基于ERNIE-BiGRU模型的摘要语步自动识别研究

学术文献的摘要是对文献主要内容的浓缩,摘要不同部分的语步具有不同的信息,语步的自动识别和抽取对于学术摘要的后续研究有着重要的应用价值,而目前语步识别的研究相对较少,并且相关算法的效果还需要提高。针对上述问题,该文提出了一种基于ERNIE-BiGRU模型的语步识别算法。该算法首先结合中文句法分析理论提出基于句法依存关系的多语步结构拆分法,对学术文献摘要多语步结构进行自动拆分,获得多个单语步结构;然后构建用于训练的单语步结构语料库,并利用知识增强语义表示预训练模型,训练出句子级词向量;最后将训练出的单语步结构词向量信息输入双向门限循环单元(BiGRU)进行摘要语步自动化识别,取得了良好的效果。实验结果表明,该算法具有较好的鲁棒性和较高的识别精度,在结构化和非结构化摘要上的识别准确率分别达到了96.57%和93.75%。     

Effects of multiple freeze–thaw cycles on meat quality,nutrients, water distribution and microstructure in bovine rumen smooth muscle

This study investigated the effect of 5 freeze–thaw cycles (freezing at −18°C for 12 h and then thawing at 4°C for approximately 12 h) on the meat quality, proximate composition, water distribution and microstructure of bovine rumen smooth muscle (BSM). As the number of freeze–thaw cycles increased, BSM pH, shear force, water content and protein content decreased by 3.06%, 35.50%, 14.49% and 21.11%, respectively, whereas BSM thawing loss, cooking loss, pressing loss, total aerobic count (TAC), ash content and fat content increased by 108.12%, 47.75%, 78.33%, 90.99%, 105% and 35.20%, respectively. The freeze–thaw cycles resulted in greater protein and lipid oxidation, as evidenced by a 36.46% reduction in the sulfhydryl content and a 209.06% and 338.46% increase in the carbonyl and malondialdehyde contents, respectively. Ice crystal formation disrupted the structural integrity of the muscle tissue. Low-field nuclear magnetic resonance results showed that the freeze–thaw cycles prolonged the relaxation times (T_2b, T₂₁ and T₂₂), indicating that immobile water shifted to free water, and consequently, free water mobility increased. After 3 freeze–thaw cycles, the decline in shear force slowed, the increase in thawing loss became accelerated, and the TAC approached the domain value (6 log colony-forming units/g). Therefore, the number of freeze–thaw cycles of smooth muscle during transport, storage and distribution should be controlled to 3 or fewer. The current results provide a theoretical basis and data support for the further utilisation and culinary processing of smooth muscle.     

Ferulic acid and EGCG alter the structural characteristics of ovalbumin and its application in mineral loading

This study aims to fabricate mineral-loading nanocarriers using natural materials. The interaction patterns between ovalbumin (OVA) and four water-soluble polyphenols, namely ferulic acid (FA), (-)-Epigallo-catechin 3-gallate (EGCG), gallic acid (GA) and epicatechin (EC), were investigated. Results showed that the optimised conditions for preparing stable OVA–polyphenol complexes are at the OVA–polyphenol ratio of 4:1 at pH 6, under which OVA–FA and OVA–EGCG showed the highest stability and mineral-loading capacity among four OVA–polyphenol complexes. The fluorescence results indicated that the addition of EGCG and FA induced a significant fluorescence quenching to OVA. The interaction between OVA and polyphenols involved hydrogen bonding, hydrophobic interaction and electrostatic interaction. Fourier transform infrared spectroscopy (FTIR) analysis suggested that both FA and EGCG enhanced the stability and orderliness of the structure of OVA. The transmission electron microscopy images also exhibited the spherical structure of OVA after the addition of FA and EGCG. Furthermore, scanning electron microscope–energy dispersive X-ray spectrum results suggested that OVA–FA and OVA–EGCG complexes were better mineral carriers than OVA–GA and OVA–EC. This study may serve as the theoretical support for the promising application of OVA in the fabrication of mineral-loading nanocarriers in functional food and pharmaceutic.     

CDBN‑IKELM的轴承变工况故障诊断方法

针对现有方法在轴承变工况方面存在的诊断精度低、人工提取特征不充分等问题，提出了基于卷积深度置信网络（convolutional deep belief network，简称CDBN）与改进核极限学习机 （improved Kernel?based extreme learning machine，简称IKELM）的滚动轴承故障智能识别方法。首先，由卷积深度置信网络对原始信号内的故障特征进行深层自适应提取；其次，利用等距特征映射对提取的多维特征进行降维，去除冗余特征信息；然后，采用改进的核极限学习机对特征进行分类，使用粒子群（particle swarm optimization， 简称PSO）对模型重要参数进行优化，实现滚动轴承变工况下的故障识别；最后，将所提方法应用于不同工况下多种轴承故障的诊断。实验结果表明，该方法能够智能有效地识别变工况的轴承故障，诊断结果优于已有的智能故障诊断方法。     

ZnO·2.7Al2O3 nanocomposite with high optical transparency

Here we report a transparent dual-phase ZnO·2.7Al₂O₃ ceramic. The composite is pore-free and consists of thin nanosheets with a spinel phase and a hexagonal phase, while the two phases match closely in both lattice and refractive index. Such features result in excellent optical transmittance (maximum value >80% in the visible spectrum) at comparable phase volume. This work may provide a new thought for the rational structural design of optical nanocomposites.     

Influence of CO2 inleakage on the slight-alkalization of generator internal cooling water

The slight-alkalization of generator internal cooling water (GICW) is widely used to inhibit the corrosion of hollow copper conductor and thereby ensure the safe operation of the generator. CO₂ inleakage is increasingly identified as a potential security risk for GICW system. In this paper, the influence of CO₂ inleakage on the slight-alkalization of GICW was theoretically discussed. Based on the equilibriums of the CO₂-NaOH-H₂O system, CO₂ inleakage saturation was derived to quantify the amount of the dissolved CO₂ in GICW. This parameter can be directly calculated with the measured conductivity and the [Na⁺] of GICW. The influence of CO₂ inleakage on the slight-alkalization conditioning of GICW and the measurement of its water quality parameters were then analyzed. The more severe the inleakage, the narrower the water quality operation ranges of GICW, resulting in the more difficult the slight-alkalization conditioning of GICW. The temperature calibrations of the conductivity and the pH value of GICW show non-linear correlations with the amount of CO₂ inleakage and the NaOH dosage. This study provides insights into the influence of CO₂ inleakage on the slight-alkalization of GICW, which can serve as the theoretical basis for the actual slight-alkalization when CO₂ inleakage occurs.     

Resource management in UAV-assisted MEC: state-of-the-art and open challenges

Wireless Networks - Unmanned aerial vehicles (UAV) have been widely used in various fields because of their high mobility and portability. At the same time, due to the rapid development of...     

基于VMD和BSA-KELM的高陡边坡位移预测模型研究

边坡位移的时间序列曲线存在复杂的非线性特性,传统的预测模型精度不足以满足预测要求。为此提出了基于变分模态分解的鸟群优化-核极限学习机的预测模型,并用于河北省某水泥厂的边坡位移预测。该方法首先采用VMD把边坡位移序列分解为一系列的有限带宽的子序列,再对各子序列分别采用相空间重构并用核极限学习机预测,采用鸟群算法优化相空间重构的嵌入维度和KELM中惩罚系数和核参数三个数值,以取得最优预测模型。最后将各个子序列预测值叠加,得到边坡位移的最终预测值。结果表明：和KELM、BSA-KELM、EEMD-BSA-KELM模型相比,基于VMD的BSA-KELM预测精度更高,为边坡位移的预测提供一种有效的方法。     

Enhancement in lithium storage performances of SiO2/graphene-based nanocomposites prepared by low cost and facile approach

Journal of Materials Science: Materials in Electronics - The new nanocomposites of silicon dioxide/reduced graphene oxide (SiO2/rGO) and silicon dioxide/nitrogen-doped reduced graphene oxide...     

Optical-luminescence properties of ZnO and TiO2 nanopowders obtained by pulsed laser reactive ablation

Journal of Materials Science: Materials in Electronics - The ZnO and TiO2 nanopowders have been prepared by means of the pulsed laser reactive ablation of metallic (Zn, Ti) targets. The Structural,...