Circuits, Perfect Matchings and Paths in Graphs

We primarily consider the problem of finding a family of circuits to cover a bidgeless graph (mainly on cubic graph) with respect to a given weight function defined on the edge set. The first chapter of this thesis is going to cover all basic concepts and notations will be used and a survey of this topic.;In Chapter two, we shall pay our attention to the Strong Circuit Double Cover Conjecture (SCDC Conjecture). This conjecture was verified for some graphs with special structure. As the complement of two factor in cubic graph, the Berge-Fulkersen Conjecture was introduced right after SCDC Conjecture. In Chapter three, we shall present a series of conjectures related to perfect matching covering and point out their relationship.;In last chapter, we shall introduce the saturation number, in contrast to extremal number (or known as Turan Number), and describe the edge spectrum of saturation number for small paths, where the spectrum was consisted of all possible integers between saturation number and Turan number

Effect of oteracil in combination with gimeracil on longterm survival and postoperative complications in elderly patients undergoing radical surgery for biliary tract cancer

Purpose: To investigate the effect of oteracil (Oxo) in combination with gimeracil (CDHP) on long-term survival and postoperative complications in elderly patients undergoing radical surgery for biliary tract cancer (BTC).Methods: Clinical data for 70 patients who underwent radical surgery for BTC in the Oncology Department of the Changle People’s Hospital, Weifang, China from April 2017 to April 2018 were collected. The patients were equally assigned to group A and group B, based on odd or even hospitalization number. After surgery, patients in group A received the combination of Oxo and CDHP, while group B patients received gemcitabine only. Long-term survival and incidence of adverse reactions were compared.Results: Compared with group B, group A had higher total treatment effectiveness (p < 0.05), lower clinical indices (p < 0.05), lower BPI score (p < 0.001) and higher 3-year overall survival (p < 0.05).Conclusion: Combined use of oteracil and gimeracil significantly prolongs the survival time and reduce cancer pain in BTC patients, with minimal toxic and side effects. However, further clinical trials are required prior to application in clinical practice.&nbsp

Why It Takes So Long to Connect to a WiFi Access Point

Today's WiFi networks deliver a large fraction of traffic. However, the performance and quality of WiFi networks are still far from satisfactory. Among many popular quality metrics (throughput, latency), the probability of successfully connecting to WiFi APs and the time cost of the WiFi connection set-up process are the two of the most critical metrics that affect WiFi users' experience. To understand the WiFi connection set-up process in real-world settings, we carry out measurement studies on $5$ million mobile users from $4$ representative cities associating with $7$ million APs in $0.4$ billion WiFi sessions, collected from a mobile "WiFi Manager" App that tops the Android/iOS App market. To the best of our knowledge, we are the first to do such large scale study on: how large the WiFi connection set-up time cost is, what factors affect the WiFi connection set-up process, and what can be done to reduce the WiFi connection set-up time cost. Based on the measurement analysis, we develop a machine learning based AP selection strategy that can significantly improve WiFi connection set-up performance, against the conventional strategy purely based on signal strength, by reducing the connection set-up failures from $33\%$ to $3.6\%$ and reducing $80\%$ time costs of the connection set-up processes by more than $10$ times.Comment: 11pages, conferenc

Is environmental tax legislation effective for pollution abatement in emerging economies? Evidence from China

This study estimates the effect of environmental tax legislation on air pollution, using the implementation of China’s Environmental Protection Tax Law (EPTL) as a quasi-natural experiment. For cities which have been authorized to raise tax rates by the EPTL, the air quality index (AQI) is 2.36 lower after the reform. The effect is reinforced in cities with stricter tax enforcement, lower fiscal stress, as well as higher initial pollution levels. Heterogeneity analyses show that the reform is more effective in cities with lower levels of marketization and legalization, as well as in developed cities. In addition, the impact of the reform is more significant in cities with higher levels of public participation in environmental governance, higher tax competition levels, and higher share of secondary industry. A series of robustness tests corroborates the results. This paper provides evidence that environmental tax legislation is efficacious in pollution abatement for developing economies

Scalable Platform for Batch Fabrication of Micro/Nano Devices on Engineering Substrates of Arbitrary Shapes and Sizes

AbstractSilicon wafers with standard sizes and shapes have served as the batch fabrication platform for microfabrication of micro/nano devices for decades. However, there is a strong demand to batch fabricate micro/nano devices on other engineering materials (e.g. titanium, stainless steel, diamond, and ceramics) of complicate shapes and sizes designed for important applications. Unfortunately it is extremely difficult to meet the demand due to various challenges involved during microfabrication. Here we present a novel batch fabrication platform which can be used to facilitate the batch fabrication of thin film devices on substrates with arbitrary shapes and sizes. This platform will eliminate photolithography related defects such as edge bead formation, which will enable fabrication of thin film devices at the edges/corners of arbitrary shaped and sized substrates. At the same time it will enable uniform and bulk polishing of these substrates. As a proof of concept, parallel/batch fabrication process was successfully applied and proved by fabricating thin film piezoelectric force sensors on polygonal shaped stainless steel plates

Lumen contour segmentation in ivoct based on n-type cnn

Automatic segmentation of lumen contour plays an important role in medical imaging and diagnosis, which is the first step towards the evaluation of morphology of vessels under analysis and the identification of possible atherosclerotic lesions. Meanwhile, quantitative information can only be obtained with segmentation, contributing to the appearance of novel methods which can be successfully applied to intravascular optical coherence tomography (IVOCT) images. This paper proposed a new end-to-end neural network (N-Net) for the automatic lumen segmentation, using multi-scale features based deep neural network, for IVOCT images. The architecture of the N-Net contains a multi-scale input layer, a N-type convolution network layer and a cross-entropy loss function. The multi-scale input layer in the proposed N-Net is designed to avoid the loss of information caused by pooling in traditional U-Net and also enriches the detailed information in each layer. The N-type convolutional network is proposed as the framework in the whole deep architecture. Finally, the loss function guarantees the degree of fidelity between the output of proposed method and the manually labeled output. In order to enlarge the training set, data augmentation is also introduced. We evaluated our method against loss, accuracy, recall, dice similarity coefficient, jaccard similarity coefficient and specificity. The experimental results presented in this paper demonstrate the superior performance of the proposed N-Net architecture, comparing to some existing networks, for enhancing the precision of automatic lumen segmentation and increasing the detailed information of edges of the vascular lumen

Intelligent Gearbox Diagnosis Methods Based on SVM, Wavelet Lifting and RBR

Given the problems in intelligent gearbox diagnosis methods, it is difficult to obtain the desired information and a large enough sample size to study; therefore, we propose the application of various methods for gearbox fault diagnosis, including wavelet lifting, a support vector machine (SVM) and rule-based reasoning (RBR). In a complex field environment, it is less likely for machines to have the same fault; moreover, the fault features can also vary. Therefore, a SVM could be used for the initial diagnosis. First, gearbox vibration signals were processed with wavelet packet decomposition, and the signal energy coefficients of each frequency band were extracted and used as input feature vectors in SVM for normal and faulty pattern recognition. Second, precision analysis using wavelet lifting could successfully filter out the noisy signals while maintaining the impulse characteristics of the fault; thus effectively extracting the fault frequency of the machine. Lastly, the knowledge base was built based on the field rules summarized by experts to identify the detailed fault type. Results have shown that SVM is a powerful tool to accomplish gearbox fault pattern recognition when the sample size is small, whereas the wavelet lifting scheme can effectively extract fault features, and rule-based reasoning can be used to identify the detailed fault type. Therefore, a method that combines SVM, wavelet lifting and rule-based reasoning ensures effective gearbox fault diagnosis