Electrocatalytic Reduction of CO2 to Ethylene by Molecular Cu‐Complex Immobilized on Graphitized Mesoporous Carbon

The electrochemical reduction of carbon dioxide (CO₂) to hydrocarbons is a challenging task because of the issues in controlling the efficiency and selectivity of the products. Among the various transition metals, copper has attracted attention as it yields more reduced and C2 products even while using mononuclear copper center as catalysts. In addition, it is found that reversible formation of copper nanoparticle acts as the real catalytically active site for the conversion of CO₂ to reduced products. Here, it is demonstrated that the dinuclear molecular copper complex immobilized over graphitized mesoporous carbon can act as catalysts for the conversion of CO₂ to hydrocarbons (methane and ethylene) up to 60%. Interestingly, high selectivity toward C2 product (40% faradaic efficiency) is achieved by a molecular complex based hybrid material from CO₂ in 0.1 m KCl. In addition, the role of local pH, porous structure, and carbon support in limiting the mass transport to achieve the highly reduced products is demonstrated. Although the spectroscopic analysis of the catalysts exhibits molecular nature of the complex after 2 h bulk electrolysis, morphological study reveals that the newly generated copper cluster is the real active site during the catalytic reactions.     

视频侦查中人像智能分析应用及算法优化

人像智能分析指的是对视频或录像中的人像进行结构化和可视化分析,对目标人物进行性别、年龄、发型等特征的智能识别,这项技术在视频侦查中有极高的应用价值。人像识别早期的算法是通过人工提取特征,通过学习低级视觉特征来针对不同属性进行分类学习,这种基于传统方法的模型表现常常不尽如人意。在计算机视觉领域,通过海量图像数据学习的神经网络比传统方法有更丰富的信息量和特征可以被提取。文章尝试通过深度学习技术训练神经网络模型对行人进行检测和识别,对于衣着不同的行人进行智能识别,具有更好的鲁棒性,提升了视频人像识别的准确率,拓展了人工智能技术在身份识别领域的应用。     

Genes Identification,Molecular Docking and Dynamics Simulation Analysis of Laccases from Amylostereum areolatum Provides Molecular Basis of Laccase Bound to Lignin

An obligate mutualistic relationship exists between the fungus Amylostereum areolatum and woodwasp Sirex noctilio. The fungus digests lignin in the host pine, providing essential nutrients for the growing woodwasp larvae. However, the functional properties of this symbiosis are poorly described. In this study, we identified, cloned, and characterized 14 laccase genes from A. areolatum. These genes encoded proteins of 508 to 529 amino acids and contained three typical copper-oxidase domains, necessary to confer laccase activity. Besides, we performed molecular docking and dynamics simulation of the laccase proteins in complex with lignin compounds (monomers, dimers, trimers, and tetramers). AaLac2, AaLac3, AaLac6, AaLac8, and AaLac10 were found that had low binding energies with all lignin model compounds tested and three of them could maintain stability when binding to these compounds. Among these complexes, amino acid residues ALA, GLN, LEU, PHE, PRO, and SER were commonly present. Our study reveals the molecular basis of A. areolatum laccases interacting with lignin, which is essential for understanding how the fungus provides nutrients to S. noctilio. These findings might also provide guidance for the control of S. noctilio by informing the design of enzyme mutants that could reduce the efficiency of lignin degradation.     

Sequence-Dependent Nanofiber Structures of Phenylalanine and Isoleucine Tripeptides

The molecular design of short peptides to achieve a tailor-made functional architecture has attracted attention during the past decade but remains challenging as a result of insufficient understanding of the relationship between peptide sequence and assembled supramolecular structures. We report a hybrid-resolution model to computationally explore the sequence–structure relationship of self-assembly for tripeptides containing only phenylalanine and isoleucine. We found that all these tripeptides have a tendency to assemble into nanofibers composed of laterally associated filaments. Molecular arrangements within the assemblies are diverse and vary depending on the sequences. This structural diversity originates from (1) distinct conformations of peptide building blocks that lead to different surface geometries of the filaments and (2) unique sidechain arrangements at the filament interfaces for each sequence. Many conformations are available for tripeptides in solution, but only an extended β-strand and another resembling a right-handed turn are observed in assemblies. It was found that the sequence dependence of these conformations and the packing of resulting filaments are determined by multiple competing noncovalent forces, with hydrophobic interactions involving Phe being particularly important. The sequence pattern for each type of assembly conformation and packing has been identified. These results highlight the importance of the interplay between conformation, molecular packing, and sequences for determining detailed nanostructures of peptides and provide a detailed insight to support a more precise design of peptide-based nanomaterials.     

Road Extraction from High Resolution Remote Sensing Image based on Shape Analysis with Gestalt Theory

Simulating the psychological experience of human vision，a road extraction model based on the format tower is proposed to extract the road in the high resolution remote sensing image from the perspective of morphology.Firstly，based on the spectral and texture information，the suspected road targets are extracted by using segmentation technology.Then these targets are classified according to their reliability and extract the road targets for each category.Finally，three types of identified road information are verified and merged，and the continuous smooth road extraction results are obtained.Experiments on real high resolution images show that the results are consistent with the visual perception of the human eye，and the overall classification accuracy is higher，indicating that the algorithm is effective and feasible and has good use value.     

Food recognition using neural network classifier and multiple hypotheses image segmentation

ABSTRACT

This paper proposes the multiple-hypotheses image segmentation and feed-forward neural network classifier for food recognition to improve the performance. Initially, the food or meal image is given as input. Then, the segmentation is applied to identify the regions, where a particular food item is located using salient region detection, multi-scale segmentation, and fast rejection. Then, the features of every food item are extracted by the global feature and local feature extraction. After the features are obtained, the classification is performed for each segmented region using a feed-forward neural network model. Finally, the calorie value is computed with the aid of (i) food volume and (ii) calorie and nutrition measure based on mass value. The experimental results and performance evaluation are validated. The outcome of the proposed method attains 0.947 for Macro Average Accuracy (MAA) and 0.959 for Standard Accuracy (SA), which provides better classification performance.     

Volatile organic compound profiles of yoghurt produced from cow's milk with different somatic cell counts

The present study aimed to investigate the effect of somatic cell count (SCC) of raw cow's milk on the volatile organic compound (VOC) profiles of yoghurt. Test yoghurt samples were produced from three batches of cow's milk with low, medium and high SCC, respectively. The VOCs were determined by gas chromatography–mass spectrometry (GC–MS) analysis. A lower diacetyl and acetoin content and a higher content of 2‐heptanone, and butanoic and hexanoic acids were established in the yoghurt samples from batches with high SCC of above 1 000 000 cells/cm³. The increased SCC of cow's milk had a negative effect on the volatile organic compound profiles of yoghurt.     

1,5-己二烯交联烯烃聚合物的合成及其抗剪切稳定性

以金属配合物为催化剂、1,5-己二烯为交联剂,采用本体聚合法合成了交联超高相对分子质量烯烃类聚合物(简称交联聚合物)。用傅里叶变换红外光谱、核磁共振、凝胶渗透色潜表征交联聚合物的结构和相对分子质量。用旋转黏度计和超声波仪研究了1,5-己二烯用量对交联聚合物溶液表观黏度的影响及交联聚合物的相对分子质量对交联聚合物溶液抗剪切稳定性的影响。实验结果表明,在最佳聚合条件(单体80mL、助催化剂0．4mL、CS-1催化剂0．090g、1,5-己二烯0．40mL、0℃、24 b)下所合成的交联聚合物的重均相对分子质量为7．7×106,数均相对分子质量3．6×106。加入少量1,5-己二烯能提高交联聚合物的抗剪切能力,同时也能提高交联聚合物的相对分子质量。交联聚合物的相对分子质量越大,抗剪切稳定性越好。1,5-己二烯用量约为0．1 mL时(单体40 mL),交联聚合物溶液的表观黏度达到最大值(16．8 mPa·s)。     

高浓度聚合物驱提高采收率方法实验研究

为探索一种新的提高原油采收率的方法,在外形尺寸为4.5 cm×4.5 cm×30 cm、气测渗透率0.9~1.0μm2、变异系数为0.72的二维纵向非均质人造岩心上,模拟大庆油田油藏流体性质及温度条件,研究了高浓度聚合物(HPAM)驱注入时机、聚合物相对分子质量、聚合物段塞体积及段塞组合对驱油效果的影响。通过注入大分子量、高浓度聚合物,结合合理的注入方式,在化学剂成本与三元复合驱相当的情况下,采收率比水驱提高20个百分点以上,接近或超过三元复合驱的水平。实验表明,采用高浓度聚合物驱油是一种较好的提高原油采收率的方法。