Teaching family carers about home based palliative care: Final results from a group education program

Without the considerable support provided by family carers, many patients receiving palliative care would be unable to remain at home. However, family carers typically lack the required information and skills to prepare them for such a role. Pilot work has demonstrated that group education programs for family carers can be readily developed; they are feasible, accessible, and useful. This project sought to build on our pilot research to further examine the effectiveness of a group education program by evaluating the outcomes with a larger number of participants. The program aimed to prepare primary family carers for the role of supporting a relative with advanced, noncurative cancer at home. The psycho-educational program consisted of three consecutive weekly sessions presented in a group format, conducted at six home-based palliative care services across metropolitan and regional Victoria, Australia. The following dependent variables were measured at three time points: carer competence, preparedness, rewards, and information needs. The three time points were: commencement of the program (Time 1), upon completion (Time 2), and two weeks later (Time 3). A total of 156 participants (including the pilot phase) completed Time 1 questionnaires and 96 completed all three time periods (62%). Between Time 1 and Time 2, the intervention had a statistically significant positive effect on preparedness, competence, rewards, and having informational needs met. Outcomes were maintained at Time 3. There was no difference in the effectiveness of the intervention for participants in regional areas compared to participants in metropolitan areas.

This study demonstrated that a group education program to prepare family carers for the role of supporting a dying relative at home was effective. Implications for further research and practice are outlined.

Trends in Approval Times for Genetically Engineered Crops in the United States and the European Union

Genetically engineered (GE) crops are subject to regulatory oversight to ensure their safety for humans and the environment. Their approval in the European Union (EU) starts with an application in a given Member State followed by a scientific step (risk assessment), and ends with a political decision-making step (risk management); and in the United States (US) it starts with a scientific (field trial) step and ends with a ‘bureaucratic’ decision-making step. We investigated trends for the time taken for these steps and the overall time taken for approving GE crops in the US and the EU (traders in these commodities). Results show that from 1996-2015 the overall time trend for approval in the EU decreased and then flattened off, with an overall mean completion-time of 1,763 days. In the US in 1998 there was a break in the trend of the overall approval time: Initially, from 1988 until 1997 the trend decreased with a mean approval time of 1,321 days; from 1998-2015, the trend almost stagnated with a mean approval time of 2,467 days.

Early-type stars in the Galactic halo from the Palomar-Green survey - III. Completion of a magnitude range limited sample

High-resolution (R approximate to 40 000) echelle spectroscopic observations of 13 high-latitude early-type stars are presented. These stars comprise the final part of a complete magnitude range limited sample based on low-resolution spectroscopy of targets drawn from the Palomar-Green survey. The magnitude range under consideration is 13 less than or equal to B-PG less than or equal to 14.6, corresponding to an approximate distance limit for main-sequence B-type objects of 5 less than or equal to d less than or equal to 40 kpc. Three stars are found to be apparently normal, young stars, based on their positions on the (T-eff, log g) diagram, normal abundance patterns and relatively large projected rotational velocities. A further star, PG 1209+263, was found to belong to the chemically peculiar (CP) silicon star class of objects. The remainder are evolved subluminous stars lying on post- horizontal branch (post-HB) tracks, with the exception of PG 2120+062, which appears to be in a post-asymptotic giant branch evolutionary stage. For the young stars in the sample, we have derived distance and age estimates through comparison of the atmospheric parameters with recent theoretical evolutionary models. We discuss formation scenarios by comparing times-of- flight and evolutionary time-scales. It is found that all stars could have formed in the Galactic disc and been ejected from there soon after their birth, with the exception of PG 1209+263. The adopted proper motion is found to be a crucial factor in the kinematical analysis. We also present some number densities for young B-type halo stars, which indicate that they are extremely scarce objects.

Real time monitoring of the polymerisation of PMMA bone cement using Raman spectroscopy

In this investigation Raman spectroscopy was shown to be a method that could be used to monitor the polymerisation of PMMA bone cement. Presently there is no objective method that orthopaedic surgeons can use to quantify the curing process of cement during surgery. Raman spectroscopy is a non-invasive, non-destructive technique that could offer such an option. Two commercially available bone cements (Palacos® R and SmartSet® HV) and different storage conditions (4 and 22°C) were used to validate the technique. Raman spectroscopy was found to be repeatable across all conditions with the completion of the polymerisation process particularly easy to establish. All tests were benchmarked against current temperature monitoring methods outlined in ISO and ASTM standards. There was found to be close agreement with the standard methods and the Raman spectroscopy used in this study.

Best of the old alongside the new: training for part-time youth workers

Set against the dearth of published research into the effectiveness of youth leadership training programmes, the present study describes how a comprehensive evaluation model was utilised to evaluate one such programme in Northern Ireland over a 3-year period. The training welds together a traditional curriculum approach and a competence-based methodology to provide an integrated experience for the part-time youth worker participants (n = 128). Self-completion questionnaires and follow-up interviews with a random sample of these youth workers and their supervisors were used to collect data. Outcomes suggest that the synthesis of these two training strategies is not only effective in meeting the learning needs of youth workers, but also leads to identifiable improvements in the range and quality of youth work programmes available to young people

Improving molecular detection of Candida DNA in whole blood:comparison of seven fungal DNA extraction protocols using real-time PCR

The limitations of classical diagnostic methods for invasive Candida infections have led to the development of molecular techniques such as real-time PCR to improve diagnosis. However, the detection of low titres of Candida DNA in blood from patients with candidaemia requires the use of extraction methods that efficiently lyse yeast cells and recover small amounts of DNA suitable for amplification. In this study, a Candida-specific real-time PCR assay was used to detect Candida albicans DNA in inoculated whole blood specimens extracted using seven different extraction protocols. The yield and quality of total nucleic acids were estimated using UV absorbance, and specific recovery of C. albicans genomic DNA was estimated quantitatively in comparison with a reference (Qiagen kit/lyticase) method currently in use in our laboratory. The extraction protocols were also compared with respect to sensitivity, cost and time required for completion. The TaqMan PCR assay used to amplify the DNA extracts achieved high levels of specificity, sensitivity and reproducibility. Of the seven extraction protocols evaluated, only the MasterPure yeast DNA extraction reagent kit gave significantly higher total nucleic acid yields than the reference method, although nucleic acid purity was highest using either the reference or YeaStar genomic DNA kit methods. More importantly, the YeaStar method enabled C. albicans DNA to be detected with highest sensitivity over the entire range of copy numbers evaluated, and appears to be an optimal method for extracting Candida DNA from whole blood.

Hierarchical Demand Response for Peak Minimization Using Dantzig-Wolfe Decomposition

Demand response (DR) algorithms manipulate the energy consumption schedules of controllable loads so as to satisfy grid objectives. Implementation of DR algorithms using a centralized agent can be problematic for scalability reasons, and there are issues related to the privacy of data and robustness to communication failures. Thus, it is desirable to use a scalable decentralized algorithm for the implementation of DR. In this paper, a hierarchical DR scheme is proposed for peak minimization based on Dantzig-Wolfe decomposition (DWD). In addition, a time weighted maximization option is included in the cost function, which improves the quality of service for devices seeking to receive their desired energy sooner rather than later. This paper also demonstrates how the DWD algorithm can be implemented more efficiently through the calculation of the upper and lower cost bounds after each DWD iteration.

Improved Real-time State-of-Charge Estimation of LiFePO4 Battery Based on a Novel Thermoelectric Model

Li-ion batteries have been widely used in electric vehicles, and battery internal state estimation plays an important role in the battery management system. However, it is technically challenging, in particular, for the estimation of the battery internal temperature and state-ofcharge (SOC), which are two key state variables affecting the battery performance. In this paper, a novel method is proposed for realtime simultaneous estimation of these two internal states, thus leading to a significantly improved battery model for realtime SOC estimation. To achieve this, a simplified battery thermoelectric model is firstly built, which couples a thermal submodel and an electrical submodel. The interactions between the battery thermal and electrical behaviours are captured, thus offering a comprehensive description of the battery thermal and electrical behaviour. To achieve more accurate internal state estimations, the model is trained by the simulation error minimization method, and model parameters are optimized by a hybrid optimization method combining a meta-heuristic algorithm and the least square approach. Further, timevarying model parameters under different heat dissipation conditions are considered, and a joint extended Kalman filter is used to simultaneously estimate both the battery internal states and time-varying model parameters in realtime. Experimental results based on the testing data of LiFePO4 batteries confirm the efficacy of the proposed method.