Expanding Emergency Department capacity : a multisite study

Objectives: To i) identify predictors of admission, and ii) describe outcomes for patients who arrived via ambulance to three Australian public Emergency Departments (EDs), before and after the opening of 41 additional ED beds within the area. Methods: A retrospective, comparative, cohort study using deterministically linked health data collected between 3 September 2006 and 2 September 2008. Data included ambulance offload delay, time to see doctor, ED length of stay (ED LOS), admission requirement, access block, hospital length of stay and in-hospital mortality. Logistic regression analysis was undertaken to identify predictors of hospital admission. Results: One third of all 286,037 ED presentations were via ambulance (n= 79,196) and 40.3% required admission. After increasing emergency capacity, the only outcome measure to improve was in-hospital mortality. Ambulance offload delay, time to see doctor, ED length of stay (ED LOS), admission requirement, access block, hospital length of stay did not improve. Strong predictors of admission before and after increased capacity included: age over 65 years, Australian Triage Scale (ATS) category 1-3, diagnoses of circulatory or respiratory conditions and ED LOS > 4 hours. With additional capacity the odds ratios for these predictors increased for age >65 and ED LOS > 4 hours and decreased for triage category and ED diagnoses. Conclusions: Expanding ED capacity from 81 to 122 beds within a health service area impacted favourably on mortality outcomes but not on time-related service outcomes such as ambulance offload time, time to see doctor and ED LOS. To improve all service outcomes, when altering (increasing/decreasing) ED bed numbers, the whole healthcare system needs to be considered.

Plasmonic Ag nanoparticles via environment-benign atmospheric microplasma electrochemistry

Atmospheric-pressure microplasma-assisted electrochemistry was used to synthesize Ag nanoparticles (NPs) for plasmonic applications. It is shown that the size and dispersion of the nanoparticles can be controlled by variation of the microplasma-assisted electrochemical process parameters such as electrolyte concentration and temperature. Moreover, Ag NP synthesis is also achieved in the absence of a stabilizer, with additional control over the dispersion and NP formation possible. As the microplasma directly reduces Ag ions in solution, the incorporation of toxic reducing agents into the electrolytic solution is unnecessary, making this an environmentally friendly fabrication technique with strong potential for the design and growth of plasmonic nanostructures for a variety of applications. These experiments therefore link microplasma-assisted electrochemical synthesis parameters with plasmonic characteristics.

Adaptive estimation of hidden semi-Markov chains with parameterised transition probabilities and exponential decaying states

This paper develops maximum likelihood (ML) estimation schemes for finite-state semi-Markov chains in white Gaussian noise. We assume that the semi-Markov chain is characterised by transition probabilities of known parametric from with unknown parameters. We reformulate this hidden semi-Markov model (HSM) problem in the scalar case as a two-vector homogeneous hidden Markov model (HMM) problem in which the state consist of the signal augmented by the time to last transition. With this reformulation we apply the expectation Maximumisation (EM ) algorithm to obtain ML estimates of the transition probabilities parameters, Markov state levels and noise variance. To demonstrate our proposed schemes, motivated by neuro-biological applications, we use a damped sinusoidal parameterised function for the transition probabilities.

A three dimensional virtual medical imaging computed tomography suite: Innovation in education

Aims: The Medical Imaging Training Immersive Environment(MITIE) Computed Tomography(CT) system is an innovative virtual reality (VR) platform that allows students to practice a range of CT techniques. The aim of this pilot study was to harvest user feedback about the educational value of teh application and inform future pedagogical development. This presentation explores the use of this technology for skills training. Background: MITIE CT is a 3D VR environment that allows students to position a patient,and set CT technical parameters including IV contrast dose and dose rate. As with VR initiatives in other health disciplines the software mimics clinical practice as much as possible and uses 3D technology to enhance immersion and realism. The software is new and was developed by the Medical Imaging Course Team at a provider University with funding from a Health Workforce Australia 'Simulated Learning Environments' grant Methods: Current third year medical imaging students were provided with additional 1 hour MITIE laboratory tutorials and studnet feedback was collated with regard to educational value and performance. Ethical approval for the project was provided by the university ethics panel Results: This presentation provides qualitative analysis of student perceptions relating to satisfaction, usability and educational value. Students reported high levels of satisfaction and both feedback and assessment results confirmed the application's significance as a pre-clinical tool. There was a clear emerging theme that MITIE could be a useful learning tool that students could access to consolidate their clinical learning, either on campus or during their clinical placement. Conclusion: Student feedback indicates that MITIE CT has a valuable role to play in the clinial skills training for medical imaging students both in the academic and clinical environment. Future work will establish a framework for an appropriate supprting pedagogy that can cross the boundary between the two environments

A comprehensive mechanistic kinetic model for dilute acid hydrolysis of switchgrass cellulose to glucose, 5-HMF and levulinic acid

Switchgrass was treated by 1% (w/w) H₂SO₄in batch tube reactors at temperatures ranging from 140–220°C for up to 60 minutes. In this study, release patterns of glucose, 5-hydroxymethylfurfural (5-HMF), and levulinic acid from switchgrass cellulose were investigated through a mechanistic kinetic model. The predictions were consistent with the measured products of interest when new parameters reflecting the effects of reaction limitations, such as cellulose crystallinity, acid soluble lignin–glucose complex (ASL–glucose) and humins that cannot be quantitatively analyzed, were included. The new mechanistic kinetic model incorporating these parameters simulated the experimental data with R² above 0.97. Results showed that glucose yield was most sensitive to variations in the parameter regarding the cellulose crystallinity at low temperatures (140–180°C), while the impact of crystallinity on the glucose yield became imperceptible at elevated temperatures (200–220 °C). Parameters related to the undesired products (e.g. ASL–glucose and humins) were the most sensitive factors compared with rate constants and other additional parameters in impacting the levulinic acid yield at elevated temperatures (200–220°C), while their impacts were negligible at 140–180°C. These new findings provide a more rational explanation for the kinetic changes in dilute acid pretreatment performance and suggest that the influences of cellulose crystallinity and undesired products including ASL–glucose and humins play key roles in determining the generation of glucose, 5-HMF and levulinic acid from biomass-derived cellulose.

Two-scale computational modelling of water flow in unsaturated soils containing irregular-shaped inclusions

The focus of this paper is two-dimensional computational modelling of water flow in unsaturated soils consisting of weakly conductive disconnected inclusions embedded in a highly conductive connected matrix. When the inclusions are small, a two-scale Richards’ equation-based model has been proposed in the literature taking the form of an equation with effective parameters governing the macroscopic flow coupled with a microscopic equation, defined at each point in the macroscopic domain, governing the flow in the inclusions. This paper is devoted to a number of advances in the numerical implementation of this model. Namely, by treating the micro-scale as a two-dimensional problem, our solution approach based on a control volume finite element method can be applied to irregular inclusion geometries, and, if necessary, modified to account for additional phenomena (e.g. imposing the macroscopic gradient on the micro-scale via a linear approximation of the macroscopic variable along the microscopic boundary). This is achieved with the help of an exponential integrator for advancing the solution in time. This time integration method completely avoids generation of the Jacobian matrix of the system and hence eases the computation when solving the two-scale model in a completely coupled manner. Numerical simulations are presented for a two-dimensional infiltration problem.

Turbulent mixed convection in a shallow enclosure with a series of heat generating components

Turbulent mixed convection flow and heat transfer in a shallow enclosure with and without partitions and with a series of block-like heat generating components is studied numerically for a range of Reynolds and Grashof numbers with a time-dependent formulation. The flow and temperature distributions are taken to be two-dimensional. Regions with the same velocity and temperature distributions can be identified assuming repeated placement of the blocks and fluid entry and exit openings at regular distances, neglecting the end wall effects. One half of such module is chosen as the computational domain taking into account the symmetry about the vertical centreline. The mixed convection inlet velocity is treated as the sum of forced and natural convection components, with the individual components delineated based on pressure drop across the enclosure. The Reynolds number is based on forced convection velocity. Turbulence computations are performed using the standard k– model and the Launder–Sharma low-Reynolds number k– model. The results show that higher Reynolds numbers tend to create a recirculation region of increasing strength in the core region and that the effect of buoyancy becomes insignificant beyond a Reynolds number of typically 5×105. The Euler number in turbulent flows is higher by about 30 per cent than that in the laminar regime. The dimensionless inlet velocity in pure natural convection varies as Gr1/3. Results are also presented for a number of quantities of interest such as the flow and temperature distributions, Nusselt number, pressure drop and the maximum dimensionless temperature in the block, along with correlations.

Load estimation with uncertainties from opportunistic sampling data: A semiparametric approach

We consider estimating the total load from frequent flow data but less frequent concentration data. There are numerous load estimation methods available, some of which are captured in various online tools. However, most estimators are subject to large biases statistically, and their associated uncertainties are often not reported. This makes interpretation difficult and the estimation of trends or determination of optimal sampling regimes impossible to assess. In this paper, we first propose two indices for measuring the extent of sampling bias, and then provide steps for obtaining reliable load estimates that minimizes the biases and makes use of informative predictive variables. The key step to this approach is in the development of an appropriate predictive model for concentration. This is achieved using a generalized rating-curve approach with additional predictors that capture unique features in the flow data, such as the concept of the first flush, the location of the event on the hydrograph (e.g. rise or fall) and the discounted flow. The latter may be thought of as a measure of constituent exhaustion occurring during flood events. Forming this additional information can significantly improve the predictability of concentration, and ultimately the precision with which the pollutant load is estimated. We also provide a measure of the standard error of the load estimate which incorporates model, spatial and/or temporal errors. This method also has the capacity to incorporate measurement error incurred through the sampling of flow. We illustrate this approach for two rivers delivering to the Great Barrier Reef, Queensland, Australia. One is a data set from the Burdekin River, and consists of the total suspended sediment (TSS) and nitrogen oxide (NO(x)) and gauged flow for 1997. The other dataset is from the Tully River, for the period of July 2000 to June 2008. For NO(x) Burdekin, the new estimates are very similar to the ratio estimates even when there is no relationship between the concentration and the flow. However, for the Tully dataset, by incorporating the additional predictive variables namely the discounted flow and flow phases (rising or recessing), we substantially improved the model fit, and thus the certainty with which the load is estimated.

Product-library-derived specification parameters in building information models augmentation

This paper conceptualizes a framework for bridging the BIM (building information modelling)-specifications divide through augmenting objects within BIM with specification parameters derived from a product library. We demonstrate how model information, enriched with data at various LODs (levels of development), can evolve simultaneously with design and construction using different representation of a window object embedded in a wall as lifecycle phase exemplars at different levels of granularity. The conceptual standpoint is informed by the need for exploring a methodological approach which extends beyond current limitations of current modelling platforms in enhancing the information content of BIM models. Therefore, this work demonstrates that BIM objects can be augmented with construction specification parameters leveraging product libraries.

Evaluation of ELISA coupled with Western blot as a surveillance tool for Trichinella infection in wild boar (Sus scrofa)

Trichinella surveillance in wildlife relies on muscle digestion of large samples which are logistically difficult to store and transport in remote and tropical regions as well as labour-intensive to process. Serological methods such as enzyme-linked immunosorbent assays (ELISAs) offer rapid, cost-effective alternatives for surveillance but should be paired with additional tests because of the high false-positive rates encountered in wildlife. We investigated the utility of ELISAs coupled with Western blot (WB) in providing evidence of Trichinella exposure or infection in wild boar. Serum samples were collected from 673 wild boar from a high- and low-risk region for Trichinella introduction within mainland Australia, which is considered Trichinella-free. Sera were examined using both an 'in-house' and a commercially available indirect-ELISA that used excretory secretory (E/S) antigens. Cut-off values for positive results were determined using sera from the low-risk population. All wild boar from the high-risk region (352) and 139/321 (43.3%) of the wild boar from the low-risk region were tested by artificial digestion. Testing by Western blot using E/S antigens, and a Trichinella-specific real-time PCR was also carried out on all ELISA-positive samples. The two ELISAs correctly classified all positive controls as well as one naturally infected wild boar from Gabba Island in the Torres Strait. In both the high- and low-risk populations, the ELISA results showed substantial agreement (k-value = 0.66) that increased to very good (k-value = 0.82) when WB-positive only samples were compared. The results of testing sera collected from the Australian mainland showed the Trichinella seroprevalence was 3.5% (95% C.I. 0.0-8.0) and 2.3% (95% C.I. 0.0-5.6) using the in-house and commercial ELISA coupled with WB respectively. These estimates were significantly higher (P < 0.05) than the artificial digestion estimate of 0.0% (95% C.I. 0.0-1.1). Real-time PCR testing of muscle from seropositive animals did not detect Trichinella DNA in any mainland animals, but did reveal the presence of a second larvae-positive wild boar on Gabba Island, supporting its utility as an alternative, highly sensitive method in muscle examination. The serology results suggest Australian wildlife may have been exposed to Trichinella parasites. However, because of the possibility of non-specific reactions with other parasitic infections, more work using well-defined cohorts of positive and negative samples is required. Even if the specificity of the ELISAs is proven to be low, their ability to correctly classify the small number of true positive sera in this study indicates utility in screening wild boar populations for reactive sera which can be followed up with additional testing. (C) 2013 Elsevier B.V. All rights reserved.

Dark-energy constraints and correlations with systematics from CFHTLS weak lensing, SNLS supernovae Ia and WMAP5

Aims We combine measurements of weak gravitational lensing from the CFHTLS-Wide survey, supernovae Ia from CFHT SNLS and CMB anisotropies from WMAP5 to obtain joint constraints on cosmological parameters, in particular, the dark-energy equation-of-state parameter w. We assess the influence of systematics in the data on the results and look for possible correlations with cosmological parameters. Methods We implemented an MCMC algorithm to sample the parameter space of a flat CDM model with a dark-energy component of constant w. Systematics in the data are parametrised and included in the analysis. We determine the influence of photometric calibration of SNIa data on cosmological results by calculating the response of the distance modulus to photometric zero-point variations. The weak lensing data set is tested for anomalous field-to-field variations and a systematic shape measurement bias for high-redshift galaxies. Results Ignoring photometric uncertainties for SNLS biases cosmological parameters by at most 20% of the statistical errors, using supernovae alone; the parameter uncertainties are underestimated by 10%. The weak-lensing field-to-field variance between 1 deg2-MegaCam pointings is 5-15% higher than predicted from N-body simulations. We find no bias in the lensing signal at high redshift, within the framework of a simple model, and marginalising over cosmological parameters. Assuming a systematic underestimation of the lensing signal, the normalisation increases by up to 8%. Combining all three probes we obtain -0.10 < 1 + w < 0.06 at 68% confidence ( -0.18 < 1 + w < 0.12 at 95%), including systematic errors. Our results are therefore consistent with the cosmological constant . Systematics in the data increase the error bars by up to 35%; the best-fit values change by less than 0.15.

Prognostic tumour markers in pancreatic cancer

Background. Pancreatic cancer is one of the major causes of cancer death in the industrialised world. The overall survival of patients with ductal pancreatic adenocarcinoma is poor: 5-year survival is only 0.2 to 4%. Tumour stage and histological grade are used as prognostic markers in pancreatic cancer. However, there are differences in survival within stages and histological grades. New, additional and more accurate prognostic tools are needed. Aims. The purpose of this study was to investigate whether the tissue expression of potential and promising tumour markers p27, tenascin C, syndecan-1, COX-2 and MMP-2 are associated with clinicopathological parameters in pancreatic cancer. The expression of p27, tenascin C and syndecan-1 was also evaluated in acute and chronic pancreatitis. The main purpose in the study was to find new prognostic markers for pancreatic adenocarcinoma. Patients. The study included 147 patients with histologically verified pancreatic adenocarcinoma treated at Helsinki University Central Hospital from 1974 to1998. Methods. The expression of tumour marker antigens was demonstrated by immunohistochemistry using monoclonal antibodies against p27, syndecan-1, tenascin C, COX-2 and MMP-2. The results were compared with clinicopathological variables, i.e. age, sex, TNM stage and histological grade. Survival analyses were performed with univariate Kaplan-Meier life-tables and the log-rank test, while multivariate analyses were performed using Cox regression. Results. Pancreatic adenocarcinomas expressed p27, syndecan-1, tenascin C, COX-2 and MMP-2 in 30, 94, 92, 36 and 50% of the samples, respectively. Loss of p27 expression was associated with poor prognosis in stage I and II pancreatic cancer. Stromal syndecan-1 expression was an independent prognostic marker in pancreatic cancer, whereas epithelial syndecan-1 expression predicted better prognosis only in stage I and II disease. Tenascin C expression did not correlate with survival but was associated with differentiation. COX-2 expression was associated with poor outcome and was an independent prognostic factor. Epithelial MMP-2 correlated with poor prognosis in pancreatic cancer. Conclusion: p27 and epithelial syndecan-1 are prognostic markers in early (stage I and II) pancreatic cancer. Stromal syndecan-1, COX-2 and epithelial MMP-2 are prognostic factors in ductal pancreatic adenocarcinoma.

Primordial Isocurvature Perturbation in Light of CMB and LSS Data

The increased accuracy in the cosmological observations, especially in the measurements of the comic microwave background, allow us to study the primordial perturbations in grater detail. In this thesis, we allow the possibility for a correlated isocurvature perturbations alongside the usual adiabatic perturbations. Thus far the simplest six parameter \Lambda CDM model has been able to accommodate all the observational data rather well. However, we find that the 3-year WMAP data and the 2006 Boomerang data favour a nonzero nonadiabatic contribution to the CMB angular power sprctrum. This is primordial isocurvature perturbation that is positively correlated with the primordial curvature perturbation. Compared with the adiabatic \Lambda CMD model we have four additional parameters describing the increased complexity if the primordial perturbations. Our best-fit model has a 4% nonadiabatic contribution to the CMB temperature variance and the fit is improved by \Delta\chi^2 = 9.7. We can attribute this preference for isocurvature to a feature in the peak structure of the angular power spectrum, namely, the widths of the second and third acoustic peak. Along the way, we have improved our analysis methods by identifying some issues with the parametrisation of the primordial perturbation spectra and suggesting ways to handle these. Due to the improvements, the convergence of our Markov chains is improved. The change of parametrisation has an effect on the MCMC analysis because of the change in priors. We have checked our results against this and find only marginal differences between our parametrisation.

Glycoprotein Interactions in the Assembly of Hantaviruses

Hantaviruses are one of the five genera of the vector-borne virus family Bunyaviridae. While other members of the family are transmitted via arthropods, hantaviruses are carried and transmitted by rodents and insectivores. Occasional transmission to humans occurs via inhalation of aerosolized rodent excreta. When transmitted to man hantaviruses cause hemorrhagic fever with renal syndrome (HFRS, in Eurasia, mortality ~10%) and hantavirus cardiopulmonary syndrome (HCPS, in the Americas, mortality ~40%). The single-stranded, negative-sense RNA genome of hantaviruses is in segments S, M and L that respectively encode for nucleocapsid (N), glycoproteins Gn and Gc, and RNA-dependent RNA-polymerase (RdRp or L protein). The genome segments, encapsidated by N protein to form ribonucleoprotein (RNP), are enclosed inside a lipid envelope decorated by spikes formed of Gn and Gc. The focus of this study was to understand the mechanisms and interactions through which the virion is formed and maintained. We observed that when extracted from virions both Gn and Gc favor homo- over hetero-oligomerization. The minimal glycoprotein complexes extracted from virion by detergent were observed, by using ultracentrifugation and gel filtration, to be tetrameric Gn and homodimeric Gc. These results led us to suggest a model where tetrameric Gn complexes are interconnected through homodimeric Gc units to form the grid-like surface architecture described for hantaviruses. This model was found to correlate with the three-dimensional (3D) reconstruction of virion surface created using cryo-electron tomography (cryo-ET). The 3D-density map showed the spike complex formed of Gn and Gc to be 10 nm high and to display a four-fold symmetry with dimensions of 15 nm times 15 nm. This unique square-shaped complex on a roughly round virion creates a hitch for the assembly, since a sphere cannot be broken into rectangles. Thus additional interactions are likely required for the virion assembly. In cryo-ET we observed that the RNP makes occasional contacts to the viral membrane, suggesting an interaction between the spike and RNP. We were able to demonstrate this interaction using various techniques, and showed that both Gn and Gc contribute to the interaction. This led us to suggest that in addition to the interactions between Gn and Gc, also the interaction between spike and RNP is required for assembly. We found galectin-3 binding protein (referred to as 90K) to co-purify with the virions and showed an interaction between 90K and the virion. Analysis of plasma samples taken from patients hospitalized for Puumala virus infection showed increased concentrations of 90K in the acute phase and the increased 90K level was found to correlate with several parameters that reflect the severity of acute HFRS. The results of these studies confirmed, but also challenged some of the dogmas on the structure and assembly of hantaviruses. We confirmed that Gn and RNP do interact, as long assumed. On the other hand we demonstrated that the glycoproteins Gn and Gc exist as homo-oligomers or appear in large hetero-oligomeric complexes, rather than form primarily heterodimers as was previously assumed. This work provided new insight into the structure and assembly of hantaviruses.

Monitoring Indigenous Tropical Montane Forests in the Taita Hills Using Airborne Digital Camera Imagery

The loss and degradation of forest cover is currently a globally recognised problem. The fragmentation of forests is further affecting the biodiversity and well-being of the ecosystems also in Kenya. This study focuses on two indigenous tropical montane forests in the Taita Hills in southeastern Kenya. The study is a part of the TAITA-project within the Department of Geography in the University of Helsinki. The study forests, Ngangao and Chawia, are studied by remote sensing and GIS methods. The main data includes black and white aerial photography from 1955 and true colour digital camera data from 2004. This data is used to produce aerial mosaics from the study areas. The land cover of these study areas is studied by visual interpretation, pixel-based supervised classification and object-oriented supervised classification. The change of the forest cover is studied with GIS methods using the visual interpretations from 1955 and 2004. Furthermore, the present state of the study forests is assessed with leaf area index and canopy closure parameters retrieved from hemispherical photographs as well as with additional, previously collected forest health monitoring data. The canopy parameters are also compared with textural parameters from digital aerial mosaics. This study concludes that the classification of forest areas by using true colour data is not an easy task although the digital aerial mosaics are proved to be very accurate. The best classifications are still achieved with visual interpretation methods as the accuracies of the pixel-based and object-oriented supervised classification methods are not satisfying. According to the change detection of the land cover in the study areas, the area of indigenous woodland in both forests has decreased in 1955 2004. However in Ngangao, the overall woodland area has grown mainly because of plantations of exotic species. In general, the land cover of both study areas is more fragmented in 2004 than in 1955. Although the forest area has decreased, forests seem to have a more optimistic future than before. This is due to the increasing appreciation of the forest areas.