An Analysis of Tzu Chi’s Public Communication Campaign on Body Donation

Since the 1996 establishment of the Tzu Chi Body Donation Center, located at the Medical School of Tzu Chi University, campaigning for body donation has become one of Tzu Chi’s on-going endeavors. By 2004, the Center has successfully secured more than 430 bodies and more than 14,000 pledges that outnumber all other medical schools in Taiwan. Why is it that the campaign messages could draw such an overwhelming response from the public, especially since the use of one’s body after death is taboo in traditional Chinese belief? It is the purpose of this paper to examine the communication efforts of Tzu Chi’s body donation campaign. In order to achieve this goal, McGuire’s (2001) public communication model is used as the basis of the analysis in this study, which includes five components: (1) source, (2) message, (3) channel, (4) audience, and (5) destination. Limitations and directions for future research are discussed as well. [China Media Research. 2008; 4(1): 56-61

An Examination Of Online Social Networks Properties With Tie-Strength

In the past, most researchers focused on the efficacy of tie-strength in various applications for both online and offline social networks. However, how tie-strength can help in the analysis of online social networks was a commonly neglected issue. The massive size and recording properties of online social networks offer the possibility to measure tie-strength objectively. In this study, we examine a social network extracted from a blog network. We then propose a tie-strength measurement and investigate several properties of the network using the tie-strength we defined. We also study how tie-strength plays a role in these properties

Online platform for applying space–time scan statistics for prospectively detecting emerging hot spots of dengue fever

Abstract Background Cases of dengue fever have increased in areas of Southeast Asia in recent years. Taiwan hit a record-high 42,856 cases in 2015, with the majority in southern Tainan and Kaohsiung Cities. Leveraging spatial statistics and geo-visualization techniques, we aim to design an online analytical tool for local public health workers to prospectively identify ongoing hot spots of dengue fever weekly at the village level. Methods A total of 57,516 confirmed cases of dengue fever in 2014 and 2015 were obtained from the Taiwan Centers for Disease Control (TCDC). Incorporating demographic information as covariates with cumulative cases (365 days) in a discrete Poisson model, we iteratively applied space–time scan statistics by SaTScan software to detect the currently active cluster of dengue fever (reported as relative risk) in each village of Tainan and Kaohsiung every week. A village with a relative risk >1 and p value <0.05 was identified as a dengue-epidemic area. Assuming an ongoing transmission might continuously spread for two consecutive weeks, we estimated the sensitivity and specificity for detecting outbreaks by comparing the scan-based classification (dengue-epidemic vs. dengue-free village) with the true cumulative case numbers from the TCDC’s surveillance statistics. Results Among the 1648 villages in Tainan and Kaohsiung, the overall sensitivity for detecting outbreaks increases as case numbers grow in a total of 92 weekly simulations. The specificity for detecting outbreaks behaves inversely, compared to the sensitivity. On average, the mean sensitivity and specificity of 2-week hot spot detection were 0.615 and 0.891 respectively (p value <0.001) for the covariate adjustment model, as the maximum spatial and temporal windows were specified as 50% of the total population at risk and 28 days. Dengue-epidemic villages were visualized and explored in an interactive map. Conclusions We designed an online analytical tool for front-line public health workers to prospectively detect ongoing dengue fever transmission on a weekly basis at the village level by using the routine surveillance data

Minimally invasive strategy for gynecologic cancer with solitary periacetabular metastasis

SummaryTumor with bone metastases to the periacetabulum is rare, and its surgical management is challenging. Instead of wide excision with reconstruction of the hip joint, we used a relatively noninvasive method to manage periacetabular metastasis. Such a procedure for this condition has the benefits of short surgical time, less bleeding, and fewer complications during surgery. Our surgical management of the case reported here included curettage, phenol cauterization and filling of cisplatin-loaded cement in order to reduce local recurrence. After following-up for 2 years, there was no local recurrence and disease progression

Accelerated colorimetric immunosensingusing surface-modified porous monolithsand gold nanoparticles

A rapid and sensitive immunoassay platform integrating polymerized monoliths and gold nanoparticles (AuNPs) has been developed. The porous monoliths are photopolymerized in situ within a silica capillary and serve as solid support for high-mass transport and high-density capture antibody immobilization to create a shorter diffusion length for antibody–antigen interactions, resulting in a rapid assay and low reagent consumption. AuNPs are modified with detection antibodies and are utilized as signals for colorimetric immunoassays without the need for enzyme, substrate and sophisticated equipment for quantitative measurements. This platform has been verified by performing a human IgG sandwich immunoassay with a detection limit of 0.1 ng ml−1. In addition, a single assay can be completed in 1 h, which is more efficient than traditional immunoassays that require several hours to complete

A Study of Machine Learning Models in Epidemic Surveillance: Using the Query Logs of Search Engines

Epidemics inevitably result in a large number of deaths and always cause considerable social and economic damage. Epidemic surveillance has thus become an important healthcare research issue. In 2009, Ginsberg et al. observed that the query logs of search engines can be used to estimate the status of epidemics in a timely manner. In this paper, we model epidemic surveillance as a classification problem and employ query statistics from Google to classify the status of a dengue fever epidemic. The query logs of twenty-three dengue-related keywords serve as observations for machine learning and testing, and a number of machine learning models are investigated to evaluate their surveillance performance. Evaluations based on a 5-year real world dataset demonstrate that search engine query logs can be used to construct accurate epidemic status classifiers. Moreover, the learned classifiers generally outperform conventional regression approaches. We also apply various machine learning models, including generative, discriminative, sequential, and non-sequential classification models, to demonstrate their applicability to epidemic surveillance

Liquid biopsy genotyping in lung cancer: ready for clinical utility?

Liquid biopsy is a blood test that detects evidence of cancer cells or tumor DNA in the circulation. Despite complicated collection methods and the requirement for technique-dependent platforms, it has generated substantial interest due, in part, to its potential to detect driver oncogenes such as epidermal growth factor receptor (EGFR) mutants in lung cancer. This technology is advancing rapidly and is being incorporated into numerous EGFR tyrosine kinase inhibitor (EGFR-TKI) development programs. It appears ready for integration into clinical care. Recent studies have demonstrated that biological fluids such as saliva and urine can also be used for detecting EGFR mutant DNA through application other user-friendly techniques. This review focuses on the clinical application of liquid biopsies to lung cancer genotyping, including EGFR and other targets of genotype-directed therapy and compares multiple platforms used for liquid biopsy