Cu/Fe3O4 catalyst for water gas shift reaction: Insight into the effect of Fe2+ and Fe3+ distribution in Fe3O4

Two precursors, namely, p-CFO-T (tetragonal) and p-CFO-C (cubic), were fabricated by a sol-gel method via citric acid and poly(vinyl alcohol) complexation, respectively. After H₂-reduction, the two were converted to Cu/Fe₃O₄ catalysts of different complexions, which are named as CFO-CA and CFO-PVA, respectively. The distribution of Fe²⁺ and Fe³⁺ in the Cu/Fe₃O₄ catalysts was studied by Raman and XPS techniques. It was disclosed that the distribution of Fe²⁺ and Fe³⁺ in Fe₃O₄ has an effect on Cu–Fe₃O₄ interaction and catalyst surface basicity. Compared to CFO-PVA, CFO-CA has a larger amount of Fe³⁺, which mostly sits at the octahedral sites, leading to stronger Cu–Fe₃O₄ interaction, and a larger amount of catalyst surface sites that are of weak basicity. As a result, the critical elementary steps of WGS reaction, viz. water dissociation, –COOH decomposition and CO₂ desorption are promoted as reflected in the lower E_a and higher catalytic activity of CFO-CA.     

太赫兹脉冲焦平面成像技术的发展与应用

作为太赫兹技术中的重要组成部分,太赫兹脉冲焦平面成像一经问世就引起了行业内的广泛关注,人们引入了各种方法去提升此成像技术的测量性能,同时也尝试将此成像技术应用于不同的工业和基础研究领域。本文综述了近年来人们对太赫兹脉冲焦平面成像的技术改良和应用研究,包括提升成像系统的空间分辨率、信噪比、信息获取能力,以及将此成像技术应用于光谱识别检测、超表面器件功能验证、太赫兹特殊光束测量、太赫兹表面波观测等,希望该综述能够推动太赫兹脉冲焦平面成像的进一步技术革新和应用拓展。     

Representation learning in discourse parsing: A survey

Science China Technological Sciences - Neural network based deep learning methods aim to learn representations of data and have produced state-of-the-art results in many natural language processing...     

基于深度残差学习的自动驾驶道路场景理解

随着道路场景理解技术的快速发展，自主驾驶领域取得了长足的进步。在相关任务中，包括道路分割、分类和车辆检测的实时性和准确性是安全性的一个关键问题。为此，提出了一个具有编/解码器网络结构的基于深度残差学习的方法。一方面，编码器网络结构使用不同层次的残差网络来提取高维中的抽象特征，这些特征在接下来的三个任务中共享使用；另一方面，解码器网络结构采用一种子任务的并行计算机制，即道路分割、车辆检测和道路分类任务同时执行。此外，全卷积神经网络用于对提取的图像特征进行上采样以解决道路分割问题。最终，实验结果表明在保证高精度的前提下处理帧率可达到15 fps以上。     

Surface nanodeformations caused by ultrashort laser pulse

Ultrashort laser pulse is a unique nanometallurgical tool which operates at extreme conditions: ultimate strength of material, the smallest spatiotemporal scales, and nonequlibrium crystallization. Approaches to ultimate strength and to highly nonequlibrium crystallization are tightly coupled with the smallness of spatiotemporal scales. Usage of the tool opens new opportunities to create materials with enhanced surface hardness, anticorrosion properties, and diverted optical constants. To use these advantages we have first of all to develop clear and reliable physical model. The paper presents new results concerning interactions of optical or X-ray lasers with metals. It is shown that ultrashort laser pulse melts surface layer, sends shock into bulk, and foams molten metal. Dense dislocation bilayer is created thanks to fast recrystallization (the first sublayer) and plastic transformations behind strong shock (the second sublayer). Plastic shock generated at moderate laser intensities attenuates sharply during its propagation into metal. During this attenuation, a plastic shock regenerates into a powerful elastic shock. This process defines boundary between the second dislocation sublayer and undamaged solid. Mechanical breaking of foam after its strong stretching and fly away of a part of melt together with fast freezing are responsible for appearance of chaotic frozen nanostructures at an irradiated surface.     

Sol–gel synthesis of Nd-doped BiFeO3 multiferroic and its characterization

Neodymium doped bismuth ferrite (BiFeO₃, BFO) nanoparticles were successfully synthesized by a facile sol–gel route. The influence of annealing temperature, time, Bi content and solvent on the crystal structure of BFO was studied. Results indicated that the optimum processing condition of BFO products was 550–600 °C/1.5 h with excess 3–6% Bi and ethylene glycol as solvent. On the other hand, Nd³⁺ ion was introduced into the BFO system and the effect of Nd³⁺ concentration on the structure, magnetic and dielectric properties of BFO were investigated. It was found that the magnetization of BFO was enhanced significantly with Nd³⁺ substitution, being attributed to the suppression of the spiral cycloidal magnetic structure led by the crystal structure transition. Furthermore, with increasing Nd³⁺ content, the dielectric constant was found to decrease while the dielectric loss was enhanced, which was mainly due to the hoping conduction mechanism with the reduction of oxygen vacancies.     

基于归一化水体指数及其阈值自适应算法的水体遥感反演效果分析

归一化水体指数（NDWI）是水体遥感反演的一种重要指标，其阈值及修正直接影响反演结果的精度。基于Landsat-8与GF-1光学多光谱影像，使用归一化水体指数法阈值0（TH₀）、最大类间方差法（OTSU）自适应阈值（TH_otsu）与均值漂移聚类算法（Mean-Shift）自适应阈值（TH_MS）分别对典型正常水体、云雾覆盖水体、富营养化水体、高含泥沙水体进行水体遥感提取与效果分析，结果表明：正常水体以TH₀为阈值提取精度最高，THMS提取精度次之，TH_otsu提取精度最差；而云雾覆盖水体、富营养化水体以及含泥沙水体使用THMS提取精度最高，尤其少量云雾覆盖下的水体，TH_MS具有更明显的优势，TH₀提取精度次之，TH_otsu提取精度最差；对于不同的阈值，Land?sat-8比GF-1总体表现出更高的水体提取精度。Mean-Shift算法应用于NDWI阈值修正与水体遥感反演具有快速、水质适应性强、效果稳定的优势，对尤其是复杂条件下的水体信息遥感反演具有较好的提取效果。     

Linking energy efficiency and innovation practices: Empirical evidence from the foundry sector

The Europe 2020 strategy currently promotes energy efficiency and innovation through disconnected targets focusing on either energy or R&D. Similar policies indicate that in practice, these two concepts are usually perceived as mutually exclusive. Furthermore, evidence in the literature regarding the relationship between R&D and energy efficiency is still highly limited. This exploratory study aims to address this gap by investigating the link between innovation practices and energy efficiency through a multiple case study of 30 foundries in Northern Italy. We analysed the firms' innovativeness, measured by internal R&D and Open Innovation practices (inbound and outbound), and energy efficiency, measured by specific energy consumption, level of adoption of energy-efficient technologies and barriers to energy efficiency. The results seem to show that those foundries complementing internal R&D with inbound practices have a higher level of energy efficiency, a higher level of adoption of available technologies, and a lower perception of barriers to efficiency improvements. This finding suggests that diversifying innovation practices could lead to better performance with respect to all three indicators of energy efficiency analysed. This study contributes to understanding how more innovative firms can be more energy efficient, providing interesting highlights for managers and policymakers.     

Automatic salient object sequence rebuilding for video segment analysis

Detection of salient object sequences from video data is challenging when the salient object changes between consecutive frames. In this study, we addressed the salient object sequence rebuilding problem with video segment analysis. We reformulated the problem as a binary labeling problem, analyzed the potential salient object sequences in the video using a clustering method, and separated the salient object sequence from the background by applying an energy optimization method. Our proposed approach determines whether temporal consecutive pixels belong to the same salient object sequence. The conditional random field is then learned to effectively integrate the salient features and the sequence consecutive constraints. A dynamic programming algorithm was developed to resolve the energy minimization problem efficiently. Experimental results confirmed the ability of our approach to address the salient object rebuilding problem in automatic visual attention applications and video content analysis.