Tuning thermal properties and microphase separation in aliphatic polyester ABA copolymers

Four alkyl substituted β-lactones were investigated as monomers in ring opening polymerisation to produce a family of poly(3-hydroxyalkanoate)s. Homopolymers were synthesised using a robust aluminium salen catalyst, resulting in polymers with low dispersity (Đ < 1.1) and predictable molecular weights. ABA triblock copolymers were prepared using poly(L-lactic acid) as the A block and the afore- mentioned poly(3-hydroxyalkanoate) as the B block via a sequential addition method. Characterisation of these copolymers determined they were well controlled with low dispersities and predictable molecular weight. DSC analysis determined copolymers prepared from β-butyrolactone or β-valerolactone yielded polymers with tunable and predictable thermal properties. Copolymers prepared from β-heptanolactone yielded a microphase separated material as indicated by SAXS, with two distinct Tgs. The polymers could be readily cast into flexible films and their improved tensile properties were explored

Supramolecular approach to new inkjet printing inks

Electronically complementary, low molecular weight polymers that self-assemble through tunable π−π stacking interactions to form extended supramolecular polymer networks have been developed for inkjet printing applications and successfully deposited using three different printing techniques. Sequential overprinting of the complementary components results in supramolecular network formation through complexation of π-electron rich pyrenyl or perylenyl chain-ends in one component with π-electron deficient naphthalene diimide residues in a chain-folding polyimide. The complementary π−π stacked polymer blends generate strongly colored materials as a result of charge-transfer absorption bands in the visible spectrum, potentially negating the need for pigments or dyes in the ink formulation. Indeed, the final color of the deposited material can be tailored by varying the end-groups of the π-electron rich polymer component. Piezoelectric printing techniques were employed in a proof of concept study to allow characterization of the materials deposited, and a thermal inkjet printer adapted with imaging software enabled in situ analysis of the ink drops as they formed and of their physical properties. Finally, continuous inkjet printing allowed greater volumes of material to be deposited, on a variety of different substrate surfaces, and demonstrated the utility and versatility of this novel type of ink for industrial applications

The grinch who stole wisdom

Dr. Seuss is wise. How the Grinch Stole Christmas (Seuss, 1957) could serve as a parable for our time. It can also be seen as a roadmap for the development of contemplative wisdom. The abiding popularity of How the Grinch Stole Christmas additionally suggests that contemplative wisdom is more readily available to ordinary people, even children, than is normally thought. This matters because from the point of view of contemplatives in any of the world's philosophies or religions, people are confused about wisdom. The content of the nascent field of wisdom studies, they might say, is largely not wisdom at all but rather what it's like to live in a particular kind of prison cell, a well appointed cell perhaps, but not a place that makes possible either personal satisfaction or deep problem solving. I believe that what the contemplative traditions have to say is important; they offer a different orientation to what personal wisdom is, how to develop it, and how to use it in the world than is presently contained in either our popular culture or our sciences. In order to illustrate this I will examine, in some detail, one contemplative path within Buddhism. Buddhism is particularly useful in this respect because its practices are nontheistic and thus avoid many of the cultural landmines associated with the contemplative aspects of Western religions

Isotopic and spin selectivity of H_2 adsorbed in bundles of carbon nanotubes

Due to its large surface area and strongly attractive potential, a bundle of carbon nanotubes is an ideal substrate material for gas storage. In addition, adsorption in nanotubes can be exploited in order to separate the components of a mixture. In this paper, we investigate the preferential adsorption of D_2 versus H_2(isotope selectivity) and of ortho versus para(spin selectivity) molecules confined in the one-dimensional grooves and interstitial channels of carbon nanotube bundles. We perform selectivity calculations in the low coverage regime, neglecting interactions between adsorbate molecules. We find substantial spin selectivity for a range of temperatures up to 100 K, and even greater isotope selectivity for an extended range of temperatures,up to 300 K. This isotope selectivity is consistent with recent experimental data, which exhibit a large difference between the isosteric heats of D_2 and H_2 adsorbed in these bundles.Comment: Paper submitted to Phys.Rev. B; 17 pages, 2 tables, 6 figure

A cluster-randomised trial to evaluate an intervention to promote handwashing in rural Nigeria.

Handwashing with soap at critical times helps prevent diarrhoeal diseases. Changing handwashing practices through behaviour change communication remains a challenge. This study designed and tested a scalable intervention to promote handwashing with soap. A cluster-randomised, controlled trial compared our intervention against standard practice. Subjects were men, women and children in 14 villages in Cross-River state, Nigeria. The primary outcome was the proportion of observed key events on which hands were washed with soap. Binomial regression analysis calculated prevalence differences between study arms. The intervention had minimal effect on the primary outcome (+2.4%, p = 0.096). The intervention was associated with increased frequency of handwashes without soap before food contact (+13%, p = 0.017). The intervention failed to produce significant changes in handwashing with soap at key times. The low dose delivered (two contact points) may have increased scalability at the cost of effectiveness, particularly in the challenging context of inconvenient water access

Assessing the impact of prescribed medicines on health outcomes

This paper reviews methods that can be used to assess the impact of medicine use on population health outcomes. In the absence of a gold standard, we argue that a convergence of evidence from different types of studies using multiple methods of independent imperfection provides the best bases for attributing improvements in health outcomes to the use of medicines. The major requirements are: good evidence that a safe and effective medicine is being appropriately prescribed; covariation between medicine use and improved health outcomes; and being able to discount alternative explanations of the covariation (via covariate adjustment, propensity analyses and sensitivity analyses), so that medicine use is the most plausible explanation of the improved health outcomes. The strongest possible evidence would be provided by the coherence of the following types of evidence: (1) individual linked data showing that patients are prescribed the medicine, there are reasonable levels of patient compliance, and there is a relationship between medicine use and health improvements that is not explained by other factors; (2) ecological evidence of improvements in these health outcomes in the population in which the medicine is used. Confidence in these inferences would be increased by: the replication of these results in comparable countries and consistent trends in population vital statistics in countries that have introduced the medicine; and epidemiological modelling indicating that changes observed in population health outcomes are plausible given the epidemiology of the condition being treated

Presenting the Uncertainties of Odds Ratios Using Empirical-Bayes Prediction Intervals

Quantifying exposure-disease associations is a central issue in epidemiology. Researchers of a study often present an odds ratio (or a logarithm of odds ratio, logOR) estimate together with its confidence interval (CI), for each exposure they examined. Here the authors advocate using the empirical-Bayes-based ‘prediction intervals’ (PIs) to bound the uncertainty of logORs. The PI approach is applicable to a panel of factors believed to be exchangeable (no extra information, other than the data itself, is available to distinguish some logORs from the others). The authors demonstrate its use in a genetic epidemiological study on age-related macular degeneration (AMD). The proposed PIs can enjoy straightforward probabilistic interpretations—a 95% PI has a probability of 0.95 to encompass the true value, and the expected number of true values that are being encompassed is for a total of 95% PIs. The PI approach is theoretically more efficient (producing shorter intervals) than the traditional CI approach. In the AMD data, the average efficiency gain is 51.2%. The PI approach is advocated to present the uncertainties of many logORs in a study, for its straightforward probabilistic interpretations and higher efficiency while maintaining the nominal coverage probability

An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies

The propensity score is the probability of treatment assignment conditional on observed baseline characteristics. The propensity score allows one to design and analyze an observational (nonrandomized) study so that it mimics some of the particular characteristics of a randomized controlled trial. In particular, the propensity score is a balancing score: conditional on the propensity score, the distribution of observed baseline covariates will be similar between treated and untreated subjects. I describe 4 different propensity score methods: matching on the propensity score, stratification on the propensity score, inverse probability of treatment weighting using the propensity score, and covariate adjustment using the propensity score. I describe balance diagnostics for examining whether the propensity score model has been adequately specified. Furthermore, I discuss differences between regression-based methods and propensity score-based methods for the analysis of observational data. I describe different causal average treatment effects and their relationship with propensity score analyses