Visualization 1.mp4

A piece of music recorded by the common-path three-wavelength cavity length demodulation system

When Text is Not Enough: The Processing of Text and Illustration for Emerging Medical Technologies

Text and illustration are two common communication modalities that are used to facilitate public understanding of new medical technologies. However, little is known about how to effectively use text and illustrations in pairs. The effects of using different types of text and illustrations have not been clearly understood. We conducted three studies to examine the effects of displaying text (non-narrative versus narrative) and illustrations (syntactic versus semantic) as a pair on a number of important outcomes. Study 1 showed that when displayed as a pair in juxtaposition, different pairs of text and illustration did not vary uncertainty or attitudes but varied fear. Study 2 found that when displayed in sequential order, different pairs of text and illustrations caused different levels of risk perceptions but their effects on fear were not different. Study 3 replicated Studies 2 with an increased sample size and found both main and interaction effects of text and illustration types. Theoretical and practical implications were discussed.</p

Table_1_The Relationship Between Elevated Serum Uric Acid and Risk of Stroke in Adult: An Updated and Dose–Response Meta-Analysis.docx

Background: Uric acid (UA) is proposed as a potential risk factor for stroke in adult, yet the results from published studies are not generally accordant.Method: We included prospective studies that explored the relationship between serum UA (SUA) and strokes. In this study, strokes include ischemic stroke and hemorrhagic stroke, which consists of intracerebral hemorrhage and subarachnoid hemorrhage. The effect-size estimates were expressed as hazard ratio (HR) and 95% confidence interval (CI). Sensitivity and subgroup analyses were performed to assess the robustness of the pooled estimation and potential sources of heterogeneity between studies.Results: We meta-analyzed 19 prospective cohort articles, which involve 37,386 males and 31,163 females. Overall analyses results showed a significant association between a 1 mg/dl increase in high levels of SUA and the risk of total stroke (HR = 1.13; 95% CI: 1.09–1.18; P Conclusions: Our findings indicate that elevated SUA is a significant risk factor for adult stroke, both for ischemic stroke and hemorrhagic stroke, and especially in females.</p

Additional file 3: of A random walk-based method to identify driver genes by integrating the subcellular localization and variation frequency into bipartite graph

The results of GO and KEGG enrichment analysis in breast cancer. (XLSX 147 kb

Table_2_The Relationship Between Elevated Serum Uric Acid and Risk of Stroke in Adult: An Updated and Dose–Response Meta-Analysis.doc

Background: Uric acid (UA) is proposed as a potential risk factor for stroke in adult, yet the results from published studies are not generally accordant.Method: We included prospective studies that explored the relationship between serum UA (SUA) and strokes. In this study, strokes include ischemic stroke and hemorrhagic stroke, which consists of intracerebral hemorrhage and subarachnoid hemorrhage. The effect-size estimates were expressed as hazard ratio (HR) and 95% confidence interval (CI). Sensitivity and subgroup analyses were performed to assess the robustness of the pooled estimation and potential sources of heterogeneity between studies.Results: We meta-analyzed 19 prospective cohort articles, which involve 37,386 males and 31,163 females. Overall analyses results showed a significant association between a 1 mg/dl increase in high levels of SUA and the risk of total stroke (HR = 1.13; 95% CI: 1.09–1.18; P Conclusions: Our findings indicate that elevated SUA is a significant risk factor for adult stroke, both for ischemic stroke and hemorrhagic stroke, and especially in females.</p

Additional file 1: of A random walk-based method to identify driver genes by integrating the subcellular localization and variation frequency into bipartite graph

The results of prediction of known cancer genes for lung, breast and prostate cancer. (XLSX 13 kb

Additional file 2: of A random walk-based method to identify driver genes by integrating the subcellular localization and variation frequency into bipartite graph

The results of GO and KEGG enrichment analysis in lung cancer. (XLSX 114 kb

Extended log-normal method of moments for solving the population balance equation for Brownian coagulation

An extended log-normal method of moments (ELNMOM) is presented in this study for solving the population balance equation (PBE) for Brownian coagulation. The method is an extension of the log-normal method of moments (LNMOM) proposed by Lee in 1983. The ELNMOM uses the superposition of log-normal subdistributions to represent the size distribution. Unlike previous modal studies, the subdistributions are not independent modes but flexible components in this study and the closure of this method is achieved by introducing additional higher-order moment equations. Based on some simplifying assumptions, the ELNMOM is implemented with only four adjustable parameters for a preliminary exploration. The method is then validated by comparing the size distribution parameters predicted by this method with those predicted by the LNMOM and other numerical methods for Brownian coagulation in the continuum regime and the free-molecular regime. The results show that the ELNMOM more accurately predicts the total particle number concentration, the geometric standard deviation and the geometric mean particle volume than the LNMOM while not taking much more computation time. Copyright © 2019 American Association for Aerosol Research</p

Additional file 4: of A random walk-based method to identify driver genes by integrating the subcellular localization and variation frequency into bipartite graph

The results of GO and KEGG enrichment analysis in prostate cancer. (XLSX 112 kb

Computational distributed fiber-optic sensing

Ghost imaging allows image reconstruction by correlation measurements between a light beam that interacts with the object without spatial resolution and a spatially resolved light beam that never interacts with the object. The two light beams are copies of each other. Its computational version removes the requirement of a spatially resolved detector when the light intensity pattern is pre-known. Here, we exploit the temporal analogue of computational ghost imaging, and demonstrate a computational distributed fiber-optic sensing technique. Temporal images containing spatially distributed scattering information used for sensing purposes are retrieved through correlating the "integrated" backscattered light and the pre-known binary patterns. The sampling rate required for our technique is inversely proportional to the total time duration of a binary sequence, so that it can be significantly reduced compared to that of the traditional methods. Our experiments demonstrate a 3 orders of magnitude reduction in the sampling rate, offering great simplification and cost reduction in the distributed fiber-optic sensors