Mechanism for cross-linking polychloroprene with ethylene thiourea and zinc oxide

An investigation into the mechanism by which ethylene thiourea (ETU) cross-links polychloroprene (CR) in combination with zinc oxide (ZnO) was undertaken. This was achieved through an examination of the mechanisms of crosslinking CR with ETU and ZnO separately and in unison. Spectroscopic and physical characterization techniques were employed to probe the cross-linking mechanisms of CRusing other standard rubber accelerators and model compounds with analogous structures and functionalities to ETU. These investigations have resulted in the proposal of a new mechanism by which ETU and ZnO can synergistically cross-link CR, in addition to providing new evidence to support concomitant mechanisms already published for cross-linking CR

Disparities in selective referral for cancer surgeries: implications for the current healthcare delivery system

Objectives: Among considerable efforts to improve quality of surgical care, expedited measures such as a selective referral to high-volume institutions have been advocated. Our objective was to examine whether racial, insurance and/or socioeconomic disparities exist in the use of high-volume hospitals for complex surgical oncological procedures within the USA. Design, setting and participants Patients undergoing colectomy, cystectomy, oesophagectomy, gastrectomy, hysterectomy, lung resection, pancreatectomy or prostatectomy were identified retrospectively, using the Nationwide Inpatient Sample, between years 1999 and 2009. This resulted in a weighted estimate of 2 508 916 patients. Primary outcome measures Distribution of patients according to race, insurance and income characteristics was examined according to low-volume and high-volume hospitals (highest 20% of patients according to the procedure-specific mean annual volume). Generalised linear regression models for prediction of access to high-volume hospitals were performed. Results: Insurance providers and county income levels varied differently according to patients’ race. Most Caucasians resided in wealthier counties, regardless of insurance types (private/Medicare), while most African Americans resided in less wealthy counties (≤$24 999), despite being privately insured. In general, Caucasians, privately insured, and those residing in wealthier counties (≥$45 000) were more likely to receive surgery at high-volume hospitals, even after adjustment for all other patient-specific characteristics. Depending on the procedure, some disparities were more prominent, but the overall trend suggests a collinear effect for race, insurance type and county income levels. Conclusions: Prevailing disparities exist according to several patient and sociodemographic characteristics for utilisation of high-volume hospitals. Efforts should be made to directly reduce such disparities and ensure equal healthcare delivery

Visualising high-dimensional Pareto relationships in two-dimensional scatterplots

Copyright © 2013 Springer-Verlag Berlin Heidelberg. The final publication is availablevia the DOI in this recordBook title: Evolutionary Multi-Criterion Optimization7th International Conference on Evolutionary Multi-Criterion Optimization (EMO 2013), Sheffield, UK, March 19-22, 2013The codebase for this paper is available at https://github.com/fieldsend/emo_2013_vizIn this paper two novel methods for projecting high dimensional data into two dimensions for visualisation are introduced, which aim to limit the loss of dominance and Pareto shell relationships between solutions to multi-objective optimisation problems. It has already been shown that, in general, it is impossible to completely preserve the dominance relationship when mapping from a higher to a lower dimension – however, approaches that attempt this projection with minimal loss of dominance information are useful for a number of reasons. (1) They may represent the data to the user of a multi-objective optimisation problem in an intuitive fashion, (2) they may help provide insights into the relationships between solutions which are not immediately apparent through other visualisation methods, and (3) they may offer a useful visual medium for interactive optimisation. We are concerned here with examining (1) and (2), and developing relatively rapid methods to achieve visualisations, rather than generating an entirely new search/optimisation problem which has to be solved to achieve the visualisation– which may prove infeasible in an interactive environment for real time use. Results are presented on randomly generated data, and the search population of an optimiser as it progresses. Structural insights into the evolution of a set-based optimiser that can be derived from this visualisation are also discussed

A visual analytics framework for spatio-temporal analysis and modelling

To support analysis and modelling of large amounts of spatio-temporal data having the form of spatially referenced time series (TS) of numeric values, we combine interactive visual techniques with computational methods from machine learning and statistics. Clustering methods and interactive techniques are used to group TS by similarity. Statistical methods for TS modelling are then applied to representative TS derived from the groups of similar TS. The framework includes interactive visual interfaces to a library of modelling methods supporting the selection of a suitable method, adjustment of model parameters, and evaluation of the models obtained. The models can be externally stored, communicated, and used for prediction and in further computational analyses. From the visual analytics perspective, the framework suggests a way to externalize spatio-temporal patterns emerging in the mind of the analyst as a result of interactive visual analysis: the patterns are represented in the form of computer-processable and reusable models. From the statistical analysis perspective, the framework demonstrates how TS analysis and modelling can be supported by interactive visual interfaces, particularly, in a case of numerous TS that are hard to analyse individually. From the application perspective, the framework suggests a way to analyse large numbers of spatial TS with the use of well-established statistical methods for TS analysis

National trends in hospital-acquired preventable adverse events after major cancer surgery in the USA

Objectives: While multiple studies have demonstrated variations in the quality of cancer care in the USA, payers are increasingly assessing structure-level and process-level measures to promote quality improvement. Hospital-acquired adverse events are one such measure and we examine their national trends after major cancer surgery. Design: Retrospective, cross-sectional analysis of a weighted-national estimate from the Nationwide Inpatient Sample (NIS) undergoing major oncological procedures (colectomy, cystectomy, oesophagectomy, gastrectomy, hysterectomy, lung resection, pancreatectomy and prostatectomy). The Agency for Healthcare Research and Quality Patient Safety Indicators (PSIs) were utilised to identify trends in hospital-acquired adverse events. Setting: Secondary and tertiary care, US hospitals in NIS Participants: A weighted-national estimate of 2 508 917 patients (>18 years, 1999–2009) from NIS. Primary outcome measures Hospital-acquired adverse events. Results: 324 852 patients experienced ≥1-PSI event (12.9%). Patients with ≥1-PSI experienced higher rates of in-hospital mortality (OR 19.38, 95% CI 18.44 to 20.37), prolonged length of stay (OR 4.43, 95% CI 4.31 to 4.54) and excessive hospital-charges (OR 5.21, 95% CI 5.10 to 5.32). Patients treated at lower volume hospitals experienced both higher PSI events and failure-to-rescue rates. While a steady increase in the frequency of PSI events after major cancer surgery has occurred over the last 10 years (estimated annual % change (EAPC): 3.5%, p<0.001), a concomitant decrease in failure-to-rescue rates (EAPC −3.01%) and overall mortality (EAPC −2.30%) was noted (all p<0.001). Conclusions: Over the past decade, there has been a substantial increase in the national frequency of potentially avoidable adverse events after major cancer surgery, with a detrimental effect on numerous outcome-level measures. However, there was a concomitant reduction in failure-to-rescue rates and overall mortality rates. Policy changes to improve the increasing burden of specific adverse events, such as postoperative sepsis, pressure ulcers and respiratory failure, are required

Microfungi in Drinking Water: The Role of the Frog Litoria caerulea

Microfungi were recovered from all parts of a municipal water distribution system in sub-tropical Australia even though virtually no colony-forming units were recovered from the treated water as it left the treatment plant. A study was then undertaken to determine the potential sources of the microfungal population in the distribution system. Observation of frogs (Litoria caerulea) using the internal infrastructure of a reservoir as diurnal sleeping places, together with observation of visible microfungal growth on their faecal pellets, led to an investigation of the possible involvement of this animal. Old faecal pellets were collected and sporulating fungal colonies growing on their surfaces were identified. Fresh faecal pellets were collected and analysed for microfungal content, and skin swabs were analysed for yeasts. It was found that the faeces and skin of L. caerulea carried large numbers of yeasts as well as spores of various filamentous fungal genera. While there are many possible sources of microfungal contamination of municipal drinking water supplies, this study has revealed that the Australian green tree frog L. caerulea is one of the important sources of filamentous microfungi and yeasts in water storage reservoirs in sub-tropical Australia where the animal is endemic

Making sense of business analytics : the case of two start-ups

Business analytics have enabled businesses to leverage unstructured and dispersed data in order to improve their operations and position themselves better within a highly turbulent environment. While much discussion has been focused on how businesses can move from data to insights to decision making, much less is known around how businesses actually interpret the insights provided by business analytics tools. This extended abstract proposes the use of sense-making as the theoretical lens for interpreting these insights, combined with contextual information. We will be using two case studies to further explore the applicability of our proposition

Assessment of learning curves in complex surgical interventions: a consecutive case-series study

Background: Surgical interventions are complex, which complicates their rigorous assessment through randomised clinical trials. An important component of complexity relates to surgeon experience and the rate at which the required level of skill is achieved, known as the learning curve. There is considerable evidence that operator performance for surgical innovations will change with increasing experience. Such learning effects complicate evaluations; the start of the trial might be delayed, resulting in loss of surgeon equipoise or, if an assessment is undertaken before performance has stabilised, the true impact of the intervention may be distorted. Methods: Formal estimation of learning parameters is necessary to characterise the learning curve, model its evolution and adjust for its presence during assessment. Current methods are either descriptive or model the learning curve through three main features: the initial skill level, the learning rate and the final skill level achieved. We introduce a fourth characterising feature, the duration of the learning period, which provides an estimate of the point at which learning has stabilised. We propose a two-phase model to estimate formally all four learning curve features. Results: We demonstrate that the two-phase model can be used to estimate the end of the learning period by incorporating a parameter for estimating the duration of learning. This is achieved by breaking down the model into a phase describing the learning period and one describing cases after the final skill level is reached, with the break point representing the length of learning. We illustrate the method using cardiac surgery data. Conclusions: This modelling extension is useful as it provides a measure of the potential cost of learning an intervention and enables statisticians to accommodate cases undertaken during the learning phase and assess the intervention after the optimal skill level is reached. The limitations of the method and implications for the optimal timing of a definitive randomised controlled trial are also discussed

Generative mechanisms for innovation in information infrastructures

This paper investigates how innovation of ICT based services takes place within existing infrastructures, including the whole network of technology, vendors and customers. Our research question is, how can an information infrastructure provide generative mechanisms for innovation of ICT based services? Building on a critical realist approach, our empirical evidence was a case study within an international airline, aiming to diversify its services. From our analysis we propose that there are two self-reinforcement mechanisms in information infrastructures. First, we identified the innovation reinforcement mechanism, resulting in new services. Second, there is the service reinforcement mechanism, resulting in more users and profits. The practical implication of our framework is to show that although ICT-based innovation cannot be planned and managed in detail, the innovation mechanism may help organisations to facilitate the innovation process in a structured way

Guillain-Barré syndrome and adjuvanted pandemic influenza A (H1N1) 2009 vaccines: A multinational self-controlled case series in Europe

Background: The risk of Guillain-Barré syndrome (GBS) following the United States' 1976 swine flu vaccination campaign in the USA led to enhanced active surveillance during the pandemic influenza (A(H1N1)pdm09) immunization campaign. This study aimed to estimate the risk