Development of Contact Lenses from a Biomaterial Point of View – Materials, Manufacture, and Clinical Application

Rigid lenses, which were originally made from glass (between 1888 and 1940) and later from polymethyl methacrylate or silicone acrylate materials, are uncomfortable to wear and are now seldom fitted to new patients. Contact lenses became a popular mode of ophthalmic refractive error correction following the discovery of the first hydrogel material – hydroxyethyl methacrylate – by Czech chemist Otto Wichterle in 1960. To satisfy the requirements for ocular biocompatibility, contact lenses must be transparent and optically stable (for clear vision), have a low elastic modulus (for good comfort), have a hydrophilic surface (for good wettability), and be permeable to certain metabolites, especially oxygen, to allow for normal corneal metabolism and respiration during lens wear. A major breakthrough in respect of the last of these requirements was the development of silicone hydrogel soft lenses in 1999 and techniques for making the surface hydrophilic. The vast majority of contact lenses distributed worldwide are mass-produced using cast molding, although spin casting is also used. These advanced mass-production techniques have facilitated the frequent disposal of contact lenses, leading to improvements in ocular health and fewer complications. More than one-third of all soft contact lenses sold today are designed to be discarded daily (i.e., ‘daily disposable’ lenses).

Prediction of CO concentrations based on a hybrid Partial Least Square and Support Vector Machine model

Due to the health impacts caused by exposures to air pollutants in urban areas, monitoring and forecasting of air quality parameters have become popular as an important topic in atmospheric and environmental research today. The knowledge on the dynamics and complexity of air pollutants behavior has made artificial intelligence models as a useful tool for a more accurate pollutant concentration prediction. This paper focuses on an innovative method of daily air pollution prediction using combination of Support Vector Machine (SVM) as predictor and Partial Least Square (PLS) as a data selection tool based on the measured values of CO concentrations. The CO concentrations of Rey monitoring station in the south of Tehran, from Jan. 2007 to Feb. 2011, have been used to test the effectiveness of this method. The hourly CO concentrations have been predicted using the SVM and the hybrid PLS–SVM models. Similarly, daily CO concentrations have been predicted based on the aforementioned four years measured data. Results demonstrated that both models have good prediction ability; however the hybrid PLS–SVM has better accuracy. In the analysis presented in this paper, statistic estimators including relative mean errors, root mean squared errors and the mean absolute relative error have been employed to compare performances of the models. It has been concluded that the errors decrease after size reduction and coefficients of determination increase from 56 to 81% for SVM model to 65–85% for hybrid PLS–SVM model respectively. Also it was found that the hybrid PLS–SVM model required lower computational time than SVM model as expected, hence supporting the more accurate and faster prediction ability of hybrid PLS–SVM model.

OSCE online : making assessment of clinical competencies transparent, accountable & authentic

Creating an authentic assessment which at once assesses competencies, scene management, communication and overall patient care is challenging in the competitive tertiary education market. Increasing student numbers and the cost of evaluating scenario based competencies serve to ensure the need for consistent objectivity and need for timely feedback to students on their performance. Objective structured clinical examination (OSCE) is currently the most flexible approach to competency based formative and summative assessment and widely used within paramedic degree programs. Students are understandably compelled to perform well and can be frustrated by not receiving timely and appropriate feedback. Increasingly a number of products aimed at providing a more efficient and paperless approach have begun to enter the market. These products, it is suggested are aimed at medicine programs and not at allied health professions and limited to one operating system and therefore ignore issues surrounding equity and accessibility. OSCE Online aims to address this gap in the market and is tailored to these disciplines. The application will provide a service that can be both tailored and standardised from a pre-written bank, depending upon requirement to fit around the needs of clinical competency assessment. Delivering authentic assessments to address student milestones in their training to become paramedics is the cornerstone of OSCE Online. By not being restricted to a specific device it will address issues of functionality, adaptability, accessibility, authenticity and importantly: transparency and accountability by producing contemporaneous data allowing issues to be easily identified and rectified.

Consensus σ70 promoter prediction using hadoop

MapReduce frameworks such as Hadoop are well suited to handling large sets of data which can be processed separately and independently, with canonical applications in information retrieval and sales record analysis. Rapid advances in sequencing technology have ensured an explosion in the availability of genomic data, with a consequent rise in the importance of large scale comparative genomics, often involving operations and data relationships which deviate from the classical Map Reduce structure. This work examines the application of Hadoop to patterns of this nature, using as our focus a wellestablished workflow for identifying promoters - binding sites for regulatory proteins - Across multiple gene regions and organisms, coupled with the unifying step of assembling these results into a consensus sequence. Our approach demonstrates the utility of Hadoop for problems of this nature, showing how the tyranny of the "dominant decomposition" can be at least partially overcome. It also demonstrates how load balance and the granularity of parallelism can be optimized by pre-processing that splits and reorganizes input files, allowing a wide range of related problems to be brought under the same computational umbrella.

Establishing research in a palliative care clinical setting : perceived barriers and implemented strategies

There are many challenges in developing research projects in research-naïve clinical settings, especially palliative care where resistance to participate in research has been identified. These challenges to the implementation of research are common in nursing practice and are associated with attitudes towards research participation, and some lack of understanding of research as a process to improve clinical practice. This is despite the professional nursing requirement to conduct research into issues that influence palliative care practice. The purpose of this paper is to describe the process of implementing a clinical research project in collaboration with the clinicians of a palliative care community team and to reflect on the strategies implemented to overcome the challenges involved. The challenges presented here demonstrate the importance of proactively implementing engagement strategies from the inception of a research project in a clinical setting.

Do prediction markets produce well-calibrated probability forecasts?

This article presents new theoretical and empirical evidence on the forecasting ability of prediction markets. We develop a model that predicts that the time until expiration of a prediction market should negatively affect the accuracy of prices as a forecasting tool in the direction of a ‘favourite/longshot bias’. That is, high-likelihood events are underpriced, and low-likelihood events are over-priced. We confirm this result using a large data set of prediction market transaction prices. Prediction markets are reasonably well calibrated when time to expiration is relatively short, but prices are significantly biased for events farther in the future. When time value of money is considered, the miscalibration can be exploited to earn excess returns only when the trader has a relatively low discount rate.

ShARe/CLEF eHealth Evaluation Lab 2013, Task 3: Information retrieval to address patients' questions when reading clinical reports

This paper presents the results of task 3 of the ShARe/CLEF eHealth Evaluation Lab 2013. This evaluation lab focuses on improving access to medical information on the web. The task objective was to investigate the effect of using additional information such as the discharge summaries and external resources such as medical ontologies on the IR effectiveness. The participants were allowed to submit up to seven runs, one mandatory run using no additional information or external resources, and three each using or not using discharge summaries.

Fire performance of cold-formed steel wall panels and prediction of their fire resistance rating

Recent research at the Queensland University of Technology has investigated the structural and thermal behaviour of load bearing Light gauge Steel Frame (LSF) wall systems made of 1.15 mm G500 steel studs and varying plasterboard and insulation configurations (cavity and external insulation) using full scale fire tests. Suitable finite element models of LSF walls were then developed and validated by comparing with test results. In this study, the validated finite element models of LSF wall panels subject to standard fire conditions were used in a detailed parametric study to investigate the effects of important parameters such as steel grade and thickness, plasterboard screw spacing, plasterboard lateral restraint, insulation materials and load ratio on their performance under standard fire conditions. Suitable equations were proposed to predict the time–temperature profiles of LSF wall studs with eight different plasterboard-insulation configurations, and used in the finite element analyses. Finite element parametric studies produced extensive fire performance data for the LSF wall panels in the form of load ratio versus time and critical hot flange (failure) temperature curves for eight wall configurations. This data demonstrated the superior fire performance of externally insulated LSF wall panels made of different steel grades and thicknesses. It also led to the development of a set of equations to predict the important relationship between the load ratio and the critical hot flange temperature of LSF wall studs. Finally this paper proposes a simplified method to predict the fire resistance rating of LSF walls based on the two proposed set of equations for the load ratio–hot flange temperature and the time–temperature relationships.

Heterogeneity of clinical and environmental isolates of Mycobacterium fortuitum using repetitive element sequence-based PCR: municipal water an unlikely source of community-acquired infections

M. fortuitum is a rapidly growing mycobacterium associated with community-acquired and nosocomial wound, soft tissue, and pulmonary infections. It has been postulated that water has been the source of infection especially in the hospital setting. The aim of this study was to determine if municipal water may be the source of community-acquired or nosocomial infections in the Brisbane area. Between 2007 and 2009, 20 strains of M. fortuitum were recovered from municipal water and 53 patients’ isolates were submitted to the reference laboratory. A wide variation in strain types was identified using repetitive element sequence-based PCR, with 13 clusters of ≥2 indistinguishable isolates, and 28 patterns consisting of individual isolates. The clusters could be grouped into seven similar groups (>95% similarity). Municipal water and clinical isolates collected during the same time period and from the same geographical area consisted of different strain types, making municipal water an unlikely source of sporadic human infection.

Strain variation amongst clinical and potable water isolates of M.kansasii using automated repetitive unit PCR

Mycobacterium kansasii is a pulmonary pathogen that has been grown readily from municipal water, but rarely isolated from natural waters. A definitive link between water exposure and disease has not been demonstrated and the environmental niche for this organism is poorly understood. Strain typing of clinical isolates has revealed seven subtypes with Type 1 being highly clonal and responsible for most infections worldwide. The prevalence of other subtypes varies geographically. In this study 49 water isolates are compared with 72 patient isolates from the same geographical area (Brisbane, Australia), using automated repetitive unit PCR (Diversilab) and ITS RFLP. The clonality of the dominant clinical strain type is again demonstrated but with rep-PCR, strain variation within this group is evident comparable with other reported methods. There is significant heterogeneity of water isolates and very few are similar or related to the clinical isolates. This suggests that if water or aerosol transmission is the mode of infection, then point source contamination likely occurs from an alternative environmental source.

Analysis of temporary traffic control cost items in transportation construction bidding process

Temporary Traffic Control Plans (TCP’s), which provide construction phasing to maintain traffic during construction operations, are integral component of highway construction project design. Using the initial design, designers develop estimated quantities for the required TCP devices that become the basis for bids submitted by highway contractors. However, actual as-built quantities are often significantly different from the engineer’s original estimate. The total cost of TCP phasing on highway construction projects amounts to 6–10% of the total construction cost. Variations between engineer estimated quantities and final quantities contribute to reduced cost control, increased chances of cost related litigations, and bid rankings and selection. Statistical analyses of over 2000 highway construction projects were performed to determine the sources of variation, which later were used as the basis of development for an automated-hybrid prediction model that uses multiple regressions and heuristic rules to provide accurate TCP quantities and costs. The predictive accuracy of the model developed was demonstrated through several case studies.

Understanding the abnormal brain activity in epilepsy as a potential predictor of the onset of an epileptic seizure

The Brain Research Institute (BRI) uses various types of indirect measurements, including EEG and fMRI, to understand and assess brain activity and function. As well as the recovery of generic information about brain function, research also focuses on the utilisation of such data and understanding to study the initiation, dynamics, spread and suppression of epileptic seizures. To assist with the future focussing of this aspect of their research, the BRI asked the MISG 2010 participants to examine how the available EEG and fMRI data and current knowledge about epilepsy should be analysed and interpreted to yield an enhanced understanding about brain activity occurring before, at commencement of, during, and after a seizure. Though the deliberations of the study group were wide ranging in terms of the related matters considered and discussed, considerable progress was made with the following three aspects. (1) The science behind brain activity investigations depends crucially on the quality of the analysis and interpretation of, as well as the recovery of information from, EEG and fMRI measurements. A number of specific methodologies were discussed and formalised, including independent component analysis, principal component analysis, profile monitoring and change point analysis (hidden Markov modelling, time series analysis, discontinuity identification). (2) Even though EEG measurements accurately and very sensitively record the onset of an epileptic event or seizure, they are, from the perspective of understanding the internal initiation and localisation, of limited utility. They only record neuronal activity in the cortical (surface layer) neurons of the brain, which is a direct reflection of the type of electrical activity they have been designed to record. Because fMRI records, through the monitoring of blood flow activity, the location of localised brain activity within the brain, the possibility of combining fMRI measurements with EEG, as a joint inversion activity, was discussed and examined in detail. (3) A major goal for the BRI is to improve understanding about ``when'' (at what time) an epileptic seizure actually commenced before it is identified on an eeg recording, ``where'' the source of this initiation is located in the brain, and ``what'' is the initiator. Because of the general agreement in the literature that, in one way or another, epileptic events and seizures represent abnormal synchronisations of localised and/or global brain activity the modelling of synchronisations was examined in some detail. References C. M. Michel, G. Thut, S. Morand, A. Khateb, A. J. Pegna, R. Grave de Peralta, S. Gonzalez, M. Seeck and T. Landis, Electric source imaging of human brain functions, Brain Res. 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Reframe : QUT's evaluation framework survey business rules

Reframe is changing our approach to the evaluation of courses, units, teaching and student experience at QUT. We are moving away from a single survey tool to a richer, more holistic and customisable approach. This approach will help our academics design and deliver high-quality learning experiences, and review the impact of their teaching practice on student learning. Through it, we will also be able to provide more timely access to specialised support and meet external reporting requirements.

Incorporating adverse event relatedness into dose-finding clinical trial designs

Dose-finding designs estimate the dose level of a drug based on observed adverse events. Relatedness of the adverse event to the drug has been generally ignored in all proposed design methodologies. These designs assume that the adverse events observed during a trial are definitely related to the drug, which can lead to flawed dose-level estimation. We incorporate adverse event relatedness into the so-called continual reassessment method. Adverse events that have ‘doubtful’ or ‘possible’ relationships to the drug are modelled using a two-parameter logistic model with an additive probability mass. Adverse events ‘probably’ or ‘definitely’ related to the drug are modelled using a cumulative logistic model. To search for the maximum tolerated dose, we use the maximum estimated toxicity probability of these two adverse event relatedness categories. We conduct a simulation study that illustrates the characteristics of the design under various scenarios. This article demonstrates that adverse event relatedness is important for improved dose estimation. It opens up further research pathways into continual reassessment design methodologies.