Topology optimization of flexure hinges with a prescribed compliance matrix based on the adaptive spring model and stress constraint

This paper focuses on the configuration design of flexure hinges with a prescribed compliance matrix and preset rotational center position. A new method for the topology optimization of flexure hinges is proposed based on the adaptive spring model and stress constraint. The hinge optimization model is formulated by maximizing the bending displacement with a spring while optimizing the compliance matrix to a prescribed value. To avoid numerical instability, an artificial spring is used as an auxiliary calculation, and a new strategy is developed for adaptively adjusting the spring stiffness according to the prescribed compliance matrix. The maximum stress of flexure hinge is limited by using a normalized P-norm of the effective von Mises stress, and a position constraint of rotational center is proposed to predetermine the position of the rotational center. In addition, to reduce the error of the stress measurement, a simple but effective filtering method is presented to obtain a complete black-and-white design. Numerical examples are used to verify the proposed method. Topology results show that the obtained flexure hinges have the prescribed compliance matrix and preset rotational center position while also meeting the stress requirements.     

Residual attention-based tracking-by-detection network with attention-driven data augmentation

Tracking-by-detection (TBD) is a significant framework for visual object tracking. However, current trackers are usually updated online based on random sampling with a probability distribution. The performance of the learning-based TBD trackers is limited by the lack of discriminative features, especially when the background is full of semantic distractors. We propose an attention-driven data augmentation method, in which a residual attention mechanism is integrated into the TBD tracking network as supplementary references to identify discriminative image features. A mask generating network is used to simulate changes in target appearances to obtain positive samples, where attention information and image features are combined to identify discriminative features. In addition, we propose a method for mining hard negative samples, which searches for semantic distractors with the response of the attention module. The experiments on the OTB2015, UAV123, and LaSOT benchmarks show that this method achieves competitive performance in terms of accuracy and robustness.     

Recent advances in carbon nanotubes-based microwave absorbing composites

With the blossom of information industry, electromagnetic wave technology shows increasingly potential in many fields. Nevertheless, the trouble caused by electromagnetic waves has also drawn extensive attention. For instance, electromagnetic pollution can threaten information safety in vital fields and the normal function of delicate electronic devices. Consequently, electromagnetic pollution and interference become an urgent issue that needs to be addressed. Carbon nanotubes (CNTs) have become a potential candidate to deal with these problems due to many advantages, such as high dielectric loss, remarkable thermodynamic stability, and low density. With the appearance of climbing demands, however, the carbon nanotubes combining various composites have shown greater prospects than the single CNTs in microwave absorbing materials. In this short review, recent advances in CNTs-based microwave absorbing materials were comprehensively discussed. Typically, we introduced the electromagnetic wave absorption mechanism of CNTs-based microwave absorbing materials and generalized the development of CNTs-based microwave absorbers, including CNTs-based magnetic metal composites, CNTs-based ferrite composites, and CNTs-based polymer composites. Ultimately, the growing trend and bottleneck of CNTs-based composites for microwave absorption were analyzed to provide some available ideas to more scientific workers.     

The Chemistry of DPPH· Free Radical and Congeners

Since the discovery in 1922 of 2,2-diphenyl-1-(2,4,6-trinitrophenyl) hydrazyl stable free radical (DPPH^·), the chemistry of such open-shell compounds has developed continuously, allowing for both theoretical and practical advances in the free radical chemistry area. This review presents the important, general and modern aspects of the chemistry of hydrazyl free radicals and the science behind it.     

车门铰链系统与车门下沉刚度的相关性

针对某型车门下沉问题,通过台架试验获得车门、铰链和车身等各单因素下沉量和车门绞链系统整体下沉量,对单因素下沉量与系统整体下沉刚度进行线性拟合分析,得到车门铰链系统各单因素与系统下沉刚度的相关度排序.对前、后车门分别选取相关度较高的单因素进行优化,最终改进方案的仿真和试验结果证明该方案可有效地提升车门下沉刚度.采用定量分析法可快速找出影响下沉刚度的敏感因素,并能够快速生成优化方案,为新车型设计提供参考.     

Optimization of room-temperature TCR of polycrystalline La0.9-xSrxK0.1MnO3 ceramics by Sr adjustment

High-density La_0.9-xSr_xK_0.1MnO₃ ceramics (LSKMO, A-site = La, Sr and K, 0 ≤ x ≤ 0.25) are successfully fabricated by using facile sol-gel method. Electrical properties are performed by using combination of phenomenological percolation (PP) model, double exchange (DE) mechanism, and Jahn-Teller (JT) effect. Moreover, X-ray diffraction and scanning electron microscopy are employed to analyze the structure and morphology of LSKMO ceramics. Valence states and ionic stoichiometry are assessed by using X-ray photoemission spectrometry. Results reveal that Sr²⁺ ions, substituting La³⁺ ions, significantly influenced DE mechanism and JT effect. In addition, Sr-doping plays essential role in improving electrical properties of LSKMO ceramics. At optimal doping content of x = 0.09, peak temperature coefficient of resistance (TCR) of the resistivity is found to be 11.56% K^?1 at 297.15 K, which is optimal TCR for A-site K-occupied perovskite manganese oxides. These results confirm that polycrystalline LSKMO ceramics render high room-temperature TCR values due to Sr-doping.     

A novel approach for bulk micromachining of 4H-SiC by tool-based electrolytic plasma etching in HF-free aqueous solution

Bulk micromachining of single-crystal SiC has been challenging due to its extreme stability both mechanically and chemically. To address this issue, a novel tool-based electrolytic plasma etching method is proposed, with which micropatterns and micro-holes are fabricated in SiC in a hydrofluoric acid-free aqueous solution with no need for masks. The material removal is the result of the combined effects of electrolytic plasma chemistry and physics. The chemistry refers to the reaction of Si with hydroxyl radical to form various SiO_x and with H to form silanes, and the reactions of C to form volatile carbon oxides or hydrocarbons, all of which are accomplished and enhanced under the electrolytic plasma atmosphere. Besides, the local high temperature of plasma thermally promotes the evaporation or dissolution of SiO₂ in NaOH solution. The tool-based electrolytic plasma etching method provides alternative approaches for the fabrication of SiC-based MEMS and devices.     

结合句法依存信息的方面级情感分类

引入句法依存信息到原方面术语,提出一种新的方面术语表示方法,利用Glove词向量表示单词以及单词与单词之间的依存关系,构造出包含句法依存信息的依存关系邻接矩阵和依存关系表示矩阵,利用图卷积神经网络和多头注意力机制将句法依存信息融入到方面术语中,使得方面术语表达与上下文结构高度相关。将改进后的方面词术语表示替换到现有模型后,模型泛化能力得到有效提升。对比试验和分析结果表明:该方法具有有效性和泛化性。     

Sustainable optimization of waste management network over extended planning time horizon

This study proposes a multiperiod mixed integer linear programming model for the management of a single municipal solid waste (MSW) treatment plant with sustainability as the objective. Discrete and continuous variables define the capacity selections for diverse MSW technologies, and the operation of the MSW network, respectively. The economic target is considered to maximize the net present value. The environmental impact is the minimization of a normalized environmental objective function (NEOF). The social target is the maximization of jobs. An interesting feature about the research work is the requirement of biodrying technologies for MSW moisture content control. Due to the conflicted nature among the sustainability components, a multiobjective optimization (MO) is carried out to find the Pareto optimal solutions. The MO results show that the Pareto optimal solutions vary around profit range of $4.9–8.5 billion, NEOF impact range of 3.2–3.6 units, and social benefit range of 2700–4828 jobs.