs. Then, a novel hybrid method is proposed to reconstruct GRNs from time series expression profiles using memetic algorithm (MA) combined with neural network (NN), which is labeled as MANNFCM-GRN. In MANNFCM-GRN, the MA is used to determine regulatory connections in GRNs and the NN is used to determine the interaction strength of the regulatory connections. In the experiments, the performance of MANNFCM-GRN is validated on both synthetic data and the benchmark dataset DREAM3 and DREAM4. The experimental results demonstrate the efficacy of MANNFCM-GRN and show that MANNFCM-GRN can reconstruct GRNs with high accuracy without expert knowledge. The comparison with existing algorithms also shows that MANNFCM-GRN outperforms ant colony optimization, non-linear Hebbian learning, and real-coded genetic algorithms.

  相似文献   
63.
Chen  Meng  Yu  Xiaohui  Liu  Yang 《World Wide Web》2019,22(6):2901-2920
World Wide Web - The wide spread use of positioning and photographing devices gives rise to a deluge of traffic trajectory data (e.g., vehicle passage records and taxi trajectory data), with each...  相似文献   
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The crystallization of capped ultrathin polymer films is closely dependent on film thickness and interfacial interaction. Using dynamic Monte Carlo simulations, the crystallization behaviors of polymer films confined between two substrates were investigated. The crystallization rate of confined polymers is reduced with high interfacial interactions. Above a critical strength of interfacial interaction, polymer crystallization in the thin film is inhibited within the simulation time scales. An increase in film thickness leads to a rise in critical interfacial interaction. In thicker films, the chains have more space to change conformation to form crystal stems. In addition, there are fewer absorbed segments in confined chains for the thicker films, and thus the chains have stronger ability to adjust their conformation. Therefore an increase in film thickness can cause a reduction in the entropic barrier required for the formation of crystals and thus an increase in the critical interfacial interaction. © 2018 Society of Chemical Industry  相似文献   
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Semiconductor particles doped Al2O3 coatings were prepared by cathode plasma electrolytic deposition in Al(NO3)3 electrolyte dispersed with SiC micro- and nano-particles (average particle sizes of 0.5–1.7?µm and 40?nm respectively). The effects of the concentrations and particle sizes of the SiC on the microstructures and tribological performances of the composite coatings were studied. In comparison with the case of dispersing with SiC microparticles, the dispersion of SiC nanoparticles in the coatings was more uniform. When the concentration of SiC nanoparticles was 5?g/L, the surface roughness of the composite coating was reduced by 63%, compared with that of the unmodified coating. Friction results demonstrated that the addition of 5?g/L SiC nanoparticles reduced the friction coefficient from 0.60 to 0.38 and decreased the wear volume under dry friction. The current density and bath voltage were measured to analyze the effects of SiC particles on the deposition process. The results showed that the SiC particles could alter the electrical behavior of the coatings during the deposition process, weaken the bombardment of the plasma, and improve the structures of the coatings.  相似文献   
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Engineering novel Sn-based bimetallic materials could provide intriguing catalytic properties to boost the electrochemical CO2 reduction. Herein, the first synthesis of homogeneous Sn1−xBix alloy nanoparticles (x up to 0.20) with native Bi-doped amorphous SnOx shells for efficient CO2 reduction is reported. The Bi-SnOx nanoshells boost the production of formate with high Faradaic efficiencies (>90%) over a wide potential window (−0.67 to −0.92 V vs RHE) with low overpotentials, outperforming current tin oxide catalysts. The state-of-the-art Bi-SnOx nanoshells derived from Sn0.80Bi0.20 alloy nanoparticles exhibit a great partial current density of 74.6 mA cm−2 and high Faradaic efficiency of 95.8%. The detailed electrocatalytic analyses and corresponding density functional theory calculations simultaneously reveal that the incorporation of Bi atoms into Sn species facilitates formate production by suppressing the formation of H2 and CO.  相似文献   
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Large‐scale production of hydrogen from water‐alkali electrolyzers is impeded by the sluggish kinetics of hydrogen evolution reaction (HER) electrocatalysts. The hybridization of an acid‐active HER catalyst with a cocatalyst at the nanoscale helps boost HER kinetics in alkaline media. Here, it is demonstrated that 1T–MoS2 nanosheet edges (instead of basal planes) decorated by metal hydroxides form highly active edge 1T‐MoS 2 / edge Ni ( OH ) 2 heterostructures, which significantly enhance HER performance in alkaline media. Featured with rich edge 1T‐MoS 2 / edge Ni ( OH ) 2 sites, the fabricated 1T–MoS2 QS/Ni(OH)2 hybrid (quantum sized 1T–MoS2 sheets decorated with Ni(OH)2 via interface engineering) only requires overpotentials of 57 and 112 mV to drive HER current densities of 10 and 100 mA cm?2, respectively, and has a low Tafel slope of 30 mV dec?1 in 1 m KOH. So far, this is the best performance for MoS2‐based electrocatalysts and the 1T–MoS2 QS/Ni(OH)2 hybrid is among the best‐performing non‐Pt alkaline HER electrocatalysts known. The HER process is durable for 100 h at current densities up to 500 mA cm?2. This work not only provides an active, cost‐effective, and robust alkaline HER electrocatalyst, but also demonstrates a design strategy for preparing high‐performance catalysts based on edge‐rich 2D quantum sheets for other catalytic reactions.  相似文献   
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