Research on design management based on green remanufacturing engineering

AbstractWith the popularization of the concept of “Product Multi-lifecycle” and “Extended Producer Responsibility”, many manufacturers put the concept of green remanufacturing engineering into practice and begin to think about how to do the design management based on green remanufacturing engineering. This paper firstly analyses the concept of the remanufacturability, then explores the design content for new products’ remanufacturability, and builds up the evaluation model of a used product's remanufacturability, in which the remanufacturability index of a used product is the product of the technological index and the economical index

Fine needle aspiration cytology of hepatic metastases of neuroendocrine tumors: A 20‐year retrospective, single institutional study

Background Fine needle aspiration (FNA) is considered an excellent technique for documenting metastatic neuroendocrine tumors (NETs). This study aims to evaluate the accuracy of FNA in diagnosing metastatic NETs to the liver and determining the grade and origin of these metastases. Methods Our laboratory information system was searched from 1997 to 2016 to identify all cases of metastatic NETs to the liver that were sampled by FNA. The cytopathology and surgical pathology reports as well as the patients' electronic medical records were reviewed. The cytohistologic type and grade of the metastatic NETs, as well as the site of the patient's primary were recorded. Results High‐grade NETs, including small cell and poorly differentiated neuroendocrine carcinomas, constituted 62% (167/271) of the cases, while low‐grade NETs, including well differentiated NET (grade1 and grade 2), pheochromocytomas, paragangliomas, and carcinoid tumors of lung, constituted 38% (104/271) of cases. The most common diagnosis was metastatic small cell carcinoma accounting for 45% (122/271) of cases. The most common primary sites were lung (44%; 119/271) followed by pancreas (19%; 51/271). The FNA diagnosis was confirmed by histopathology in 121 cases that had a concurrent biopsies or resection specimens. Conclusions FNA is an accurate method for diagnosing metastatic NETs to the liver. There were significantly more high‐grade (62%) than low‐grade (38%) metastatic NETs to the liver. In our practice, lung (44%) and pancreas (19%) were the most common primary sites of metastatic NETs involving the liver. In 16% of the cases, a primary site could not be established

Lubrication in Chemical and Mechanical Planarization

Chemical mechanical planarization (CMP) has been widely used in integrated circuit (IC) processing to achieve both local and global surface planarity through combined chemical and mechanical actions. The lubrication plays a significant role in CMP and can be determined by the Stribeck curve since it provides direct evidence of the extent of contact among wafer, pad asperities, and slurry particles. The advancements in the construction of the Stribeck curve are highlighted in this chapter. Traditionally, the procedure for constructing the Stribeck curve is as follows: (1) polish wafers at various pressures and sliding velocities to obtain the coefficient of friction (COF) values; (2) plot the experimental data as COF vs. Sommerfeld number; (3) construct the Stribeck curve via curve fitting. Recently, an alternative method was presented to construct the Stribeck curve via only performing one wafer polishing experiment. Pressure and sliding velocity are varied separately or together for a desired length of time, so that multiple measurements can be taken within one run. In this study, a back-propagation (BP) neural network is proposed to construct the Stribeck curve. Results show that the BP neural network could construct a more accurate Stribeck curve and thus could better provide insight into the lubrication mechanism of CMP processes

Full Hydrodynamic Model of Nonlinear Electromagnetic Response in Metallic Metamaterials

Applications of metallic metamaterials have generated significant interest in recent years. Electromagnetic behavior of metamaterials in the optical range is usually characterized by a local-linear response. In this article, we develop a finite-difference time-domain (FDTD) solution of the hydrodynamic model that describes a free electron gas in metals. Extending beyond the local-linear response, the hydrodynamic model enables numerical investigation of nonlocal and nonlinear interactions between electromagnetic waves and metallic metamaterials. By explicitly imposing the current continuity constraint, the proposed model is solved in a self-consistent manner. Charge, energy and angular momentum conservation laws of high-order harmonic generation have been demonstrated for the first time by the Maxwell-hydrodynamic FDTD model. The model yields nonlinear optical responses for complex metallic metamaterials irradiated by a variety of waveforms. Consequently, the multiphysics model opens up unique opportunities for characterizing and designing nonlinear nanodevices.Comment: 11 pages, 14 figure

The Impact of Politeness in Bidding Descriptions on Hiring Decisions in Online Labor Markets

Due to the lack of face-to-face interactions in online labor market, employers often have to rely on bidding descriptions to assess the interpersonal aspects of freelancers. Since politeness is a potential indicator of one’s willingness and ability to facilitate cooperation, our study examines the impact of politeness in bidding descriptions on hiring decisions. Based on data collected from Freelancer.com, we differentiate the politeness of bidding descriptions with textual analysis. Surprisingly, our findings reveal that politeness in bidding descriptions is negatively associated with the probability of getting hired, and the association is negatively moderated by the capability of freelancers and the textual similarity of bidding descriptions. Specifically, the association is positive for incapable workers or unique bidding descriptions but becomes more negative for capable workers or bidding descriptions similar to others. The findings contribute novel insights on the contingent impact of politeness in bidding descriptions in online labor market

Achieving Minimum Coverage Breach under Bandwidth Constraints in Wireless Sensor Networks

This paper addresses the coverage breach problem in wireless sensor networks with limited bandwidths. In wireless sensor networks, sensor nodes are powered by batteries. To make efficient use of battery energy is critical to sensor network lifetimes. When targets are redundantly covered by multiple sensors, especially in stochastically deployed sensor networks, it is possible to save battery energy by organizing sensors into mutually exclusive subsets and alternatively activating only one subset at any time. Active nodes are responsible for sensing, computing and communicating. While the coverage of each subset is an important metric for sensor organization, the size of each subset also plays an important role in sensor network performance because when active sensors periodically send data to base stations, contention for channel access must be considered. The number of available channels imposes a limit on the cardinality of each subset. Coverage breach happens when a subset of sensors cannot completely cover all the targets. To make efficient use of both energy and bandwidth with a minimum coverage breach is the goal of sensor network design. This paper presents the minimum breach problem using a mathematical model, studies the computational complexity of the problem, and provides two approximate heuristics. Effects of increasing the number of channels and increasing the number of sensors on sensor network coverage are studied through numerical simulations. Overall, the simulation results reveal that when the number of sensors increases, network lifetimes can be improved without loss of network coverage if there is no bandwidth constraint; with bandwidth constraints, network lifetimes may be improved further at the cost of coverage breach

Attention Mechanism and Detection Box Information Based Real-time Multi-Object Vehicle Detection

Ensuring both the accuracy of vehicle target detection and meeting real-time requirements is crucial in traffic videos. The YOLOv5s target detection framework, known for its accuracy and efficiency, has attracted attention in academic circles. However, there are still some features that can be optimized. First of all, the detection subnet of the YOLOv5s framework cannot smoothly convert complex feature maps into relatively sparse target prediction boxes. To solve this, we integrate a self-attention-based gating mechanism into the detection subnet, forming the YOLOv5s-SAG network. Secondly, the loss function of CIoU used by YOLOv5s pays insufficient attention to the overlapping area of the detection frame, which can be used as metric for measuring target detection effectiveness. We add the loss term of area ratio to CIoU to further improve the modeling ability. Finally, the current multi-class Non-Maximum Suppression algorithm can cause high overlap of multi-class detection frames. To improve it, we propose a multi-class CS-NMS algorithm based on category suppression. Experimental results show an approximately 8% improvement in the mAP50 index on the UA-DETRAC dataset compared with YOLOv5s. The proposed algorithm also achieves better detection results compared to mainstream target detection algorithms and meets the real-time requirements of traffic video analysis