Creating interaction in online learning: a case study

This paper uses the case‐study method to examine detailed data related to student and tutor usage of an asynchronous discussion board as an interactive communication forum during a first‐semester associate degree course in applied psychology at the City University of Hong Kong. The paper identifies ‘what works’ in relation to discussion board use, demonstrating how students might gradually create an online community of their own, but only if prompted in a timely and appropriate way by the course structure. It also identifies three distinct phases in online interaction and suggests these might, to some extent, be mediated by assessment tasks

A Posteriori Risk Classification and Ratemaking with Random Effects in the Mixture-of-Experts Model

A well-designed framework for risk classification and ratemaking in automobile insurance is key to insurers' profitability and risk management, while also ensuring that policyholders are charged a fair premium according to their risk profile. In this paper, we propose to adapt a flexible regression model, called the Mixed LRMoE, to the problem of a posteriori risk classification and ratemaking, where policyholder-level random effects are incorporated to better infer their risk profile reflected by the claim history. We also develop a stochastic variational Expectation-Conditional-Maximization algorithm for estimating model parameters and inferring the posterior distribution of random effects, which is numerically efficient and scalable to large insurance portfolios. We then apply the Mixed LRMoE model to a real, multiyear automobile insurance dataset, where the proposed framework is shown to offer better fit to data and produce posterior premium which accurately reflects policyholders' claim history

Chinese Social Media Reaction to the MERS-Cov and Avian Influenza A (H7N9) Outbreaks

Background: As internet and social media use have skyrocketed, epidemiologists have begun to use online data such as Google query data and Twitter trends to track the activity levels of influenza and other infectious diseases. In China, Weibo is an extremely popular microblogging site that is equivalent to Twitter. Capitalizing on the wealth of public opinion data contained in posts on Weibo, this study used Weibo as a measure of the Chinese people’s reactions to two different outbreaks: the 2012 Middle East Respiratory Syndrome Coronavirus (MERS-CoV) outbreak, and the 2013 outbreak of human infection of avian influenza A(H7N9) in China. Methods: Keyword searches were performed in Weibo data collected by The University of Hong Kong’s Weiboscope project. Baseline values were determined for each keyword and reaction values per million posts in the days after outbreak information was released to the public. Results: The results show that the Chinese people reacted significantly to both outbreaks online, where their social media reaction was two orders of magnitude stronger to the H7N9 influenza outbreak that happened in China than the MERS-CoV outbreak that was far away from China. Conclusions: These results demonstrate that social media could be a useful measure of public awareness and reaction to disease outbreak information released by health authorities

Rare ligamentum flavum cyst causing incapacitating lumbar spinal stenosis: Experience with 3 Chinese patients

Three Chinese patients suffered from severe lumbar spinal stenosis with debilitating symptoms due to a rare condition of ligamentum flavum cysts in the midline of the lumbar spine. This disease is distinct from synovial cyst of the facet joints or ganglion cysts, both intraoperatively and histopathologically. Magnetic Resonance imaging features of the ligamentum flavum cyst are also demonstrated. We share our surgical experiences of identification of the ligamentum flavum cysts, decompression and excision for two of the patients with demonstrably good recovery. This disease should be considered in the differential diagnosis of an extradural instraspinal mass in patients with lumbar spinal stenosis

How did Ebola information spread on twitter : broadcasting or viral spreading?

BACKGROUND: Information and emotions towards public health issues could spread widely through online social networks. Although aggregate metrics on the volume of information diffusion are available, we know little about how information spreads on online social networks. Health information could be transmitted from one to many (i.e. broadcasting) or from a chain of individual to individual (i.e. viral spreading). The aim of this study is to examine the spreading pattern of Ebola information on Twitter and identify influential users regarding Ebola messages. METHODS: Our data was purchased from GNIP. We obtained all Ebola-related tweets posted globally from March 23, 2014 to May 31, 2015. We reconstructed Ebola-related retweeting paths based on Twitter content and the follower-followee relationships. Social network analysis was performed to investigate retweeting patterns. In addition to describing the diffusion structures, we classify users in the network into four categories (i.e., influential user, hidden influential user, disseminator, common user) based on following and retweeting patterns. RESULTS: On average, 91% of the retweets were directly retweeted from the initial message. Moreover, 47.5% of the retweeting paths of the original tweets had a depth of 1 (i.e., from the seed user to its immediate followers). These observations suggested that the broadcasting was more pervasive than viral spreading. We found that influential users and hidden influential users triggered more retweets than disseminators and common users. Disseminators and common users relied more on the viral model for spreading information beyond their immediate followers via influential and hidden influential users. CONCLUSIONS: Broadcasting was the dominant mechanism of information diffusion of a major health event on Twitter. It suggests that public health communicators can work beneficially with influential and hidden influential users to get the message across, because influential and hidden influential users can reach more people that are not following the public health Twitter accounts. Although both influential users and hidden influential users can trigger many retweets, recognizing and using the hidden influential users as the source of information could potentially be a cost-effective communication strategy for public health promotion. However, challenges remain due to uncertain credibility of these hidden influential users

Efficacy, safety and immunogenicity of a human rotavirus vaccine (RIX4414) in Hong Kong children up to three years of age: A randomized, controlled trial

AbstractBackgroundA phase III, double-blind, randomized, controlled trial was conducted in Hong Kong to evaluate the efficacy, safety and immunogenicity of a human rotavirus vaccine, RIX4414 (Rotarix™) against severe rotavirus gastroenteritis in children up to three years of age.MethodsHealthy infants aged 6–12 weeks were enrolled between 08-December-2003 and 31-August-2005 and received two oral doses of either RIX4414 vaccine (N=1513) or placebo (N=1512) given 2 months apart. Vaccine efficacy was assessed from two weeks post-Dose 2 until the children were two and three years of age. Anti-rotavirus IgA seroconversion rate was calculated pre-vaccination and 1–2 months post-Dose 2 using ELISA (cut-off=20U/mL) for 100 infants. Safety was assessed until the children were two years of age; serious adverse events (SAEs) were recorded throughout the study period.ResultsIn children aged two and three years of life, vaccine efficacy against severe rotavirus gastroenteritis was 95.6% (95% CI: 73.1%–99.9%) and 96.1% (95% CI: 76.5%–99.9%), respectively. The seroconversion rate 1–2 months after the second dose of RIX4414 was 97.5% (95% CI: 86.8%–99.9%). At least one SAE was recorded in 439 and 477 infants who were administered RIX4414 and placebo, respectively (p-value=0.130). Six intussusception cases were reported (RIX4414=4; placebo=2) and none was assessed to be vaccine-related.ConclusionRIX4414 was efficacious, immunogenic and safe in the prevention of rotavirus gastroenteritis for at least two years post-vaccination in Hong Kong children

The central role of natural killer cells in mediating acute myocarditis after mRNA COVID-19 vaccination

BACKGROUND: Vaccine-related acute myocarditis is recognized as a rare and specific vaccine complication following mRNA-based COVID-19 vaccinations. The precise mechanisms remain unclear. We hypothesized that natural killer (NK) cells play a central role in its pathogenesis. METHODS: Samples from 60 adolescents with vaccine-related myocarditis were analyzed, including pro-inflammatory cytokines, cardiac troponin T, genotyping, and immunophenotyping of the corresponding activation subsets of NK cells, monocytes, and T cells. Results were compared with samples from 10 vaccinated individuals without myocarditis and 10 healthy controls. FINDINGS: Phenotypically, high levels of serum cytokines pivotal for NK cells, including interleukin-1β (IL-1β), interferon α2 (IFN-α2), IL-12, and IFN-γ, were observed in post-vaccination patients with myocarditis, who also had high percentage of CD57 NK cells in blood, which in turn correlated positively with elevated levels of cardiac troponin T. Abundance of the CD57 NK subset was particularly prominent in males and in those after the second dose of vaccination. Genotypically, killer cell immunoglobulin-like receptor (KIR) KIR2DL5B(-)/KIR2DS3(+)/KIR2DS5(-)/KIR2DS4del(+) was a risk haplotype, in addition to single-nucleotide polymorphisms related to the NK cell-specific expression quantitative trait loci DNAM-1 and FuT11, which also correlated with cardiac troponin T levels in post-vaccination patients with myocarditis. CONCLUSION: Collectively, these data suggest that NK cell activation by mRNA COVID-19 vaccine contributed to the pathogenesis of acute myocarditis in genetically and epidemiologically vulnerable subjects