基于数据质量评价的目标估计

针对目标估计过程需要大量人工参与、自动化程度低的问题，提出了基于数据质量评价的目标估计方法。利用目标数据质量评价方法，对不同传感器得到的目标数据质量进行科学、有效的测度和评价，并根据质量得分动态调整各数据源在目标估计过程中所占的权重，从而减少人工干预，提高目标估计效能。仿真试验结果证明了该方法的有效性。     

Mutual information maximizing GAN inversion for real face with identity preservation

Recent generative adversarial networks (GANs) have yielded remarkable performance in face image synthesis. GAN inversion embeds an image into the latent space of a pretrained generator, enabling it to be used for real face manipulation. However, current inversion approaches for real faces suffer the dilemma of initialization collapse and identity loss. In this paper, we propose a hierarchical GAN inversion for real faces with identity preservation based on mutual information maximization. We first use a facial domain guaranteed initialization to avoid the initialization collapse. Furthermore, we prove that maximizing the mutual information between inverted faces and their identities is equivalent to minimizing the distance between identity features from inverted and original faces. Optimization for real face inversion with identity preservation is implemented on this mutual information-maximizing constraint. Extensive experimental results show that our approach outperforms state-of-the-art solutions for inverting and editing real faces, particularly in terms of face identity preservation.     

控制爆破法处理卡钻事故

介绍了在包头市某工程实施管道穿越黄河施工中,采用爆破法处理卡钻的经验。针对深水环境条件及钻杆内径小不宜采用集团装药的条件,确定采用"小直径爆破筒,钻杆内部装药"的爆破方案,阐述了爆破设计及施工注意事项。可供类似工程参考。     

IRS辅助的SWIPT系统中基于能效优先的波束成形设计与优化

以智能反射面(intelligent reflecting surface,IRS)辅助的无线携能通信(simultaneous wireless information and power transfer,SWIPT)系统为背景,研究了该系统中基于能效优先的多天线发送端有源波束成形与IRS无源波束成形联合设计与优化方法。以最大化接收端的最小能效为优化目标,构造在发送端功率、接收端能量阈值、IRS相移等多约束下的非线性优化问题,用交替方向乘子法(alternating direction method of multipliers,ADMM)求解。采用Dinkelbach算法转化目标函数,通过奇异值分解(singular value decomposition,SVD)和半定松弛(semi-definite relaxation,SDR)得到发送端有源波束成形向量。采用SDR得到IRS相移矩阵与反射波束成形向量。结果表明,该系统显著降低了系统能量收集(energy harvesting,EH)接收端的能量阈值。当系统总电路功耗为?15 dBm时,所提方案的用户能效为300 KB/J。当IRS反射阵源数与发送天线数均为最大值时,系统可达最大能效。     

Chemically complex intermetallic alloys: A new frontier for innovative structural materials

Intermetallic materials are bestowed by diverse ordered superlattice structures together with many unusual properties. In particular, the advent of chemically complex intermetallic alloys (CCIMAs) has received considerable attention in recent years and offers a new paradigm to develop novel metallic materials for advanced structural applications. These newly emerged CCIMAs exhibit synergistic modulations of structural and chemical features, such as self-assembled long-range close-packed ordering, complex sublattice occupancy, and interfacial disordered nanoscale layer, potentially allowing for superb physical and mechanical properties that are unmatched in conventional metallic materials. In this paper, we critically review the historical developments and recent advances in ordered intermetallic materials from the simple binary to chemically complex alloy systems. We are focused on the unique multicomponent superlattice microstructures, nanoscale grain-boundary segregation, and disordering, as well as the various extraordinary mechanical and functional properties of these newly developed CCIMAs. Finally, perspectives on the future research orientation, challenges, and opportunities of this new frontier are provided.     

Structure engineering of amorphous P–CoS hollow electrocatalysts for promoted oxygen evolution reaction

Oxygen evolution reaction (OER) is a key process involved in many energy-related conversion systems. An ideal OER electrocatalyst should possess rich active sites and optimal binding strength with oxygen-containing intermediates. Although numerous endeavors have been devoted to the modification and optimization of transition-metal-based OER electrocatalysts, they are still operated with sluggish kinetics. Herein, an ion-exchange approach is proposed to realize the structure engineering of amorphous P–CoS hollow nanomaterials by utilizing the ZIF-67 nanocubes as the precursors. The precise structure control of the amorphous hollow nanostructure contributes to the large exposure of surface active sites. Moreover, the introduction of phosphorus greatly modifies the electronic structure of CoS₂, which is thus favorable for optimizing the binding energies of oxygenated species. Furthermore, the incorporation of phosphorus may also induce the formation of surface defects to regulate the local electronic structure and surface environment. As a result of this, such P–CoS hollow nanocatalysts display remarkable electrocatalytic activity and durability towards OER, which require an overpotential of 283 mV to afford a current density of 10 mA cm^?2, outperforming commercial RuO₂ catalyst.     

Locating wind farm for power and hydrogen production based on Geographic information system and multi-criteria decision making method: An application

Hydrogen generation from renewable energy resources is considered as a suitable solution to solve the problems related to the energy sector and the reduction of greenhouse gases. The aim of this study is to provide an integrated framework for identifying suitable areas for the construction of wind farms to produce hydrogen. For this purpose, a combined method of Geographic Information System (GIS) and multi-criteria decision making (MCDM) has been used to locate the power plant in Yazd province. The GIS method in the present study consisted of two parts: constraints and criteria. The constraint section included areas that were unsuitable for the construction of wind farms to produce power and hydrogen. In the present study, various aspects such as physical, economic and environmental had been considered as constraints. In the criteria section, eight different criteria from technical aspects (including average wind speed, hydrogen production potential, land slope) and economic aspects (including distance to electricity grid, distance to urban areas, distance to road, distance to railway and distance to centers of High hydrogen consumption) had been investigated. The MCDM tool had been used to weigh the criteria and identify suitable areas. Analytic Hierarchy Process (AHP) technique was used for weighting the criteria. The results of AHP weighting method showed that economic criteria had the highest importance with a value of 0.681. The most significant sub-criterion was the distance to urban areas and the least significant sub-criterion was the distance to power transmission lines. The results of GIS-MCDM analysis had shown that the most proper areas were in the southern and central sectors of Yazd province. In addition, the feasibility of hydrogen production from wind energy had shown that this province had the capacity to generate hydrogen at the rate of 53.6–128.6 tons per year.     

Adenine-functionalized conjugated polymer as an efficient photocatalyst for hydrogen evolution from water

Conjugated polymers have emerged as a promising class of organic photocatalysts for photocatalytic hydrogen evolution from water splitting due to their adjustable chemical structures and electronic properties. However, developing highly efficient organic polymer photocatalysts with high photocatalytic activity for hydrogen evolution remains a significant challenge. Herein, we present an efficient approach to enhance the photocatalytic performance of linear conjugated polymers by modifying the surface chemistry via introducing a hydrophilic adenine group into the side chain. The adenine unit with five nitrogen atoms could enhance the interaction between the surface of polymer photocatalyst and water molecules through the formation of hydrogen bonding, which improves the hydrophilicity and dispersity of the resulting polymer photocatalyst in the photocatalytic reaction solution. In addition, the strong electron-donating ability of adenine group with plentiful nitrogen atoms could promote the separation of light-induced electrons and holes. As a result, the adenine-functionalized conjugated polymer PF6A-DBTO2 shows a high photocatalytic activity with a hydrogen evolution rate (HER) of 25.21 mmol g^?1 h^?1 under UV-Vis light irradiation, which is much higher than that of its counterpart polymer PF6-DBTO2 without the adenine group (6.53 mmol g^?1 h^?1). More importantly, PF6A-DBTO2 without addition of a Pt co-catalyst also exhibits an impressive HER of 21.93 mmol g^?1 h^?1 under visible light (λ > 420 nm). This work highlights that it is an efficient strategy to improve the photocatalytic activity of conjugated polymer photocatalysts by the modification of surface chemistry.     

土木工程施工课程线上平台教学实践

土木工程施工课程作为土木工程及工程管理专业的学科基础课和核心专业课程,在疫情防控期间"停课不停教""停课不停学"的要求下,通过线上平台进行授课。由于土木工程施工课程内容庞杂、综合性强、实践性强,且章节之间关联性较弱,探究既能使学生快速适应,又能保证教学质量的在线教学方法至关重要。以华南某高校土木工程施工课程为例,基于中国大学MOOC、建筑云课、腾讯课堂、QQ群等线上平台讲授教学内容,并运用问卷调查对课程线上教学效果进行评价。结果表明,线上教学为学生提供了丰富灵活的学习方式,显著提高了学生的自主学习能力,扩大了学生的知识面,达到了较好的学习效果。     

A Tradeoff Between Accuracy and Speed for K-Means Seed Determination

With a sharp increase in the information volume, analyzing and retrieving this vast data volume is much more essential than ever. One of the main techniques that would be beneficial in this regard is called the Clustering method. Clustering aims to classify objects so that all objects within a cluster have similar features while other objects in different clusters are as distinct as possible. One of the most widely used clustering algorithms with the well and approved performance in different applications is the k-means algorithm. The main problem of the k-means algorithm is its performance which can be directly affected by the selection in the primary clusters. Lack of attention to this crucial issue has consequences such as creating empty clusters and decreasing the convergence time. Besides, the selection of appropriate initial seeds can reduce the cluster’s inconsistency. In this paper, we present a new method to determine the initial seeds of the k-mean algorithm to improve the accuracy and decrease the number of iterations of the algorithm. For this purpose, a new method is proposed considering the average distance between objects to determine the initial seeds. Our method attempts to provide a proper tradeoff between the accuracy and speed of the clustering algorithm. The experimental results showed that our proposed approach outperforms the Chithra with 1.7% and 2.1% in terms of clustering accuracy for Wine and Abalone detection data, respectively. Furthermore, achieved results indicate that comparing with the Reverse Nearest Neighbor (RNN) search approach, the proposed method has a higher convergence speed.