Growing rod analysis for the fusionless correction of early onset scoliosis (EOS)

Managing spinal deformities in young children is challenging, particularly early onset scoliosis (EOS). Surgical intervention is often required if EOS has been unresponsive to conservative treatment particularly with rapidly progressive curves. An emerging treatment option for EOS is fusionless scoliosis surgery. Similar to bracing, this surgical option potentially harnesses growth, motion and function of the spine along with correcting spinal deformity. Dual growing rods are one such fusionless treatment, which aims to modulate growth of the vertebrae. The aim of this study was to ascertain the extent to which semi-constrained growing rods (Medtronic Sofamor Danek Memphis, TN, USA) with a telescopic sleeve component, reduce rotational constraint on the spine compared with standard rigid rods and hence potentially provide a more physiological mechanical environment for the growing spine. This study found that semi-constrained growing rods would be expected to allow growth via the telescopic rod components while maintaining the axial flexibility of the spine and the improved capacity for final correction.

Uncertainty quantification applied to the performance analysis of a conical diffuser

This paper offers an uncertainty quantification (UQ) study applied to the performance analysis of the ERCOFTAC conical diffuser. A deterministic CFD solver is coupled with a non-statistical generalised Polynomial Chaos(gPC)representation based on a pseudo-spectral projection method. Such approach has the advantage to not require any modification of the CFD code for the propagation of random disturbances in the aerodynamic field. The stochactic results highlihgt the importance of the inlet velocity uncertainties on the pressure recovery both alone and when coupled with a second uncertain variable. From a theoretical point of view, we investigate the possibility to build our gPC representation on arbitray grid, thus increasing the flexibility of the stochastic framework.

Adaptive finite element analysis of elliptic problems based on bubble-type local mesh generation

A new mesh adaptivity algorithm that combines a posteriori error estimation with bubble-type local mesh generation (BLMG) strategy for elliptic differential equations is proposed. The size function used in the BLMG is defined on each vertex during the adaptive process based on the obtained error estimator. In order to avoid the excessive coarsening and refining in each iterative step, two factor thresholds are introduced in the size function. The advantages of the BLMG-based adaptive finite element method, compared with other known methods, are given as follows: the refining and coarsening are obtained fluently in the same framework; the local a posteriori error estimation is easy to implement through the adjacency list of the BLMG method; at all levels of refinement, the updated triangles remain very well shaped, even if the mesh size at any particular refinement level varies by several orders of magnitude. Several numerical examples with singularities for the elliptic problems, where the explicit error estimators are used, verify the efficiency of the algorithm. The analysis for the parameters introduced in the size function shows that the algorithm has good flexibility.

Human vs. machine : identification of bat species from their echolocation calls by humans and by artificial neural networks

Automated remote ultrasound detectors allow large amounts of data on bat presence and activity to be collected. Processing of such data involves identifying bat species from their echolocation calls. Automated species identification has the potential to provide more consistent, predictable, and potentially higher levels of accuracy than identification by humans. In contrast, identification by humans permits flexibility and intelligence in identification, as well as the incorporation of features and patterns that may be difficult to quantify. We compared humans with artificial neural networks (ANNs) in their ability to classify short recordings of bat echolocation calls of variable signal to noise ratios; these sequences are typical of those obtained from remote automated recording systems that are often used in large-scale ecological studies. We presented 45 recordings (1–4 calls) produced by known species of bats to ANNs and to 26 human participants with 1 month to 23 years of experience in acoustic identification of bats. Humans correctly classified 86% of recordings to genus and 56% to species; ANNs correctly identified 92% and 62%, respectively. There was no significant difference between the performance of ANNs and that of humans, but ANNs performed better than about 75% of humans. There was little relationship between the experience of the human participants and their classification rate. However, humans with <1 year of experience performed worse than others. Currently, identification of bat echolocation calls by humans is suitable for ecological research, after careful consideration of biases. However, improvements to ANNs and the data that they are trained on may in future increase their performance to beyond those demonstrated by humans.

Using the WWW to teach undergraduate nurses clinical communication

On-line learning is increasingly being used in nursing education. Nevertheless, there is still insufficient evidence to demonstrate: whether students respond positively when this form of learning is used to teach relatively practical or clinical subjects; whether it is effective; and whether it is fair to students with less access to, or familiarity with, computers and the internet. In 2003, an on-line Unit on clinical communication was developed for Australian undergraduate nurses in partnership between an Australian School of Nursing and the a Department of Clinical Psychology. Students were overwhelmingly positive in their evaluation of the Unit although some regretted the lack of face-to-face contact with tutors and peers. The best aspects of the Unit included the content and structure being perceived as interesting, fun and informative, the relevance of the material for them as nurses, flexibility to work independently, promotion of critical thinking and gaining an understanding of client issues. Neither their evaluation nor their final grades were related to students’ age or whether they preferred on-line or traditional learning. Students who had readily available computer access, however, had better final grades. Also, students’ grades were correlated with how often they accessed the Unit.

What’s driving the uptake of prefabricated housing in Australia?

Prefabrication has been promoted as a means to improve the efficiency of the Australian house building industry. Issues affecting the uptake of prefabrication were identified through interviews with small and medium sized building companies. Prefabrication’s specific impact on housing construction and smaller organisations has not been frequently investigated. Similar past research has been conducted without the use of a clear theoretical grounding guiding the identification of relevant issues. The current study is guided by a combination of the Theory of Planned Behaviour (TPB) and the Technology Acceptance Model (TAM). This allowed the identification of a broad range of issues across attitudinal, normative, behavioural control and technology adaptation domains. Results revealed improved quality was often offset against practical cost implications. While a high quality of prefabricated products was reported, key technical challenges included coordinating the transporting of modules, and balancing standardisation and product flexibility. Resistance from traditional industry stakeholders regarding build methods, financing, and openness to encouraging prefabrication was commonly reported. The key role of government decision making in facilitating greater demand and competitiveness of prefabricated businesses in the consumer marketplace was also highlighted. Further research is currently being undertaken by the authors, which builds on the exploratory results of the current study through confirmatory, quantitative surveying.

Versatility of polymethacrylate monoliths for chromatographic purification of biomolecules

Polymethacrylate monoliths, specifically poly(glycidyl methacrylate-co-ethylene dimethacrylate) or poly(GMA-co-EDMA) monoliths, are a new generation of chromatographic supports and are significantly different from conventional particle-based adsorbents, membranes, and other monolithic supports for biomolecule purification. Similar to other monoliths, polymethacrylate monoliths possess large pores which allow convective flow of mobile phase and result in high flow rates at reduced pressure drop, unlike particulate supports. The simplicity of the adsorbent synthesis, pH resistance, and the ease and flexibility of tailoring their pore size to that of the target biomolecule are the key properties which differentiate polymethacrylate monoliths from other monoliths. Polymethacrylate monoliths are endowed with reactive epoxy groups for easy functionalization (with anion-exchange, hydrophobic, and affinity ligands) and high ligand retention. In this review, the structure and performance of polymethacrylate monoliths for chromatographic purification of biomolecules are evaluated and compared to those of other supports. The development and use of polymethacrylate monoliths for research applications have grown rapidly in recent times and have enabled the achievement of high through-put biomolecule purification on semi-preparative and preparative scales.

Practical implementation of species' recovery plans - Lessons from the White-backed Woodpecker Action Plan in Sweden

Successful biodiversity conservation requires safeguarding viable populations of species. To work with this challenge Sweden has introduced a concept of Action Plans, which focus on the recovery of one or more species; while keeping in mind the philosophy of addressing ecosystems in a more comprehensive way, following the umbrella concept. In this paper we investigate the implementationprocess of the ActionPlanfor one umbrella species, the White-backed Woodpecker (WBW) Dendrocopos leucotos. We describe the plan's organisation and goals, and investigate its implementation and accomplishment of particular targets, based on interviewing and surveying the key actors. The achievement of the targets in 2005-2008 was on average much lower than planned, explained partially by the lack of knowledge/data, experienced workers, and administrative flexibility. Surprisingly, the perceived importance of particular conservation measures, the investment priority accorded to them, the money available and various practical obstacles all failed to kg? explain the target levels achieved. However qualitative data from both the interviews and the survey highlight possible implementation obstacles: competing interests with other conservation actions and the level of engagement of particular implementing actors. Therefore we suggest that for successful implementation of recovery plans, there is aneed for initial and inclusive scoping prior to embarking on the plan, where not only issues like ecological knowledge and practical resources are considered, but also possible conflicts and synergies with other conservation actions. An adaptive approach with regular review of the conservation process is essential, particularly in the case of such complex action plans as the one for the WBW.

Regional avian species declines estimated from volunteer-collected long-term data using List Length Analysis

Long-term systematic population monitoring data sets are rare but are essential in identifying changes in species abundance. In contrast, community groups and natural history organizations have collected many species lists. These represent a large, untapped source of information on changes in abundance but are generally considered of little value. The major problem with using species lists to detect population changes is that the amount of effort used to obtain the list is often uncontrolled and usually unknown. It has been suggested that using the number of species on the list, the "list length," can be a measure of effort. This paper significantly extends the utility of Franklin's approach using Bayesian logistic regression. We demonstrate the value of List Length Analysis to model changes in species prevalence (i.e., the proportion of lists on which the species occurs) using bird lists collected by a local bird club over 40 years around Brisbane, southeast Queensland, Australia. We estimate the magnitude and certainty of change for 269 bird species and calculate the probabilities that there have been declines and increases of given magnitudes. List Length Analysis confirmed suspected species declines and increases. This method is an important complement to systematically designed intensive monitoring schemes and provides a means of utilizing data that may otherwise be deemed useless. The results of List Length Analysis can be used for targeting species of conservation concern for listing purposes or for more intensive monitoring. While Bayesian methods are not essential for List Length Analysis, they can offer more flexibility in interrogating the data and are able to provide a range of parameters that are easy to interpret and can facilitate conservation listing and prioritization. © 2010 by the Ecological Society of America.

Dynamic agent composition for large-scale agent-based models

PURPOSE: This paper describes dynamic agent composition, used to support the development of flexible and extensible large-scale agent-based models (ABMs). This approach was motivated by a need to extend and modify, with ease, an ABM with an underlying networked structure as more information becomes available. Flexibility was also sought after so that simulations are set up with ease, without the need to program. METHODS: The dynamic agent composition approach consists in having agents, whose implementation has been broken into atomic units, come together at runtime to form the complex system representation on which simulations are run. These components capture information at a fine level of detail and provide a vast range of combinations and options for a modeller to create ABMs. RESULTS: A description of the dynamic agent composition is given in this paper, as well as details about its implementation within MODAM (MODular Agent-based Model), a software framework which is applied to the planning of the electricity distribution network. Illustrations of the implementation of the dynamic agent composition are consequently given for that domain throughout the paper. It is however expected that this approach will be beneficial to other problem domains, especially those with a networked structure, such as water or gas networks. CONCLUSIONS: Dynamic agent composition has many advantages over the way agent-based models are traditionally built for the users, the developers, as well as for agent-based modelling as a scientific approach. Developers can extend the model without the need to access or modify previously written code; they can develop groups of entities independently and add them to those already defined to extend the model. Users can mix-and-match already implemented components to form large-scales ABMs, allowing them to quickly setup simulations and easily compare scenarios without the need to program. The dynamic agent composition provides a natural simulation space over which ABMs of networked structures are represented, facilitating their implementation; and verification and validation of models is facilitated by quickly setting up alternative simulations.

Performance evaluation of cloud-based parallel computing

As computational models in fields such as medicine and engineering get more refined, resource requirements are increased. In a first instance, these needs have been satisfied using parallel computing and HPC clusters. However, such systems are often costly and lack flexibility. HPC users are therefore tempted to move to elastic HPC using cloud services. One difficulty in making this transition is that HPC and cloud systems are different, and performance may vary. The purpose of this study is to evaluate cloud services as a means to minimise both cost and computation time for large-scale simulations, and to identify which system properties have the most significant impact on performance. Our simulation results show that, while the performance of Virtual CPU (VCPU) is satisfactory, network throughput may lead to difficulties.

Response of segmented bored transit tunnels to surface blast

Increasing threat of terrorism highlights the importance of enhancing the resilience of underground tunnels to all hazards. This paper develops, applies and compares the Arbitrary Lagrangian Eulerian (ALE) and Smooth Particle Hydrodynamics (SPH) techniques to treat the response of buried tunnels to surface explosions. The results and outcomes of the two techniques were compared, along with results from existing test data. The comparison shows that the ALE technique is a better method for describing the tunnel response for above ground explosion with regards to modeling accuracy and computational efficiency. The ALE technique was then applied to treat the blast response of different types of segmented bored tunnels buried in dry sand. Results indicate that the most used modern ring type segmented tunnels were more flexible for in-plane response, however, they suffered permanent drifts between the rings. Hexagonal segmented tunnels responded with negligible drifts in the longitudinal direction, but the magnitudes of in-plane drifts were large and hence hazardous for the tunnel. Interlocking segmented tunnels suffered from permanent drifts in both the longitudinal and transverse directions. Multi-surface radial joints in both the hexagonal and interlocking segments affected the flexibility of the tunnel in the transverse direction. The findings offer significant new information in the behavior of segmented bored tunnels to guide their future implementation in civil engineering applications.

Resilience and work-life balance in first-line nurse manager

Purpose The aim of this study was to explore how first-line nurse managers constructed the meaning of resilience and its relationship to work-life balance for nurses in Korea. Methods Participants were 20 first-line nurse managers working in six university hospitals. Data were collected through in-depth interviews from December 2011 to August 2012, and analyzed using Strauss and Corbin's grounded theory method. Results Analysis revealed that participants perceived work-life balance and resilience to be shaped by dynamic, reflective processes. The features consisting resilience included "positive thinking", "flexibility", "assuming responsibility", and "separating work and life". This perception of resilience has the potential to facilitate a shift in focus from negative to positive experiences, from rigidity to flexibility, from task-centered to person-centered thinking, and from the organization to life. Conclusions Recognizing the importance of work-life balance in producing and sustaining resilience in first-line nurse managers could increase retention in the Korean nursing workforce.