Some Sufficient Conditions for Graphs to Be (g, f, n)-Critical Graphs

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A Review of Intrusion Detection Technology Based on Deep Rein-forcement Learning

With the rapid development of modern science and technology, all kinds of network attacks are updated constantly. Therefore, the traditional network security defense mechanism needs to be further improved. Through extensive investigation, this paper presents the latest work of network intrusion detection technology based on deep learning. Firstly, this paper introduces the related concepts of network intrusion detection technology. On this basis, we further evaluate the performance of three common deep learning models in intrusion detection, and conclude that DBN algorithm has some strong advantages. Afterwards, it also puts forward several improvement strategies of intrusion detection models

DiffuseExpand: Expanding dataset for 2D medical image segmentation using diffusion models

Dataset expansion can effectively alleviate the problem of data scarcity for medical image segmentation, due to privacy concerns and labeling difficulties. However, existing expansion algorithms still face great challenges due to their inability of guaranteeing the diversity of synthesized images with paired segmentation masks. In recent years, Diffusion Probabilistic Models (DPMs) have shown powerful image synthesis performance, even better than Generative Adversarial Networks. Based on this insight, we propose an approach called DiffuseExpand for expanding datasets for 2D medical image segmentation using DPM, which first samples a variety of masks from Gaussian noise to ensure the diversity, and then synthesizes images to ensure the alignment of images and masks. After that, DiffuseExpand chooses high-quality samples to further enhance the effectiveness of data expansion. Our comparison and ablation experiments on COVID-19 and CGMH Pelvis datasets demonstrate the effectiveness of DiffuseExpand. Our code is released at https://anonymous.4open.science/r/DiffuseExpand.Comment: 10 pages, 5 figure

An Empirical Comparative Study on the Two Methods of Eliciting Singers’ Emotions in Singing: Self-Imagination and VR Training

Emotional singing can affect vocal performance and the audience’s engagement. Chinese universities use traditional training techniques for teaching theoretical and applied knowledge. Self-imagination is the predominant training method for emotional singing. Recently, virtual reality (VR) technologies have been applied in several fields for training purposes. In this empirical comparative study, a VR training task was implemented to elicit emotions from singers and further assist them with improving their emotional singing performance. The VR training method was compared against the traditional self-imagination method. By conducting a two-stage experiment, the two methods were compared in terms of emotions’ elicitation and emotional singing performance. In the first stage, electroencephalographic (EEG) data were collected from the subjects. In the second stage, self-rating reports and third-party teachers’ evaluations were collected. The EEG data were analyzed by adopting the max-relevance and min-redundancy algorithm for feature selection and the support vector machine (SVM) for emotion recognition. Based on the results of EEG emotion classification and subjective scale, VR can better elicit the positive, neutral, and negative emotional states from the singers than not using this technology (i.e., self-imagination). Furthermore, due to the improvement of emotional activation, VR brings the improvement of singing performance. The VR hence appears to be an effective approach that may improve and complement the available vocal music teaching methods

The influence of a ban on outpatient intravenous antibiotic therapy among the secondary and tertiary hospitals in China.

BACKGROUND: Antimicrobial resistance (AMR) is a serious global public health challenge. Physicians' over-prescription of antibiotics is a major contributor, and intravenous (IV) antibiotic use has been a particular concern in China. To address the rapid fallout of antibiotic overuse, the Chinese government has piloted a ban of IV antibiotics in the outpatient department (OD) with the exemption of paediatrics, emergency department (ED), and inpatient ward of secondary and tertiary hospitals in several provinces. METHODS: To assess the potential impact of the policy, we conducted a mixed-methods study including 1) interviews about the ban of IV antibiotic use with 68 stakeholders, covering patients, health workers, and policy-makers, from two cities and 2) a hospital case study which collected routine hospital data and survey data with 207 doctors. RESULTS: Our analyses revealed that the ban of IV antibiotics in the OD led to a reduction in the total and IV antibiotic prescriptions and improved the rational antibiotic prescribing practice in the OD. Nevertheless, the policy has diverted patient flow from OD to ED, inpatient ward, and primary care for IV antibiotic prescriptions. We also found that irrational antibiotic use in paediatrics was neglected. Radical policy implementation, doctors circumvented the regulations, and lack of doctor-patient communication during patient encounters were barriers to the implementation of the ban. CONCLUSIONS: Future efforts may include 1) to de-escalate both oral and IV antibiotic therapy in paediatric and reduce oral antibiotic therapy among adults in outpatient clinics, 2) to reduce unnecessary referrals by OD doctors to ED, primary care, or inpatient services and better coordinate for patients who clinically need IV antibiotics, 3) to incorporate demand-side tailored measures, such as public education campaigns, and 4) to improve doctor-patient communication. Future research is needed to understand how primary care and other community clinics implement the ban

Association of the CHRNA3 Locus with Lung Cancer Risk and Prognosis in Chinese Han Population

IntroductionRecent genome-wide association studies in Caucasians revealed association with lung cancer risk of single nucleotide polymorphisms (SNPs) in the locus containing two nicotine acetylcholine receptor CHRNA genes. However, the reported risk SNPs are extremely rare in Asians. This study sought to identify other variants on CHRNA3 associated with lung cancer susceptibility and to explore whether SNPs of CHRNA3 are of prognostic factors in patients with non-small cell lung cancer (NSCLC) in Chinese Han population.MethodsA case-control study of 529 cases and 567 controls was performed to study the association of three SNPs (rs3743076, rs3743078, and rs3743073) in CHRNA3 with lung cancer risk in Chinese Han population using logistic regression models. The relationship between CHRNA3 polymorphisms with overall survival among 122 patients with advanced stage (stage IIIb and IV) NSCLC were evaluated using Cox multiple model based on the International Association for the Study of Lung Cancer recommended tumor, node, metastasis new staging.ResultsPatients with genotypes TG or GG for the novel SNP rs3743073 in CHRNA3 gene, compared with those with TT, showed an increased risk of lung cancer (adjusted odds ratio = 1.91; 95% confidence interval, 1.38–2.63; p = 9.67 × 10−5) and worst survival (adjusted hazard ratio = 2.35; 95% confidence interval, 1.05–5.26; p = 0.04) in patients with advanced stage NSCLC based on International Association for the Study of Lung Cancer recommended tumor, node, metastasis new staging.ConclusionsThese results suggest that the rs3743073 polymorphism in CHRNA3 is predictive for lung cancer risk and prognostic in advanced stage NSCLC in Chinese Han population

Risk communication on behavioral responses during COVID-19 among general population in China: A rapid national study.

OBJECTIVES: To describe the risk perception and behavioral responses among Chinese adults and to assess the associations of risk communication, risk perception, and behavioral adherence during the COVID-19 epidemic. METHODS: A national cross-sectional survey was conducted in 31 provinces in China with a total number of 5039 effective questionnaires collected. The questionnaire included sociodemographic characteristics, COVID-19 risk communication factors, mask and soap supply, and engagement in preventive behaviors during the epidemic. Multivariable Logistic regression was used. RESULTS: An overwhelmingly high prevalence of Chinese people was exposed to COVID-19 related risk communication messages (86.5%) and an overwhelming majority of respondents reported engagement in preventive behaviors (88.3%). Exposed to risk communication messages were positively associated with engaging in preventive behaviors, whereas, believing in misinformation were negatively associated with wearing masks when in public (p < 0.01). Respondents encountered an inadequate supplies of personal protection materials were negatively associated with their outdoor hygiene behaviors. People who were male, in an older age group, minorities, with lower education, with lower income, and lived in rural area showed lower exposures to risk communication messages. CONCLUSIONS: Future risk communication practices are recommended to better monitor population risk perceptions and pay attention to socio-demographically disadvantaged people