Determination of Lysophosphatidic Acids by Capillary Electrophoresis with Indirect Ultraviolet Detection

Lysophosphatidic acid (LPA) is the simplest form of lysophospholipid. Molecular species of LPA have been identified as the potent components in the ovarian cancer activation factor. The elevated plasma LPAs may be used as potential biomarkers for the early detection of ovarian cancer. This paper is the first report on the quantitative analysis of molecular species of LPA using capillary electrophoresis. In this work, the separation of LPAs was achieved within 14 min in an adenosine monophosphate-borate–methanol–water solution, and the measurement was accomplished by indirect UV detection. With LPA (D) as internal standard, the method had linear calibration ranges for LPAs from 2.8 to 75 μM. The detection limits for various molecular species of LPA were from 1.2 to 2.3 μM by the pressure injection at 3.45 kPa for 5 s. The method had been applied to serum fortified with LPA (S), LPA (O), LPA (P), and LPA (M) and the recoveries ranged from 83 to 112%

Advances in Monte Carlo methods: exponentially tilted sequential proposal distributions and regenerative Markov chain samplers

Inference for Bayesian models often require one to simulate from some non-standard multivariate probability distributions. In the first part of the thesis, we successfully simulate exactly from certain Bayesian posteriors (the Tobit, the constrained linear regression, smoothing spline, and the Lasso) by applying rejection sampling using exponentially tilted sequential proposal distributions. This technique is typically efficient for posteriors which have the form of truncated multivariate normal/student. In this manner, we are able to simulate exactly from the posterior in hundreds of dimensions, which has until now being unattainable. Due to the curse of dimensionality, these rejection schemes are unfortunately bound to fail as the dimensions of the problems grow. In such cases, one ultimately has to resort to approximate MCMC schemes. It is known that the sampling error of a Markov chain can be a lot easier if we can identify the regeneration times for the Markov chain. In particular, the convergence rate of a geometrically ergodic Markov chain can be estimated if one can identify the underlying regeneration events. While the idea of using regeneration in the error analysis of MCMC is not new, our contribution in the second part of the thesis is to provide simpler estimates of the total variation error, and a new graphical diagnostic with strong theoretical justification. Finally, in the third part of the thesis, we consider the exponentially tilted sequential distributions in part one as proposal distributions for the MCMC samplers in part two. We introduce a novel Reject-Regenerate sampler, which combines the lessons learned about exact sampling and regenerative MCMC into a single framework. The resulting MCMC algorithm is a Markov chain with clearly demarcated regeneration events. Moreover, in the event of a regeneration, the Markov chain achieves a perfect draw with some probability

The Charisma of Online Group-Buying: The Moderating Role of Social Motivation

Group buying can spread worldwide because the growth of the online shopping market has been considerable. In addition to deal popularity and discount rate, social motivation was included in this study. If a consumer cannot achieve an economic exchange benefit, a social exchange benefit might provide another function for the group member to stay in the community. This study adopted convenience sampling and an online questionnaire to conduct a survey. Among 240 questionnaires collected, 204 were valid. According to ANOVA analysis, the results demonstrated that social motivation has a positive influence on the relationship between the discount of a product and customers 'purchasing intention but not on the relationship between the popularity of a product and customers' purchasing intention. Therefore, we concluded that strengthening social networking can have a positive effect on customers' purchasing intention and thus encouraging the development of group purchasing retailers and related industries

Optimisation- based time slot assignment and synchronisation for TDMA MAC in industrial wireless sensor network

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/166209/1/cmu2bf02232.pd

Fabrication and Performance of MEMS-Based Pressure Sensor Packages Using Patterned Ultra-Thick Photoresists

A novel plastic packaging of a piezoresistive pressure sensor using a patterned ultra-thick photoresist is experimentally and theoretically investigated. Two pressure sensor packages of the sacrifice-replacement and dam-ring type were used in this study. The characteristics of the packaged pressure sensors were investigated by using a finite-element (FE) model and experimental measurements. The results show that the thermal signal drift of the packaged pressure sensor with a small sensing-channel opening or with a thin silicon membrane for the dam-ring approach had a high packaging induced thermal stress, leading to a high temperature coefficient of span (TCO) response of −0.19% span/°C. The results also show that the thermal signal drift of the packaged pressure sensors with a large sensing-channel opening for sacrifice-replacement approach significantly reduced packaging induced thermal stress, and hence a low TCO response of −0.065% span/°C. However, the packaged pressure sensors of both the sacrifice-replacement and dam-ring type still met the specification −0.2% span/°C of the unpackaged pressure sensor. In addition, the size of proposed packages was 4 × 4 × 1.5 mm3 which was about seven times less than the commercialized packages. With the same packaging requirement, the proposed packaging approaches may provide an adequate solution for use in other open-cavity sensors, such as gas sensors, image sensors, and humidity sensors

Decreased Risk of Osteoporosis Incident in Subjects Receiving Chinese Herbal Medicine for Sjögren Syndrome Treatment: A Retrospective Cohort Study with a Nested Case-Control Analysis

Sjögren syndrome (SS) is a long-lasting inflammatory autoimmune disease that may cause diverse manifestations, particularly osteoporosis. Though usage of Chinese herbal medicine (CHM) can safely manage autoimmune disease and treatment-related symptoms, the relation between CHM use and osteoporosis risk in SS persons is not yet recognized. With that in mind, this population-level nested case-control study aimed to compare the risk of osteoporosis with and without CHM use. Potential subjects aged 20–70 years, diagnosed with SS between 2001 and 2010, were retrieved from a national health claims database. Those diagnosed with osteoporosis after SS were identified and randomly matched to those without osteoporosis. We capitalize on the conditional logistic regression to estimate osteoporosis risk following CHM use. A total of 1240 osteoporosis cases were detected and randomly matched to 1240 controls at a ratio of 1:1. Those receiving conventional care plus CHM had a substantially lower chance of osteoporosis than those without CHM. Prolonged use of CHM, especially for one year or more, markedly dwindled sequent osteoporosis risk by 71%. Integrating CHM into standard care may favor the improvement of bone function, but further well-designed randomized controlled trials to investigate the possible mechanism are needed