A Delphi study to validate an advanced practice nursing tool

Aim This paper is a report of a study conducted to validate an instrument for measuring advanced practice nursing role delineation in an international contemporary health service context using the Delphi technique. Background Although most countries now have clear definitions and competency standards for nurse practitioners, no such clarity exists for many advanced practice nurse roles, leaving healthcare providers uncertain whether their service needs can or should be met by an advanced practice nurse or a nurse practitioner. The validation of a tool depicting advanced practice nursing is essential for the appropriate deployment of advanced practice nurses. This paper is the second in a three-phase study to develop an operational framework for assigning advanced practice nursing roles. Method An expert panel was established to review the activities in the Strong Model of Advanced Practice Role Delineation tool. Using the Delphi technique, data were collected via an on-line survey through a series of iterative rounds in 2008. Feedback and statistical summaries of responses were distributed to the panel until the 75% consensus cut-off was obtained. Results After three rounds and modification of five activities, consensus was obtained for validation of the content of this tool. Conclusion The Strong Model of Advanced Practice Role Delineation tool is valid for depicting the dimensions of practice of the advanced practice role in an international contemporary health service context thereby having the potential to optimize the utilization of the advanced practice nursing workforce.

Introduction

The 1990s saw the United Nations, the militaries of key member states, and NGOs increasingly entangled in the complex affairs of disrupted states. Whether as deliverers of humanitarian assistance or as agents of political, social, and civic reconstruction, whether in Somalia, Bosnia, Kosovo, or East Timor, these actors have had to learn ways of interacting with each other in order to optimize the benefits for the populations they seek to assist. Yet the challenges have proved daunting. Civil and military actors have different organizational cultures and standard operating procedures and are confronted with the need to work together to perform tasks to which different actors may attach quite different priorities. From Civil Strife to Civil Society explores the nature of these challenges, blending the experience of scholars and practitioners. It is underpinned by an understanding that recovery from disruption is a laborious process that can easily be de-railed. The first part of the book offers a rigorous examination of the dimensions of state disruption and the roles of the international community in responding to it; the second part looks at military doctrine for dealing with disorder and humanitarian emergencies; the third part examines mechanisms for ending violence and delivering justice in post-conflict times; the fourth part investigates the problems of rebuilding trust and promoting democracy; the fifth part deals with the reconstitution of the rule of law; while the sixth and seventh parts address the reestablishment of social and civil order.

Performance optimization for parallel processing on a multiple-CPU server

Symmetric multi-processor (SMP) systems, or multiple-CPU servers, are suitable for implementing parallel algorithms because they employ dedicated communication devices to enhance the inter-processor communication bandwidth, so that a better performance can be obtained. However, the cost for a multiple-CPU server is high and therefore, the server is usually shared among many users. The work-load due to other users will certainly affect the performance of the parallel programs so it is desirable to derive a method to optimize parallel programs under different loading conditions. In this paper, we present a simple method, which can be applied in SPMD type parallel programs, to improve the speedup by controlling the number of threads within the programs.

Bitrate modeling of scalable videos using quantization parameter, frame rate and spatial resolution

The quality and bitrate modeling is essential to effectively adapt the bitrate and quality of videos when delivered to multiplatform devices over resource constraint heterogeneous networks. The recent model proposed by Wang et al. estimates the bitrate and quality of videos in terms of the frame rate and quantization parameter. However, to build an effective video adaptation framework, it is crucial to incorporate the spatial resolution in the analytical model for bitrate and perceptual quality adaptation. Hence, this paper proposes an analytical model to estimate the bitrate of videos in terms of quantization parameter, frame rate, and spatial resolution. The model can fit the measured data accurately which is evident from the high Pearson correlation. The proposed model is based on the observation that the relative reduction in bitrate due to decreasing spatial resolution is independent of the quantization parameter and frame rate. This modeling can be used for rate-constrained bit-stream adaptation scheme which selects the scalability parameters to optimize the perceptual quality for a given bandwidth constraint.

Implementation results of efficient trajectories on a testbed AUV

In this paper we consider the implementation of time and energy efficient trajectories onto a test-bed autonomous underwater vehicle. The trajectories are losely connected to the results of the application of the maximum principle to the controlled mechanical system. We use a numerical algorithm to compute efficient trajectories designed using geometric control theory to optimize a given cost function. Experimental results are shown for the time minimization problem.

The role of assisted self-help in services for alcohol-related disorders

Potentially harmful substance use is common, but many affected people do not receive treatment. Brief face-to-face treatments show impact, as do strategies to assist self-help remotely, by using bibliotherapies, computers or mobile phones. Remotely delivered treatments offer more sustained and multifaceted support than brief interventions, and they show a substantial cost advantage as users increase in number. They may also build skills, confidence and treatment fidelity in providers who use them in sessions. Engagement and retention remain challenges, but electronic treatments show promise in engaging younger populations. Recruitment may be assisted by integration with community campaigns or brief opportunistic interventions. However, routine use of assisted self-help by standard services faces significant challenges. Strategies to optimize adoption are discussed. ----- ----- Research Highlights: ► Many people with risky or problematic drinking do not currently receive treatment. ► Assisted self-help has a significant impact and can be delivered at low cost. ► Maximal effects from assisted self-help require engagement of potential users. ► Marketing campaigns and integration into existing service models may assist.

The conversion of lignocellulosics to levulinic acid

Biomass represents an abundant and relatively low cost carbon resource that can be utilized to produce platform chemicals such as levulinic acid. Current processing technology limits the cost-effective production of levulinic acid in commercial quantities from biomass. The key to improving the yield and effi ciency of levulinic acid production from biomass lies in the ability to optimize and isolate the intermediate products at each step of the reaction pathway and reduce re-polymerization and side reactions. New technologies (including the use of microwave irradiation and ionic liquids) and the development of highly selective catalysts would provide the necessary step change for the optimization of key reactions. A processing environment that allows the use of biphasic systems and/or continuous extraction of products would increase reaction rates, yields and product quality. This review outlines the chemistry of levulinic acid synthesis and discusses current and potential technologies for producing levulinic acid from lignocellulosics.

Patient-specific computational biomechanics for simulating adolescent scoliosis surgery : predicted vs clinical correction for a preliminary series of six patients

Scoliosis is a spinal deformity that requires surgical correction in progressive cases. In order to optimize surgical outcomes, patient-specific finite element models are being developed by our group. In this paper, a single rod anterior correction procedure is simulated for a group of six scoliosis patients. For each patient, personalised model geometry was derived from low-dose CT scans, and clinically measured intra-operative corrective forces were applied. However, tissue material properties were not patient-specific, being derived from existing literature. Clinically, the patient group had a mean initial Cobb angle of 47.3 degrees, which was corrected to 17.5 degrees after surgery. The mean simulated post-operative Cobb angle for the group was 18.1 degrees. Although this represents good agreement between clinical and simulated corrections, the discrepancy between clinical and simulated Cobb angle for individual patients varied between -10.3 and +8.6 degrees, with only three of the six patients matching the clinical result to within accepted Cobb measurement error of +-5 degrees. The results of this study suggest that spinal tissue material properties play an important role in governing the correction obtained during surgery, and that patient-specific modelling approaches must address the question of how to prescribe patient-specific soft tissue properties for spine surgery simulation.

Shrinking neighborhood evolution : a novel stochastic algorithm for numerical optimization

Focusing on the conditions that an optimization problem may comply with, the so-called convergence conditions have been proposed and sequentially a stochastic optimization algorithm named as DSZ algorithm is presented in order to deal with both unconstrained and constrained optimizations. The principle is discussed in the theoretical model of DSZ algorithm, from which we present the practical model of DSZ algorithm. Practical model efficiency is demonstrated by the comparison with the similar algorithms such as Enhanced simulated annealing (ESA), Monte Carlo simulated annealing (MCS), Sniffer Global Optimization (SGO), Directed Tabu Search (DTS), and Genetic Algorithm (GA), using a set of well-known unconstrained and constrained optimization test cases. Meanwhile, further attention goes to the strategies how to optimize the high-dimensional unconstrained problem using DSZ algorithm.

Numerical simulation of flow in a photocatalytic reactor containing baffles

In this study a new immobilized flat plate photocatalytic reactor for wastewater treatment has been investigated using computational fluid dynamics (CFD). The reactor consists of a reactor inlet, a reactive section where the catalyst is coated, and outlet parts. For simulation, the reactive section of the reactor was modelled with an array of baffles. In order to optimize the fluid mixing and reactor design, this study attempts to investigate the influence of baffles with differing heights on the flow field of the flat plate reactor. The results obtained from the simulation of a baffled flat plate reactor hydrodynamics for differing baffle heights for certain positions are presented. Under the conditions simulated, the qualitative flow features, such as the distribution of local stream lines, velocity contours, and high shear region, boundary layers separation, vortex formation, and the underlying mechanism are examined. At low and high Re numbers, the influence of baffle heights on the distribution of species mass fraction of a model pollutant are also highlighted. The simulation of qualitative and quantitative properties of fluid dynamics in a baffled reactor provides valuable insight to fully understand the effect of baffles and their role on the flow pattern, behaviour, and features of wastewater treatment using a photocatalytic reactor.

CFD Simulation of turbulence promoters in a water treatment reactor

A new immobilized flat plate photocatalytic reactor for wastewater treatment has been proposed in this study to avoid subsequent catalyst removal from the treated water. The reactor consists of an inlet, reactive section where catalyst is coated and an outlet parts. In order to optimize the fluid mixing and reactor design, this study aims to investigate the influence of baffles and its arrangement on the flat plate reactor hydrodynamics using computational fluid dynamics (CFD) simulation. For simulation, an array of baffles acting as turbulence promoters is inserted in the reactive zone of the reactor. In this regard, results obtained from the simulation of a baffled- flat plate photoreactor hydrodynamics for different baffle positions, heights and intervals are presented utilizing RNG k-ε turbulence model. Under the conditions simulated, the qualitative flow features, such as the development and separation of boundary layers, vortex formation, the presence of high shear regions and recirculation zones, and the underlying mechanism are examined. The influence of various baffle sizes on the distribution of pollutant concentration is also highlighted. The results presented here indicate that the spanning of recirculation increases the degree of interfacial distortion with a larger interfacial area between fluids which results in substantial enhancement in fluid mixing. The simulation results suggest that the qualitative and quantitative properties of fluid dynamics in a baffled reactor can be obtained which provides valuable insight to fully understand the effect of baffles and its arrangements on the flow pattern, behaviour, and feature.

PCR bias Toward the wild-type k-ras and p53 sequences: Implications for PCR detection of mutations and cancer diagnosis

PCR-based cancer diagnosis requires detection of rare mutations in k- ras, p53 or other genes. The assumption has been that mutant and wild-type sequences amplify with near equal efficiency, so that they are eventually present in proportions representative of the starting material. Work on factor IX suggests that this assumption is invalid for one case of near- sequence identity. To test the generality of this phenomenon and its relevance to cancer diagnosis, primers distant from point mutations in p53 and k-ras were used to amplify wild-type and mutant sequences from these genes. A substantial bias against PCR amplification of mutants was observed for two regions of the p53 gene and one region of k-ras. For k-ras and p53, bias was observed when the wild-type and mutant sequences were amplified separately or when mixed in equal proportions before PCR. Bias was present with proofreading and non-proofreading polymerase. Mutant and wild-type segments of the factor V, cystic fibrosis transmembrane conductance regulator and prothrombin genes were amplified and did not exhibit PCR bias. Therefore, the assumption of equal PCR efficiency for point mutant and wild-type sequences is invalid in several systems. Quantitative or diagnostic PCR will require validation for each locus, and enrichment strategies may be needed to optimize detection of mutants.

Group maintenance scheduling : a case study for a pipeline network

This paper presents a group maintenance scheduling case study for a water distributed network. This water pipeline network presents the challenge of maintaining aging pipelines with the associated increases in annual maintenance costs. The case study focuses on developing an effective maintenance plan for the water utility. Current replacement planning is difficult as it needs to balance the replacement needs under limited budgets. A Maintenance Grouping Optimization (MGO) model based on a modified genetic algorithm was utilized to develop an optimum group maintenance schedule over a 20-year cycle. The adjacent geographical distribution of pipelines was used as a grouping criterion to control the searching space of the MGO model through a Judgment Matrix. Based on the optimum group maintenance schedule, the total cost was effectively reduced compared with the schedules without grouping maintenance jobs. This optimum result can be used as a guidance to optimize the current maintenance plan for the water utility.

Persistent ocean monitoring with underwater gliders : adapting sampling resolution

Ocean processes are dynamic, complex, and occur on multiple spatial and temporal scales. To obtain a synoptic view of such processes, ocean scientists collect data over long time periods. Historically, measurements were continually provided by fixed sensors, e.g., moorings, or gathered from ships. Recently, an increase in the utilization of autonomous underwater vehicles has enabled a more dynamic data acquisition approach. However, we still do not utilize the full capabilities of these vehicles. Here we present algorithms that produce persistent monitoring missions for underwater vehicles by balancing path following accuracy and sampling resolution for a given region of interest, which addresses a pressing need among ocean scientists to efficiently and effectively collect high-value data. More specifically, this paper proposes a path planning algorithm and a speed control algorithm for underwater gliders, which together give informative trajectories for the glider to persistently monitor a patch of ocean. We optimize a cost function that blends two competing factors: maximize the information value along the path, while minimizing deviation from the planned path due to ocean currents. Speed is controlled along the planned path by adjusting the pitch angle of the underwater glider, so that higher resolution samples are collected in areas of higher information value. The resulting paths are closed circuits that can be repeatedly traversed to collect long-term ocean data in dynamic environments. The algorithms were tested during sea trials on an underwater glider operating off the coast of southern California, as well as in Monterey Bay, California. The experimental results show significant improvements in data resolution and path reliability compared to previously executed sampling paths used in the respective regions.

An exercise intervention for women undergoing chemotherapy for ovarian cancer : feasibility and preliminary outcomes

Exercise interventions during adjuvant cancer treatment have been shown to increase functional capacity, relieve fatigue and distress and in one recent study, assist chemotherapy completion. These studies have been limited to breast, prostate or mixed cancer groups and it is not yet known if a similar intervention is even feasible among women diagnosed with ovarian cancer. Women undergoing treatment for ovarian cancer commonly have extensive pelvic surgery followed by high intensity chemotherapy. It is hypothesized that women with ovarian cancer may benefit most from a customised exercise intervention during chemotherapy treatment. This could reduce the number and severity of chemotherapy-related side-effects and optimize treatment adherence. Hence, the aim of the research was to assess feasibility and acceptability of a walking intervention in women with ovarian cancer whilst undergoing chemotherapy, as well as pre-post intervention changes in a range of physical and psychological outcomes. Newly diagnosed women with ovarian cancer were recruited from the Royal Brisbane and Women’s Hospital (RBWH), to participate in a walking program throughout chemotherapy. The study used a one group pre- post-intervention test design. Baseline (conducted following surgery but prior to the first or second chemotherapy cycles) and follow-up (conducted three weeks after the last chemotherapy dose was received) assessments were performed. To accommodate changes in side-effects associated with treatment, specific weekly walking targets with respect to frequency, intensity and duration, were individualised for each participant. To assess feasibility, adherence and compliance with prescribed walking sessions, withdrawals and adverse events were recorded. Physical and psychological outcomes assessed included functional capacity, body composition, anxiety and depression, symptoms experienced during treatment and quality of life. Chemotherapy completion data was also documented and self-reported program helpfulness was assessed using a questionnaire post intervention. Forty-two women were invited to participate. Nine women were recruited, all of whom completed the program. There were no adverse events associated with participating in the intervention and all women reported that the walking program was helpful during their neo-adjuvant or adjuvant chemotherapy treatment. Adherence and compliance to the walking prescription was high. On average, women achieved at least two of their three individual weekly prescription targets 83% of the time (range 42% to 94%). Positive changes were found in functional capacity and quality of life, in addition to reductions in the number and intensity of treatment-associated symptoms over the course of the intervention period. Functional capacity increased for all nine women from baseline to follow-up assessment, with improvements ranging from 10% to 51%. Quality of life improvements were also noted, especially in the physical well-being scale (baseline: median 18; follow-up: median 23). Treatment symptoms reduced in presence and severity, specifically, in constipation, pain and fatigue, post intervention. These positive yet preliminary results suggest that a walking intervention for women receiving chemotherapy for ovarian cancer is safe, feasible and acceptable. Importantly, women perceived the program to be helpful and rewarding, despite being conducted during a time typically associated with elevated distress and treatment symptoms that are often severe enough to alter or cease chemotherapy prescription.