Evaluation of edge detection algorithm of frontal image of facial contour in plastic surgery

With the improvement of medical levels and the continuous improvement of people’s living standards, the demand for beauty by the general public is increasing. The plastic surgery industry has also developed by leaps and bounds. People’s dissatisfaction with their own facial appearance, facial injuries and some other reasons have prompted people to carry out facial reconstruction, and facial plastic surgery has developed rapidly. However, in the current facial plastic surgery, the edge detection effect on the contour image is general. In order to improve the edge detection effect of facial contour lines in medical images, this paper proposed a facial contour line generation algorithm. First, the detection effects of four operators were compared. After comparing the effects, the Sobel operator was used as the input data to generate an edge detection algorithm. Then, the grayscale features of the tissue in the image and the symmetry of the image were used to perform bidirectional contour tracking on the detected image to extract facial contour lines. In addition, for facial contour features, the midpoint method can be used to generate auxiliary contours. The algorithm was verified by a set of facial CT (Computed Tomography) images in the experiment. The results showed that the new generation algorithm accelerated the edge detection speed, had good denoising performance, and enhanced the edge detection effect by about 12.05% compared with the traditional edge detection algorithm. The validity and practicability of facial edge detection were verified, and it provided a theoretical basis for further realizing the design of a facial contour digital image processing system

What explains Alibaba’s miraculous IPO success on the New York Stock Exchange?

Funding This work was supported by the Natural Science Foundation of China under Grant 72173036; the Natural Science Foundation of Hainan Province under Grant 721RC515. The authors are solely responsible for any error or omission herein. Funding Information: This work was supported by the National Natural Science Foundation of China under Grant 72173036; the Natural Science Foundation of Hainan Province under Grant 721RC515. The authors are solely responsible for any error or omission herein. Publisher Copyright: © 2022 Informa UK Limited, trading as Taylor & Francis Group.Peer reviewe

Is cloud computing the digital solution to the future of banking?

Acknowledgment: We express our thanks to the editors and anonymous referees for their constructive comments and suggestions, which have helped us significantly improve this paper. We have benefitted from discussions with colleagues and participants of different seminars/workshops in China and the UK. All remaining errors are our own. This research is financially supported by the Natural Science Foundation of China (72173036, 71973148) and the Chinese National Funding of Social Sciences (19CJY065).Peer reviewedPublisher PD

Build A Multi-Dimensional Collaborative Logistics Talent Training Model -Taking Chengdu University of Information Technology as an example

The “Opinions of the Ministry of Education on Accelerating the Construction of High-level Undergraduate Education to Comprehensively Improve the Ability of Talent Training (Jiao Gao [2018] No. 2)” clearly requires that the formation of a high-level undergraduate talent training system should be accelerated around the overall improvement of talent training capabilities. After 18 years of development, the logistics major of our school has made certain achievements in professional construction, teacher team construction, teacher teaching ability construction and experimental teaching guarantee construction, forming a relatively complete talent training system, but the social adaptation of talent training Sex still needs to be improved. This paper adheres to the problem orientation, based on the concept of collaborative education, and builds a multi-dimensional collaborative education talent training model from multiple perspectives, such as promoting the integration of production and education, condensing professional characteristics, implementing segmented training and building a capacity improvement system, and comprehensively improving the ability of logistics personnel training

Energy trading and pricing in microgrids with uncertain energy supply:A three-stage hierarchical game approach

This paper studies an energy trading and pricing problem for microgrids with uncertain energy supply. The energy provider with the renewable energy (RE) generation (wind power) determines the energy purchase from the electricity markets and the pricing strategy for consumers to maximize its profit, and then the consumers determine their energy demands to maximize their payoffs. The hierarchical game is established between the energy provider and the consumers. The energy provider is the leader and the consumers are the followers in the hierarchical game. We consider two types of consumers according to their response to the price, i.e., the price-taking consumers and the price-anticipating consumers. We derive the equilibrium point of the hierarchical game through the backward induction method. Comparing the two types of consumers, we study the influence of the types of consumers on the equilibrium point. In particular, the uncertainty of the energy supply from the energy provider is considered. Simulation results show that the energy provider can obtain more profit using the proposed decision-making scheme

Polymorphism Profile of Nine Short Tandem Repeat Loci in the Han Chinese

Nine short tandem repeat (STR) markers (D3S1358, VWA, FGA, THO1, TPOX, CSFIPO, D5S818, D13S317, and D7S820) and a sex-identification marker (Amelogenin locus) were amplified with multiplex PCR and were genotyped with a four-color fluorescence method in samples from 174 unrelated Han individuals in North China. The allele frequencies, genotype frequencies, heterozygosity, probability of discrimination powers, probability of paternity exclusion and Hardy-Weinberg equilibrium expectations were determined. The results demonstrated that the genotypes at all these STR loci in Han population conform to Hardy-Weinberg equilibrium expectations. The combined discrimination power (DP) was 1.05×10−10 within nine STR loci analyzed and the probability of paternity exclusion (EPP) was 0.9998. The results indicate that these nine STR loci and the Amelogenin locus are useful markers for human identification, paternity and maternity testing and sex determination in forensic sciences

Identifying interacting genetic variations by fish-swarm logic regression

Understanding associations between genotypes and complex traits is a fundamental problem in human genetics. A major open problem in mapping phenotypes is that of identifying a set of interacting genetic variants, which might contribute to complex traits. Logic regression (LR) is a powerful multivariant association tool. Several LR-based approaches have been successfully applied to different datasets. However, these approaches are not adequate with regard to accuracy and efficiency. In this paper, we propose a new LR-based approach, called fish-swarm logic regression (FSLR), which improves the logic regression process by incorporating swarm optimization. In our approach, a school of fish agents are conducted in parallel. Each fish agent holds a regression model, while the school searches for better models through various preset behaviors. A swarm algorithm improves the accuracy and the efficiency by speeding up the convergence and preventing it from dropping into local optimums. We apply our approach on a real screening dataset and a series of simulation scenarios. Compared to three existing LR-based approaches, our approach outperforms them by having lower type I and type II error rates, being able to identify more preset causal sites, and performing at faster speeds

Past, present, and future of gastrointestinal microbiota research in cats

The relationship between microbial community and host has profound effects on the health of animals. A balanced gastrointestinal (GI) microbial population provides nutritional and metabolic benefits to its host, regulates the immune system and various signaling molecules, protects the intestine from pathogen invasion, and promotes a healthy intestinal structure and an optimal intestinal function. With the fast development of next-generation sequencing, molecular techniques have become standard tools for microbiota research, having been used to demonstrate the complex intestinal ecosystem. Similarly to other mammals, the vast majority of GI microbiota in cats (over 99%) is composed of the predominant bacterial phylaFirmicutes,Bacteroidetes,Actinobacteria, andProteobacteria. Many nutritional and clinical studies have shown that cats' microbiota can be affected by several different factors including body condition, age, diet, and inflammatory diseases. All these factors have different size effects, and some of these may be very minor, and it is currently unknown how important these are. Further research is needed to determine the functional variations in the microbiome in disease states and in response to environmental and/or dietary modulations. Additionally, further studies are also needed to explain the intricate relationship between GI microbiota and the genetics and immunity of its host. This review summarizes past and present knowledge of the feline GI microbiota and looks into the future possibilities and challenges of the field

Novel Implications of Exosomes and lncRNAs in the Diagnosis and Treatment of Pancreatic Cancer

Pancreatic cancer remains a leading cause of cancer-related deaths. Most patients are present with advanced stages of the disease at the time of diagnosis; thus, surgery, which is the best curative option for this malignancy, is no longer an effective treatment modality for affected individuals. As a likely source of “liquid biopsies,” exosomes, which are secreted by fusing intracellular multivesicular bodies with cell membranes, have relative stability and composition, allowing them to cover the entire range of cancer-related biomarkers, including cellular proteins, lipids, DNA, RNA, miRNA, and long non-coding RNAs (lncRNAs). To explore the early detection biomarkers of pancreatic cancer and to develop successful therapeutic intervention for this disease, assessing the implications of exosomes in pancreatic cancer patients is essential. In this chapter, we wish to focus on the possibility of using exosomes and lncRNAs in the clinical management of patients with pancreatic cancer. We will discuss the mechanisms of tumor formation under the exosomal action, demonstrate how circulating exosomes and lncRNAs have come into the research spotlight as likely biomarkers of pancreatic cancer, and discuss the applications of exosomes as transfer vectors in tumor therapeutics