Supine to standing Cobb angle change in idiopathic scoliosis : the effect of endplate pre-selection

Background Supine imaging modalities provide valuable 3D information on scoliotic anatomy, but the altered spine geometry between the supine and standing positions affects the Cobb angle measurement. Previous studies report a mean 7°-10° Cobb angle increase from supine to standing, but none have reported the effect of endplate pre-selection or whether other parameters affect this Cobb angle difference. Methods Cobb angles from existing coronal radiographs were compared to those on existing low-dose CT scans taken within three months of the reference radiograph for a group of females with adolescent idiopathic scoliosis. Reformatted coronal CT images were used to measure supine Cobb angles with and without endplate pre-selection (end-plates selected from the radiographs) by two observers on three separate occasions. Inter and intra-observer measurement variability were assessed. Multi-linear regression was used to investigate whether there was a relationship between supine to standing Cobb angle change and eight variables: patient age, mass, standing Cobb angle, Risser sign, ligament laxity, Lenke type, fulcrum flexibility and time delay between radiograph and CT scan. Results Fifty-two patients with right thoracic Lenke Type 1 curves and mean age 14.6 years (SD 1.8) were included. The mean Cobb angle on standing radiographs was 51.9° (SD 6.7). The mean Cobb angle on supine CT images without pre-selection of endplates was 41.1° (SD 6.4). The mean Cobb angle on supine CT images with endplate pre-selection was 40.5° (SD 6.6). Pre-selecting vertebral endplates increased the mean Cobb change by 0.6° (SD 2.3, range −9° to 6°). When free to do so, observers chose different levels for the end vertebrae in 39% of cases. Multi-linear regression revealed a statistically significant relationship between supine to standing Cobb change and fulcrum flexibility (p = 0.001), age (p = 0.027) and standing Cobb angle (p < 0.001). The 95% confidence intervals for intra-observer and inter-observer measurement variability were 3.1° and 3.6°, respectively. Conclusions Pre-selecting vertebral endplates causes minor changes to the mean supine to standing Cobb change. There is a statistically significant relationship between supine to standing Cobb change and fulcrum flexibility such that this difference can be considered a potential alternative measure of spinal flexibility.

The effect of endplate preselection when measuring supine versus standing cobb angle change in idiopathic scoliosis

The primary aim of this study was to determine whether endplate pre-selection makes a difference to the Cobb Angle change between supine and standing which is known to occur in idiopathic scoliosis. A secondary aim of this study was to identify which (if any) patient characteristics were correlated with supine versus standing Cobb change. The study found that pre-selecting vertebral endplates causes only has a minor effect on supine to standing Cobb change in scoliosis. There is a statistically significant relationship between supine to standing Cobb Angle change and fulcrum flexibility. Therefore, supine to standing Cobb Angle change can be considered as a measure of spinal flexibility when both standing and supine images are clinically available.

Large-scale analysis of soccer matches using spatiotemporal tracking data

Although the collection of player and ball tracking data is fast becoming the norm in professional sports, large-scale mining of such spatiotemporal data has yet to surface. In this paper, given an entire season's worth of player and ball tracking data from a professional soccer league (approx 400,000,000 data points), we present a method which can conduct both individual player and team analysis. Due to the dynamic, continuous and multi-player nature of team sports like soccer, a major issue is aligning player positions over time. We present a "role-based" representation that dynamically updates each player's relative role at each frame and demonstrate how this captures the short-term context to enable both individual player and team analysis. We discover role directly from data by utilizing a minimum entropy data partitioning method and show how this can be used to accurately detect and visualize formations, as well as analyze individual player behavior.

Understanding Uncertainties in Non-Linear Population Trajectories: A Bayesian Semi-Parametric Hierarchical Approach to Large-Scale Surveys of Coral Cover

Recently, attempts to improve decision making in species management have focussed on uncertainties associated with modelling temporal fluctuations in populations. Reducing model uncertainty is challenging; while larger samples improve estimation of species trajectories and reduce statistical errors, they typically amplify variability in observed trajectories. In particular, traditional modelling approaches aimed at estimating population trajectories usually do not account well for nonlinearities and uncertainties associated with multi-scale observations characteristic of large spatio-temporal surveys. We present a Bayesian semi-parametric hierarchical model for simultaneously quantifying uncertainties associated with model structure and parameters, and scale-specific variability over time. We estimate uncertainty across a four-tiered spatial hierarchy of coral cover from the Great Barrier Reef. Coral variability is well described; however, our results show that, in the absence of additional model specifications, conclusions regarding coral trajectories become highly uncertain when considering multiple reefs, suggesting that management should focus more at the scale of individual reefs. The approach presented facilitates the description and estimation of population trajectories and associated uncertainties when variability cannot be attributed to specific causes and origins. We argue that our model can unlock value contained in large-scale datasets, provide guidance for understanding sources of uncertainty, and support better informed decision making

Exploring the effect of political risks in large infrastructure projects in politically unstable countries using a probabilistic modelling approach

This research aims to explore and identify political risks on a large infrastructure project in an exaggerated environment to ascertain whether sufficient objective information can be gathered by project managers to utilise risk modelling techniques. During the study, the author proposes a new definition of political risk; performs a detailed project study of the Neelum Jhelum Hydroelectric Project in Pakistan; implements a probabilistic model using the principle of decomposition and Bayes probabilistic theorem and answers the question: was it possible for project managers to obtain all the relevant objective data to implement a probabilistic model?

Longitudinal performance of polycaprolactone-based scaffold plus recombinant human morphogenetic protein-2 (rhBMP-2) in large preclinical animal model : 6- versus 12 months

There is strong current interest in the use of biodegradable scaffolds in combination with bone growth factors as a valuable alternative to the current gold standard autograft in spinal fusion surgery Yong et al. (2013). Here we report on 6- vs 12- month data set evaluating the longitudinal performance of a CaP coated polycaprolactone (PCL) scaffold loaded with recombinant human bone morphogenetic protein-2 (rhBMP-2) as a bone graft substitute within a preclinical ovine thoracic spine. The results of this study demonstrate the efficacy of scaffold-based delivery of rhBMP-2 in promoting higher fusion grades at 6- and 12- months in comparison to the scaffold alone or autograft group within the same time frame. Fusion grades achieved at six months using PCL+rhBMP-2 are not significantly increased at twelve months post surgery.

Large scale multiuser digital mind mapping tool : a study in usability

Project work can involve multiple people from varying disciplines coming together to solve problems as a group. Large scale interactive displays are presenting new opportunities to support such interactions with interactive and semantically enabled cooperative work tools such as intelligent mind maps. In this paper, we present a novel digital, touch-enabled mind-mapping tool as a first step towards achieving such a vision. This first prototype allows an evaluation of the benefits of a digital environment for a task that would otherwise be performed on paper or flat interactive surfaces. Observations and surveys of 12 participants in 3 groups allowed the formulation of several recommendations for further research into: new methods for capturing text input on touch screens; inclusion of complex structures; multi-user environments and how users make the shift from single- user applications; and how best to navigate large screen real estate in a touch-enabled, co-present multi-user setting.

Estimating the impact of reduced inertia on frequency stability due to large-scale wind penetration in Australian electricity network

Large-scale integration of non-inertial generators such as wind farms will create frequency stability issues due to reduced system inertia. Inertia based frequency stability study is important to predict the performance of power system with increased level of renewables. This paper focuses on the impact large-scale wind penetration on frequency stability of the Australian Power Network. MATLAB simulink is used to develop a frequency based dynamic model utilizing the network data from a simplified 14-generator Australian power system. The loss of generation is modeled as the active power disturbance and minimum inertia required to maintain the frequency stability is determined for five-area power system.

The BAD project: data mining, database and prediction of protein adsorption on surfaces

Protein adsorption at solid-liquid interfaces is critical to many applications, including biomaterials, protein microarrays and lab-on-a-chip devices. Despite this general interest, and a large amount of research in the last half a century, protein adsorption cannot be predicted with an engineering level, design-orientated accuracy. Here we describe a Biomolecular Adsorption Database (BAD), freely available online, which archives the published protein adsorption data. Piecewise linear regression with breakpoint applied to the data in the BAD suggests that the input variables to protein adsorption, i.e., protein concentration in solution; protein descriptors derived from primary structure (number of residues, global protein hydrophobicity and range of amino acid hydrophobicity, isoelectric point); surface descriptors (contact angle); and fluid environment descriptors (pH, ionic strength), correlate well with the output variable-the protein concentration on the surface. Furthermore, neural network analysis revealed that the size of the BAD makes it sufficiently representative, with a neural network-based predictive error of 5% or less. Interestingly, a consistently better fit is obtained if the BAD is divided in two separate sub-sets representing protein adsorption on hydrophilic and hydrophobic surfaces, respectively. Based on these findings, selected entries from the BAD have been used to construct neural network-based estimation routines, which predict the amount of adsorbed protein, the thickness of the adsorbed layer and the surface tension of the protein-covered surface. While the BAD is of general interest, the prediction of the thickness and the surface tension of the protein-covered layers are of particular relevance to the design of microfluidics devices.

Some comparison on whole-proteome phylogeny of large dsDNA viruses based on dynamical language approach and feature frequency profiles method

There has been a growing interest in alignment-free methods for phylogenetic analysis using complete genome data. Among them, CVTree method, feature frequency profiles method and dynamical language approach were used to investigate the whole-proteome phylogeny of large dsDNA viruses. Using the data set of large dsDNA viruses from Gao and Qi (BMC Evol. Biol. 2007), the phylogenetic results based on the CVTree method and the dynamical language approach were compared in Yu et al. (BMC Evol. Biol. 2010). In this paper, we first apply dynamical language approach to the data set of large dsDNA viruses from Wu et al. (Proc. Natl. Acad. Sci. USA 2009) and compare our phylogenetic results with those based on the feature frequency profiles method. Then we construct the whole-proteome phylogeny of the larger dataset combining the above two data sets. According to the report of The International Committee on the Taxonomy of Viruses (ICTV), the trees from our analyses are in good agreement to the latest classification of large dsDNA viruses.

Teaching and Assessing Reflective Writing in a Large Undergraduate Core Substantive Law Unit

The focus of higher education has shifted towards building students’ skills and self-awareness for future employment, in addition to developing substantive discipline knowledge. This means that there is an increasing need for embedding approaches to teaching and learning which provide a context for skills development and opportunities for students to prepare for the transition from legal education to professional practice. This chapter reports on a large (500-600 students) core undergraduate Equity law unit in an Australian University. ePortfolio has been embedded in Equity as a means of enabling students to document their reflections on their skill development in that unit. Students are taught, practice and are assessed on their teamwork and letter writing skills in the context of writing a letter of advice to a fictional client in response to a real world problem. Following submission of the team letter, students are asked to reflect on their skill development and document their reflections in ePortfolio. A scaffolded approach to teaching reflective writing is adopted using a blended model of delivery which combines face to face lectures and online resources, including an online module, facts sheets designed to guide students through the process of reflection by following the TARL model of reflection, and exemplars of reflective writing. Although students have engaged in the process of reflective writing in Equity for some years, in semester one 2011 assessment criteria were developed and the ePortfolio reflections were summatively assessed for the first time. The model of teaching and assessing reflective practice was evaluated in a range of ways by seeking feedback from students and academic staff responsible for implementing the model and asking them to reflect on their experiences. This chapter describes why skill development and reflective writing were embedded in the undergraduate law unit Equity; identify the teaching and learning approaches which were implemented to teach reflective writing to online and internal Equity students; explain the assessment processes; analyse the empirical evidence from evaluations; document the lessons learnt and discuss planned future improvements to the teaching and assessment strategies.

Large Scale Simulations of Hippocampal-Neocortical Interactions in a Parallel Version of Genesis

A hippocampal-CA3 memory model was constructed with PGENESIS, a recently developed version of GENESIS that allows for distributed processing of a neural network simulation. A number of neural models of the human memory system have identified the CA3 region of the hippocampus as storing the declarative memory trace. However, computational models designed to assess the viability of the putative mechanisms of storage and retrieval have generally been too abstract to allow comparison with empirical data. Recent experimental evidence has shown that selective knock-out of NMDA receptors in the CA1 of mice leads to reduced stability of firing specificity in place cells. Here a similar reduction of stability of input specificity is demonstrated in a biologically plausible neural network model of the CA3 region, under conditions of Hebbian synaptic plasticity versus an absence of plasticity. The CA3 region is also commonly associated with seizure activity. Further simulations of the same model tested the response to continuously repeating versus randomized nonrepeating input patterns. Each paradigm delivered input of equal intensity and duration. Non-repeating input patterns elicited a greater pyramidal cell spike count. This suggests that repetitive versus non-repeating neocortical inpus has a quantitatively different effect on the hippocampus. This may be relevant to the production of independent epileptogenic zones and the process of encoding new memories.

A thermal expulsion approach to homogeneous large-volume methacrylate monolith preparation; enabling large-scale rapid purification of biomolecules

Numerous efforts have been dedicated to the synthesis of large-volume methacrylate monoliths for large-scale biomolecules purification but most were obstructed by the enormous release of exotherms during preparation, thereby introducing structural heterogeneity in the monolith pore system. A significant radial temperature gradient develops along the monolith thickness, reaching a terminal temperature that supersedes the maximum temperature required for structurally homogenous monoliths preparation. The enormous heat build-up is perceived to encompass the heat associated with initiator decomposition and the heat released from free radical-monomer and monomer-monomer interactions. The heat resulting from the initiator decomposition was expelled along with some gaseous fumes before commencing polymerization in a gradual addition fashion. Characteristics of 80 mL monolith prepared using this technique was compared with that of a similar monolith synthesized in a bulk polymerization mode. An extra similarity in the radial temperature profiles was observed for the monolith synthesized via the heat expulsion technique. A maximum radial temperature gradient of only 4.3°C was recorded at the center and 2.1°C at the monolith peripheral for the combined heat expulsion and gradual addition technique. The comparable radial temperature distributions obtained birthed identical pore size distributions at different radial points along the monolith thickness.