Tar sand extractions with microemulsions: I-the dissolution of light hydrocarbons by microemulsions using 2-butoxyethanol and diethylmethylamine as cosurfactants

For oil sand extractions with microemulsions it is important to disperse large quantities of light hydrocarbons in an aqueous medium. Fundamental studies on the properties of 2-butoxyethanol (BE) and diethylmethylamine (Et₂McN) in water suggest that these two liquids could be more effective cosurfactants than the usual alcohols used for this purpose. The phase diagrams of microemulsions using BE and Et₂MeN as cosurfactants, combined with typical ionic and non-ionic surfactants and typical aliphatic and aromatic hydrocarbons, were therefore investigated and compared with microemulsions based on n-butanol. Although the phase diagrams depend significantly on the nature of the surfactant and of the oil, the monophasic region generally increases with the cosurfactant in the order n-butanol < Et₂McN < BE. With the active mixture BE-cetyltrimethylammonium bromide, temperature has little effect on the phase diagram and NaCl generally destabilizes the microemulsion.     

Re-GAN：残差生成式对抗网络算法

目的 生成式对抗网络（generative adversarial network,GAN）是一种无监督生成模型,通过生成模型和判别模型的博弈学习生成图像。GAN的生成模型是逐级直接生成图像,下级网络无法得知上级网络学习的特征,以至于生成的图像多样性不够丰富。另外,随着网络层数的增加,参数变多,反向传播变得困难,出现训练不稳定和梯度消失等问题。针对上述问题,基于残差网络（residual network,ResNet）和组标准化（group normalization,GN）,提出了一种残差生成式对抗网络（residual generative adversarial networks,Re-GAN）。方法 Re-GAN在生成模型中构建深度残差网络模块,通过跳连接的方式融合上级网络学习的特征,增强生成图像的多样性和质量,改善反向传播过程,增强生成式对抗网络的训练稳定性,缓解梯度消失。随后采用组标准化（GN）来适应不同批次的学习,使训练过程更加稳定。结果 在Cifar10、CelebA和LSUN数据集上对算法的性能进行测试。Re-GAN的IS （inception score）均值在批次为64时,比DCGAN （deep convolutional GAN）和WGAN （Wasserstein-GAN）分别提高了5%和30%,在批次为4时,比DCGAN和WGAN分别提高了0.2%和13%,表明无论批次大小,Re-GAN生成图像具有很好的多样性。Re-GAN的FID （Fréchet inception distance）在批次为64时比DCGAN和WGAN分别降低了18%和11%,在批次为4时比DCGAN和WGAN分别降低了4%和10%,表明Re-GAN生成图像的质量更好。同时,Re-GAN缓解了训练过程中出现的训练不稳定和梯度消失等问题。结论 实验结果表明,在图像生成方面,Re-GAN的生成图像质量高、多样性强;在网络训练方面,Re-GAN在不同批次下的训练具有更好的兼容性,使训练过程更加稳定,梯度消失得到缓解。     

Micro cam system driven by electrostatic comb-drive actuators based on SOI-MEMS technology

Microsystem Technologies - This paper reports a design and fabrication process of a micro cam system (MCS) with a flat-faced translating follower. The cam rim with cover diameter of 2.4&nbsp;mm...     

基于SPI双机通信的弧光保护系统

针对弧光保护系统的实际需要,设计了一种基于SPI的双机通信系统。简要阐述了该系统的设计思路,并给出了具体的实现方法。实验表明,采用该方法能够满足实际工程中的需求,对于其他SPI的应用也有很好的借鉴价值。     

聚类算法在高脂血症辨证分型研究中的应用

高脂血症的辨证分型标准化研究是中医基础研究的热点与难点,利用计算机挖掘技术中的聚类算法对高脂血症临床中医症状数据进行分析,得到具有统计学意义的分类结果,同时寻找其与中医证候相对应的关系具有重要研究价值.通过编写适用于中医证候分类的聚类算法并提供设置相似度阈值等交互界面,实现了大规模样本的自适应分类,从而使聚类结果更加科学客观.将得到的每个类别中所对应样本的病症特征与所属中医的证候类别联系起来,为辨证分型标准化奠定了基础.     

VICUR: A human-vision-based algorithm for curve reconstruction

In this paper, a new algorithm, named VICUR, is presented for curve reconstruction problem. From a set of unorganized points, the proposed algorithm can construct curves that look natural to human vision. The VICUR algorithm is based on two connectivity criteria: proximity and good continuation from the prominent Gestalt principles of perception. Experimental results are presented to show the effectiveness of VICUR.     

Semplore: A scalable IR approach to search the Web of Data

The Web of Data keeps growing rapidly. However, the full exploitation of this large amount of structured data faces numerous challenges like usability, scalability, imprecise information needs and data change. We present Semplore, an IR-based system that aims at addressing these issues. Semplore supports intuitive faceted search and complex queries both on text and structured data. It combines imprecise keyword search and precise structured query in a unified ranking scheme. Scalable query processing is supported by leveraging inverted indexes traditionally used in IR systems. This is combined with a novel block-based index structure to support efficient index update when data changes. The experimental results show that Semplore is an efficient and effective system for searching the Web of Data and can be used as a basic infrastructure for Web-scale Semantic Web search engines.     

Cell Development Enhanced Bionic Silk Hydrogel on Remodeling Immune Pathogenesis of Spinal Cord Injury via M2 Polarization of Microglial

Due to the complex spatial-temporal pathophysiology of spinal cord injury (SCI), effective modulation of SCI-specific inflammatory pathogenesis to achieve desirable therapeutic effects on functional recovery still remains challenging. Herein, cell-enhanced photocrosslinked silk fibroin hydrogels with extracellular matrix-mimicking cues of mechanical properties and RGD (Arg-Gly-Asp) signals are gelled in situ to fill the lesion site to modulate injury-induced neuroinflammation and promote neurite regrowth after SCI. The bionic hydrogel system provides biomimetic mechanical cues to promote neuronal differentiation of neural stem/progenitor cells (NPCs) and neurite growth by activating YAP nuclear expression. Importantly, favored by the strong capacity of silk fibroin hydrogels on macrophage/microglia recruitment, NPCs encapsulated hydrogel (NPCs@SFRGD0.1) effectively promotes recruited macrophages/microglia to M2 polarization in the lesion site by releasing S100A4 and thereby remodels the inflammatory microenvironment after SCI. Moreover, NPCs@SFRGD0.1 successfully reduces glial scar formation and accelerates corticospinal tract axon regrowth to improve locomotor recovery. Overall, this work contributes to illustrating the therapeutic mechanism of NPCs development based biomaterial therapies on modulating inflammatory microenvironment and this NPCs enhanced silk fibroin hydrogel provides a promising therapeutic strategy for SCI.     

Metal Single-Site Molecular Complex–MXene Heteroelectrocatalysts Interspersed Graphene Nanonetwork for Efficient Dual-Task of Water Splitting and Metal–Air Batteries

Development of multifunctional electrocatalysts with high efficiency and stability is of great interest in recent energy conversion technologies. Herein, a novel heteroelectrocatalyst of molecular iron complex (Fe_MC)-carbide MXene (Mo₂TiC₂T_x) uniformly embedded in a 3D graphene-based hierarchical network (GrH) is rationally designed. The coexistence of Fe_MC and MXene with their unique interactions triggers optimum electronic properties, rich multiple active sites, and favorite free adsorption energy for excellent trifunctional catalytic activities. Meanwhile, the highly porous GrH effectively promotes a multichannel architecture for charge transfer and gas/ion diffusion to improve stability. Therefore, the Fe_MC–MXene/GrH results in superb performances towards oxygen reduction reaction (ORR), oxygen evolution reaction (OER), and hydrogen evolution reaction (HER) in alkaline medium. The practical tests indicate that Zn/Al–air batteries derived from Fe_MC–MXene/GrH cathodic electrodes produce high power densities of 165.6 and 172.7 mW cm⁻², respectively. Impressively, the liquid-state Zn–air battery delivers excellent cycling stability of over 1100 h. In addition, the alkaline water electrolyzer induces a low cell voltage of 1.55 V at 10 mA cm⁻² and 1.86 V at 0.4 A cm⁻² in 30 wt.% KOH at 80 °C, surpassing recent reports. The achievements suggest an exciting multifunctional electrocatalyst for electrochemical energy applications.