2 resultados para Measurement-based

em QSpace: Queen's University - Canada


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The purpose of this research is to investigate potential methods to produce an ion-exchange membrane that can be integrated directly into a polydimethylsiloxane Lab-on-a-Chip or Micro-Total-Analysis-System. The majority of microfluidic membranes are based on creating microporous structures, because it allows flexibility in the choice of material such that it can match the material of the microfluidic chip. This cohesion between the material of the microfluidic chip and membrane is an important feature to prevent bonding difficulties which can lead to leaking and other practical problems. However, of the materials commonly used to manufacture microfluidic chips, there are none that provide the ion-exchange capability. The DuPont product Nafion{TM} is chosen as the ion-exchange membrane, a copolymer with high conductivity and selectivity to cations and suitable for many applications such as electrolysis of water and the chlor-alkali process. The use of such an ion-exchange membrane in microfluidics could have multiple advantages, but there is no reversible/irreversible bonding that occurs between PDMS and Nafion{TM}. In this project multiple methods of physical entrapment of the ion-exchange material inside a film of PDMS are attempted. Through the use of the inherent properties of PDMS, very inexpensive sugar granulate can be used to make an inexpensive membrane mould which does not interfere with the PDMS crosslinking process. After dissolving away this sacrificial mould material, Nafion{TM} is solidified in the irregular granulate holes. Nafion{TM} in this membrane is confined in the irregular shape of the PDMS openings. The outer structure of the membrane is all PDMS and can be attached easily and securely to any PDMS-based microfluidic device through reversible or irreversible PDMS/PDMS bonding. Through impedance measurement, the effectiveness of these integrated membranes are compared against plain Nafion{TM} films in simple sodium chloride solutions.

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When we study the variables that a ffect survival time, we usually estimate their eff ects by the Cox regression model. In biomedical research, e ffects of the covariates are often modi ed by a biomarker variable. This leads to covariates-biomarker interactions. Here biomarker is an objective measurement of the patient characteristics at baseline. Liu et al. (2015) has built up a local partial likelihood bootstrap model to estimate and test this interaction e ffect of covariates and biomarker, but the R code developed by Liu et al. (2015) can only handle one variable and one interaction term and can not t the model with adjustment to nuisance variables. In this project, we expand the model to allow adjustment to nuisance variables, expand the R code to take any chosen interaction terms, and we set up many parameters for users to customize their research. We also build up an R package called "lplb" to integrate the complex computations into a simple interface. We conduct numerical simulation to show that the new method has excellent fi nite sample properties under both the null and alternative hypothesis. We also applied the method to analyze data from a prostate cancer clinical trial with acid phosphatase (AP) biomarker.