Formulation/cure technology for ultrahigh molecular weight silphenylene-siloxane polymers

Molecular weights above one million were achieved for methylvinylsilphenylene-siloxane terpolymers using a two-stage polymerization technique which was successfully scaled up to 200 grams. The resulting polymer was vulcanized by two different formulations and compared to an identically formulated commercial methylvinyl silicone on the basis of ultimate strength, Young's modulus, percent elongation at failure, and tear strength. Relative thermal/oxidative stabilities of the elastomers were assessed by gradient and isothermal thermogravimetric analyses performed in both air and nitrogen. The experimental elastomer exhibited enhanced thermal/oxidative stability and possed equivalent or superior mechanical properties. The effect of variations in prepolymer molecular weight on mechanical properties was also investigated

Ultra-high molecular weight silphenylene-siloxane polymers

Silphenylene-siloxane copolymers with molecular weights above one million were prepared using a two stage polymerization technique. The technique was successfully scaled up to produce 50 grams of this high polymer in a single run. The reactive monomer approach was also investigated using the following aminosilanes: bis(dimethylamino)dimethylsilane, N,N-bis(pyrrolidinyl)dimethylsilane and N,N-bis(gamma-butyrolactam)dimethylsilane). Thermal analyses were performed in both air and nitrogen. The experimental polymers decomposed at 540 to 562 C, as opposed to 408 to 426 C for commercial silicones. Differential scanning calorimetry showed a glass transition (Tg) at -50 to -55 C for the silphenylene-siloxane copolymer while the commercial silicones had Tg's at -96 to -112 C

Multi-Estimator Full Left Ventricle Quantification through Ensemble Learning

Cardiovascular disease accounts for 1 in every 4 deaths in United States. Accurate estimation of structural and functional cardiac parameters is crucial for both diagnosis and disease management. In this work, we develop an ensemble learning framework for more accurate and robust left ventricle (LV) quantification. The framework combines two 1st-level modules: direct estimation module and a segmentation module. The direct estimation module utilizes Convolutional Neural Network (CNN) to achieve end-to-end quantification. The CNN is trained by taking 2D cardiac images as input and cardiac parameters as output. The segmentation module utilizes a U-Net architecture for obtaining pixel-wise prediction of the epicardium and endocardium of LV from the background. The binary U-Net output is then analyzed by a separate CNN for estimating the cardiac parameters. We then employ linear regression between the 1st-level predictor and ground truth to learn a 2nd-level predictor that ensembles the results from 1st-level modules for the final estimation. Preliminary results by testing the proposed framework on the LVQuan18 dataset show superior performance of the ensemble learning model over the two base modules.Comment: Jiasha Liu, Xiang Li and Hui Ren contribute equally to this wor

Alternative Financial Services as a Social Determinant of Health in U.S. Metropolitan Statistical Areas

Alternative financial services (AFS) such as payday lenders, pawn brokers, tax refund loans, and check cashers are more prevalent in minority and lower income neighborhoods. These are neighborhoods also found to have disparities in health, compared to more affluent neighborhoods and communities. The focus of this paper is to determine if any relationship exists between use of AFS and health disparities. Using data from a survey performed by the Federal Deposit Insurance Corporation (FDIC), we compared four banking variables to several measures of health for 85 metropolitan statistical areas (MSA) across the nation. The four banking variables all related to degrees of reliance on alternative financial services. The three health related measures were all-cause mortality, cancer mortality, and drug and alcohol related mortality. The regression analysis controlled for income, education, and relative size of the nonwhite population. We found that for all-cause mortality there is a statistically significant relationship between three of the four banking variables, in particular “Used an AFS” has a strong association with a coefficient of 0.25 and a p-value of 0.001. The conclusion of this analysis is that when use of AFS increases for an MSA, health status declines, as seen with all-cause mortality. This study adds evidence to establish a finer and often unrecognized dimension of “social determinants of health.

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Alternative Financial Services and Health Status in U.S. Metropolitan Statistical Areas

Abstract Alternative financial services (AFS) such as, payday lenders, pawn brokers, tax refund loans, and check cashers are more prevalent in minority and lower income neighborhoods. These are neighborhoods also found to have disparities in health, compared to more affluent neighborhoods and communities. The focus of this paper is to determine if any relationship exists between use of AFS and health disparities. Using data from a survey performed by the Federal Deposit Insurance Corporation (FDIC), we compared four banking variables to several measures of health for 85 metropolitan statistical areas (MSA) across the nation. The four banking variables all related to degrees of reliance on alternative financial services. The three health related measures were all-cause mortality, cancer mortality, and drug and alcohol related mortality. The regression analysis controlled for income, education, and relative size of the nonwhite population. We found that for all-cause mortality there is a statistically significant relationship between three of the four banking variables, in particular “Used an AFS” has a strong association with a coefficient of 0.25 and a p-value of 0.001. The conclusion of this analysis is that when use of AFS increases for an MSA, health status declines, as seen with all-cause mortality. This study adds evidence to establish a finer and often unrecognized dimension of “social determinants of health.

Collaborative ‘science of science’ needed to ensure research and education make a difference to practice.

There has been much recent interest in ‘impact of research’, what it means, why we need it, and how we measure it. Much of this has focused on academic research, driven by the need to include impact case studies within submissions to the 2014 Research Excellence Framework (REF). However, the impact of education and practice is also of significant importance. In October 2014 the Centre of Postgraduate Medical Research and Education hosted a symposium exploring issues around impact. The event brought together academics, researchers, and clinicians working in healthcare to hear from a range of presenters. A combination of local and national speakers shared their views on impact in their professional and disciplinary areas

Giant Magnetoelectric Effect in a Multiferroic Material with a High Ferroelectric Transition Temperature

We present a unique example of giant magnetoelectric effect in a conventional multiferroic HoMnO3, where polarization is very large (~56 mC/m2) and the ferroelectric transition temperature is higher than the magnetic ordering temperature by an order. We attribute the uniqueness of the giant magnetoelectric effect to the ferroelectricity induced entirely by the off-center displacement of rare earth ions with large magnetic moments. This finding suggests a new avenue to design multiferroics with large polarization and higher ferroelectric transition temperature as well as large magnetoelectric effects