With the progress of the Internet and information technology, emotion analysis has been applied to analyse the emotional orientation and evolution trend of online public opinion of online tweets. At ...present, most of the existing methods use econometric model and machine learning algorithm to predict the trend of online public opinion. Although these methods have achieved good prediction results, they do not take into account the influence of internal factors on network public opinion prediction, such as mutual migration among emotion classes. The emotion may change dynamically because different events trigger it in the evolution process. In this view, this article proposes a novel method, called Deviation Rule Markov Model (DRMM), to predict the emotional change trend of Internet users in online public opinion by analysing the correlation between Internet users’ emotional categories. Structurally, the proposed DRMM involves various processes such as pre-processing, emotion classification, data mining and transfer prediction. For the processing of network comment data, the proposed model initially undergoes pre-processing to delete unnecessary data. Then, the extended fuzzy emotion ontology is used to annotate the emotion class of the comment data. Besides, an extended association rule mining algorithm is used in the emotion association analysis process to obtain the transfer probability between emotion classes. Moreover, Markov chain is used to construct an emotional state transition matrix to predict the transition probability of positive or negative emotions. According to the predicted single emotion transfer probability results, the analytic hierarchy process is used to assign values to different emotion classes, and finally, the transfer probability of the overall emotion in a certain period is obtained. Compared with the actual case, the mean absolute error (MAE) and root mean square error (RMSE) of the proposed model are 2.7119 and 3.7254, respectively, which has good prediction performance.
IntroductionInfluenza is a major public health threat, and vaccination is the most effective prevention method. However, vaccination coverage remains suboptimal. Low health literacy regarding ...influenza vaccination may contribute to vaccine hesitancy. This study aims to evaluate the effect of health education interventions on influenza vaccination rates and health literacy.Methods and analysisThis cluster randomised controlled trial will enrol 3036 students in grades 4–5 from 20 primary schools in Dongguan City, China. Schools will be randomised to an intervention group receiving influenza vaccination health education or a control group receiving routine health education. The primary outcome is the influenza vaccination rate. Secondary outcomes include health literacy levels, influenza diagnosis rate, influenza-like illness incidence and vaccine protection rate. Data will be collected through questionnaires, influenza surveillance and self-reports at baseline and study conclusion.Ethics and disseminationEthical approval has been sought from the Ethics Committee of the School of Public Health, Sun Yat-sen University. Findings from the study will be made accessible to both peer-reviewed journals and key stakeholders.Trial registration numberNCT06048406.
Studies have investigated PAX1 and SEPT methylation were closely associated with cervical cancer. For this study, we verified the expressions of PAX1 and SEPT9 methylation in 236 hrHPV women cervical ...exfoliated cells by using quantitative methylation-specific PCR and we further explored their diagnostic value in cervical (pre)cancer detection. Our results identified that the methylation rates and levels of PAX1 and SEPT9 increased with cervical lesion severity. For a diagnosis of cervical (pre)cancer, the area under the curve (AUC) of PAX1 methylation was 0.77 (95% CI 0.71-0.83) and the AUC of SEPT9 methylation was 0.86 (95% CI 0.81∼0.90). Analyses of the PAX1 and SEPT9 methylation statuses alone or combined with commonly used tests can efficiently identify cervical (pre)cancer. In particular, SEPT9 methylation might serve as an effective and powerful biomarker for the diagnosis of cervical (pre)cancer and as an alternative triage test in HPV-based cervical (pre)cancer screening programs.
Impact Statement
What is already known on this subject? This subject showed that PAX1 and SEPT9 methylation were closely associated with cervical cancer. The methylation rates and levels of PAX1 and SEPT9 increased with cervical lesion severity and reached a peak in cervical cancer exfoliated cells. We further assessed the diagnostic performances of PAX1 and SEPT9 methylation in cervical cancer screening. In detecting cervical (pre)cancer, the sensitivity values of PAX1 and SEPT9 methylation were up to 61.18% and 82.35%, respectively, and the specificity values of PAX1 and SEPT9 methylation were up to 95.36% and 86.75%, respectively. Moreover, the ROC curve analysis showed AUC values of 0.77 for PAX1 methylation and 0.86 for SEPT9 methylation tests, which were significantly superior to other commonly used tests. These findings suggest that PAX1 and SEPT9 methylation detection may have great clinical potential in cervical cancer screening.
What the results of this study add? The rates and levels of PAX1 and SEPT9 methylation increased with the severity of the cervical lesions. For a diagnosis of cervical (pre)cancer, the area under the curve (AUC) of PAX1 methylation was 0.77 (95% CI 0.71-0.83), and the sensitivity and specificity values were 61.18% and 95.36%, respectively. The AUC value of the SEPT9 methylation was 0.86 (95% CI 0.81 ∼ 0.90), and the sensitivity and specificity values were 82.35% and 86.75%, respectively. Compared with the various tests we conducted, the PAX1 methylation showed the highest specificity (95.36%), and the SEPT9 methylation demonstrated the highest accuracy(86.00%).
What the implications are of these findings for clinical practice and/or further research? The methylation levels of PAX1 and SEPT9 had a certain predictive effect on the severity of cervical lesions in hrHPV-positive women. In addition, SEPT9 methylation analysis performs better than PAX1 methylation analysis and commonly used tests in cervical exfoliated cells for detecting cervical (pre)cancer in hrHPV-positive women. SEPT9 methylation analysis merits consideration as an effective and objective, alternative triage test in HPV-based cervical (pre)cancer screening programs.
With the introduction of many derivatives into the capital market, including stock index futures, the trading strategies in financial markets have been gradually enriched. However, there is still no ...theoretical model that can determine whether these strategies are effective, what the risks are, and how costly the strategies are. We built an agent-based cross-market platform that includes five stocks and one stock index future, and constructed an evaluation system for stock index futures trading strategies. The evaluation system includes four dimensions: effectiveness, risk, occupation of capital, and impact cost. The results show that the informed strategy performs well in all aspects. The risk of the technical strategy is relatively higher than that of the other strategies. Moreover, occupation of capital and impact cost are both higher for the arbitrage strategy. Finally, the wealth of noise traders is almost lost.
Aberrant Septin9 methylation in cervical cancer has been rarely studied. We aimed to identify its diagnostic value in cervical cancer using cervical scrapings, and its predictive potential in plasma ...for pelvic nodal metastasis of cervical cancer. The statuses of methylated Septin9 in fresh cervical lesions and cervical scrapings were first evaluated by using quantitative methylation-specific PCR. Subsequently, the relationship between Septin9 methylation in 113 plasma samples and pelvic nodal metastasis of cervical cancer was evaluated. Methylated Septin9 was detected in all cancerous tissues, but not in cervicitis. The degrees of Septin9 methylation increased with growing severity of cervical lesions in cervical scrapings. The sensitivity of methylated Septin9 was lower than that of cytology, while it yielded a high specificity and area under the curve in detecting high-grade squamous intraepithelial lesion or cervical cancer; and when Septin9 methylation combined with HPV16/18 genotyping, the sensitivity would increase from 70.42% to 82.39%. Plasma-based Septin9 methylation had a high discriminatory power in predicting pelvic nodal metastasis of cervical cancer, with an optimal specificity of 81.48%. In conclusion, we demonstrated methylated Septin9 to be an innovative diagnostic biomarker for cervical cancer and its non-invasive predictive potential in plasma for pelvic nodal metastasis of cervical cancer.
Impact statement
What is already known on this subject? The occurrence of cervical cancer is related to Septin9 methylation. In fresh specimens and cervical scrapings, we found the degrees of methylated Septin9 increased with growing severity of cervical lesions. Compared with HPV16/18 genotyping and cytological detection, Septin9 methylation had a better specificity and AUC in detecting ≥ HSIL. Furthermore, plasma-based Septin9 methylation also had a high specificity for pelvic lymphatic metastasis prediction.
What the results of this study add? Methylation analysis of Septin9 indicated a similar sensitivity, specificity and AUC in detecting ≥ HSIL, relative to HPV16/18 genotyping. Compared with cytological method, Septin9 methylation also yielded a higher specificity and AUC in detecting ≥ HSIL. And we also found plasma-based Septin9 methylation had a high discriminatory power in predicting pelvic nodal metastasis of cervical cancer, with an optimal specificity of 81.48%; additionally an increasing sensitivity from 50% to nearly 80% was found when combined with SCCAg.
What the implications are of these findings for clinical practice and/or further research? This study aimed to evaluate the relationship between Septin9 methylation and cervical cancer, and to explore the value of methylated Septin9 in the detection of cervical (pre)cancerous lesions. Moreover, we would explore plasma-based ctDNA biomarkers for pelvic lymphatic metastasis prediction of cervical cancer, to improve non-invasive predictive accuracy of pelvic nodal metastasis and reduce the complications caused by pelvic lymphadenectomy.
Sentiment analysis of microblogging texts can facilitate both organisations' public opinion monitoring and governments' response strategies development. Nevertheless, most of the existing analysis ...methods are conducted on Twitter, lacking of sentiment analysis of Chinese microblogging (Weibo), and they generally rely on a large number of manually annotated training or machine learning to perform sentiment classification, yielding with difficulties in application. This paper addresses these problems and employs a sentiment ontology model to examine sentiment analysis of Chinese microblogging. We conduct a sentiment analysis of all public microblogging posts about '7.23 Wenzhou Train Collision' broadcasted by Sina microblogging users between 23 July and 1 August 2011. For every day in this time period, we first extract eight dimensions of sentiment (expect, joy, love, surprise, anxiety, sorrow, angry, and hate), and then build fuzzy sentiment ontology based on HowNet and semantic similarity for sentiment analysis; we also establish computing methods of influence and sentiment of microblogging texts; and we finally explore the change of public sentiment after '7.23 Wenzhou Train Collision'. The results show that the established sentiment analysis method has excellent application, and the change of different emotional values can reflect the success or failure of guiding the public opinion by the government.
This paper has investigated the asymmetric relationship between carbon emission trading market and stock market in China by using the nonlinear auto-regressive distributed lag (NARDL) model. Based on ...our investigation on both of the overall and sector level of stock market, we have obtained interesting and convincing empirical results that show there are significantly negative long-run and short-run asymmetric relationships between carbon emission trading market and overall stock market in China. Specifically, we have noticed that while passing the effects from the former to the later, the increasing of carbon emission trading price would make greater effects on the stock price than its decreasing. Also, on the sector level, carbon emission trading price is significantly related to some energy intense sectors and financial sector stock market. Furthermore, we have surprisingly found out that there are no significant effects passing from stock index to carbon emission trading price in China, neither on the overall level nor on the sector level of stock market.
•Investigate asymmetric relationship between China carbon emission trading market and stock market by NARDL model•Carbon emission trading markets affect both overall and sector level of stock markets in China•Significantly negative long-run asymmetry is between overall stock market and carbon emission trading market•Carbon emission trading prices significantly relate with some energy intense sectors and financial sector stock market
Identifying and preventing the cross-market risk contagion is very important for the market stability. This paper uses a MODWT-Vine quantile regression method to study the dynamic dependence and risk ...contagion effects among the international oil market, the Chinese commodity market and the Chinese stock market under multiple time scales, thus bringing in more specific information by considering the influence of covariates. The empirical results show that for the original time scale, the positive correlation between oil and stock decreases with the impact of the Chinese commodity market. The spread of the risk from the international oil market to the Chinese commodity market is relatively stronger than that to the Chinese stock market when the influence of covariates is controlled. The Chinese commodity market shares the risk contagion of the international oil market to the Chinese stock market to a certain degree. Volatility spillovers within the Chinese market are stronger than oil market spillovers to the Chinese domestic market. Besides, the risk contagion is different on different investment levels, for instance, the risk in the Chinese stock market of the medium-term investment time scale of 2–32 days is more contagious than that of the short-term time scale of 1–2 days. Finally, the asymmetry of risk contagion across the discussed markets of oil, stock and commodity reveals the specific and important information about the sensitivity of the risk contagion.
•The risk contagion of oil spread to the Chinese commodity is relatively stronger than that to the Chinese stock.•The Chinese commodity shares the risk contagion of the international oil to the Chinese stock to a certain degree.•Volatility spillovers within the Chinese market are stronger than oil market spillovers to the Chinese domestic market.•The asymmetry of risk contagion across the markets reveals the important information about the sensitivity of the risk contagion.
Web Services that provide a real-time e-business solution via online binding of software components must have a mechanism to win users' confidence in the quality of service (QoS) to establish a solid ...foot holding in the market. Inspired by the trust third-party approach in the public key system, we explored the idea of expanding the role of registrars to include (1) assessing quality of Web Services and (2) syndicating Web Services. The Analytic Hierarchy Process (AHP) and the Brown–Gibson (BG) methods were adapted to facilitate quality assessment. An optimization model was proposed for Web Service syndication. A heuristic algorithm was developed to solve the NP-hard problem, and an experiment was conducted, with two sensitivity analyses involving adjusting parameters, to compare its performance and the optimal solutions.
This study examines the predictability of stock market implied volatility on stock volatility in five developed economies (the US, Japan, Germany, France, and the UK) using monthly volatility data ...for the period 2000 to 2017. We utilize a simple linear autoregressive model to capture predictive relationships between stock market implied volatility and stock volatility. Our in-sample results show there exists very significant Granger causality from stock market implied volatility to stock volatility. The out-of-sample results also indicate that stock market implied volatility is significantly more powerful for stock volatility than the oil price volatility in five developed economies.
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