Planning volunteer responses to low-volume mass gatherings: do event characteristics predict patient workload?

INTRODUCTION: Workforce planning for first aid and medical coverage of mass gatherings is hampered by limited research. In particular, the characteristics and likely presentation patterns of low-volume mass gatherings of between several hundred to several thousand people are poorly described in the existing literature. OBJECTIVES: This study was conducted to: 1. Describe key patient and event characteristics of medical presentations at a series of mass gatherings, including events smaller than those previously described in the literature; 2. Determine whether event type and event size affect the mean number of patients presenting for treatment per event, and specifically, whether the 1:2,000 deployment rule used by St John Ambulance Australia is appropriate; and 3. Identify factors that are predictive of injury at mass gatherings. METHODS: A retrospective, observational, case-series design was used to examine all cases treated by two Divisions of St John Ambulance (Queensland) in the greater metropolitan Brisbane region over a three-year period (01 January 2002-31 December 2004). Data were obtained from routinely collected patient treatment forms completed by St John officers at the time of treatment. Event-related data (e.g., weather, event size) were obtained from event forms designed for this study. Outcome measures include: total and average number of patient presentations for each event; event type; and event size category. Descriptive analyses were conducted using chi-square tests, and mean presentations per event and event type were investigated using Kruskal-Wallis tests. Logistic regression analyses were used to identify variables independently associated with injury presentation (compared with non-injury presentations). RESULTS: Over the three-year study period, St John Ambulance officers treated 705 patients over 156 separate events. The mean number of patients who presented with any medical condition at small events (less than or equal to 2,000 attendees) did not differ significantly from that of large (>2,000 attendees) events (4.44 vs. 4.67, F = 0.72, df = 1, 154, p = 0.79). Logistic regression analyses indicated that presentation with an injury compared with non-injury was independently associated with male gender, winter season, and sporting events, even after adjusting for relevant variables. CONCLUSIONS: In this study of low-volume mass gatherings, a similar number of patients sought medical treatment at small (<2,000 patrons) and large (>2,000 patrons) events. This demonstrates that for low-volume mass gatherings, planning based solely on anticipated event size may be flawed, and could lead to inappropriate levels of first-aid coverage. This study also highlights the importance of considering other factors, such as event type and patient characteristics, when determining appropriate first-aid resourcing for low-volume events. Additionally, identification of factors predictive of injury presentations at mass gatherings has the potential to significantly enhance the ability of event coordinators to plan effective prevention strategies and response capability for these events.

An enhanced mill extraction model

An enhanced mill extraction model has been developed to calculate mill performance parameters and to predict the extraction performance of a milling unit. The model takes into account the fibre suspended in juice streams and calculates filling ratio, reabsorption factor, imbibition coefficient, and separation efficiency using more complete definitions than those used in previous extraction models. A mass balance model is used to determine the fibre, brix and moisture mass flows between milling units so that a complete milling train, including the return stream from the juice screen, is modelled. Model solutions are presented to determine the effect of different levels of fibre in juice and efficiency of fibre separation in the juice screen on brix extraction. The model provides more accurate results than earlier models leading to better understanding and improvement of the milling process.

Heat and mass transfer modeling of the osmo-convective drying of yacon roots (Smallanthus sonchifolius)

Osmotic treatments are often applied prior to convective drying of foods to impart sensory appeal aspects. During this process a multicomponent mass flow, composed mainly of water and osmotic agent, takes place. In this work, a heat and mass transfer model for the osmo-convective drying of yacon was developed and solved by the Finite Element Method using COMSOL Multiphysics®, considering a 2-D axisymmetric geometry and moisture dependent thermophysical properties. Yacon slices were osmotically dehydrated for 2 hours in a solution of sucralose and then dried in a tray dryer for 3 hours. The model was validated by experimental data of temperature, moisture content and sucralose uptake (R²> 0.90).

Modelling the flow of cane constituents in the milling process

A model has been developed to track the flow of cane constituents through the milling process. While previous models have tracked the flow of fibre, brix and water through the process, this model tracks the soluble and insoluble solid cane components using modelling theory and experiment data, assisting in further understanding the flow of constituents into mixed juice and final bagasse. The work provided an opportunity to understand the factors which affect the distribution of the cane constituents in juice and bagasse. Application of the model should lead to improvements in the overall performance of the milling train.

Encapsulation of transition metal species into zeolites and molecular sieves as redox catalysts: Part I-preparation and characterisation of nanosized TiO2, CdO and ZnO semiconductor particles anchored in NaY zeolite

In this paper, we report the preparation and characterisation of nanometer-sized TiO2, CdO, and ZnO semiconductor particles trapped in zeolite NaY. Preparation of these particles was carried out via the traditional ion exchange method and subsequent calcination procedure. It was found that the smaller cations, i.e., Cd2+ and Zn2+ could be readily introduced into the SI′ and SII′ sites located in the sodalite cages, through ion exchange; while this is not the case for the larger Ti species, i.e., Ti monomer [TiO]2+ or dimer [Ti2O3]2+ which were predominantly dispersed on the external surface of zeolite NaY. The subsequent calcination procedure promoted these Ti species to migrate into the internal surface of the supercages. These semiconductor particles confined in NaY zeolite host exhibited a significant blue shift in the UV-VIS absorption spectra, in contrast to the respective bulk semiconductor materials, due to the quantum size effect (QSE). The particle sizes calculated from the UV-VIS optical absorption spectra using the effective mass approximation model are in good agreement with the atomic absorption data.

Temperature redistribution modelling during intermittent microwave convective heating

Microwave power is used for heating and drying processes because of its faster and volumetric heating capability. Non-uniform temperature distribution during microwave application is a major drawback of these processes. Intermittent application of microwave potentially reduces the impact of non-uniformity and improves energy efficiency by redistributing the temperature. However, temperature re-distribution during intermittent microwave heating has not been investigated adequately. Consequently, in this study, a coupled electromagnetic with heat and mass transfer model was developed using the finite element method embedded in COMSOL-Multyphysics software. Particularly, the temperature redistribution due to intermittent heating was investigated. A series of experiments were performed to validate the simulation. The test specimen was an apple and the temperature distribution was closely monitored by a TIC (Thermal Imaging Camera). The simulated temperature profile matched closely with thermal images obtained from experiments.

Multiphase porous media model for heat and mass transfer during drying of agricultural products

Modelling of food processing is complex because it involves sophisticated material and transport phenomena. Most of the agricultural products such fruits and vegetables are hygroscopic porous media containing free water, bound water, gas and solid matrix. Considering all phase in modelling is still not developed. In this article, a comprehensive porous media model for drying has been developed considering bound water, free water separately, as well as water vapour and air. Free water transport was considered as diffusion, pressure driven and evaporation. Bound water assumed to be converted to free water due to concentration difference and also can diffuse. Binary diffusion between water vapour and air was considered. Since, the model is fundamental physics based it can be applied to any drying applications and other food processing where heat and mass transfer takes place in porous media with significant evaporation and other phase change.

Micropolar flow in a porous channel with high mass transfer

Two dimensional flow of a micropolar fluid in a porous channel is investigated. The flow is driven by suction or injection at the channel walls, and the micropolar model due to Eringen is used to describe the working fluid. An extension of Berman's similarity transform is used to reduce the governing equations to a set of non-linear coupled ordinary differential equations. The latter are solved for large mass transfer via a perturbation analysis where the inverse of the cross-flow Reynolds number is used as the perturbing parameter. Complementary numerical solutions for strong injection are also obtained using a quasilinearisation scheme, and good agreement is observed between the solutions obtained from the perturbation analysis and the computations.

Development of a particle number and particle mass vehicle emissions inventory for an urban fleet

Motor vehicles are major emitters of gaseous and particulate pollution in urban areas, and exposure to particulate pollution can have serious health effects, ranging from respiratory and cardiovascular disease to mortality. Motor vehicle tailpipe particle emissions span a broad size range from 0.003-10µm, and are measured as different subsets of particle mass concentrations or particle number count. However, no comprehensive inventories currently exist in the international published literature covering this wide size range. This paper presents the first published comprehensive inventory of motor vehicle tailpipe particle emissions covering the full size range of particles emitted. The inventory was developed for urban South-East Queensland by combining two techniques from distinctly different disciplines, from aerosol science and transport modelling. A comprehensive set of particle emission factors were combined with traffic modelling, and tailpipe particle emissions were quantified for particle number (ultrafine particles), PM1, PM2.5 and PM10 for light and heavy duty vehicles and buses. A second aim of the paper involved using the data derived in this inventory for scenario analyses, to model the particle emission implications of different proportions of passengers travelling in light duty vehicles and buses in the study region, and to derive an estimate of fleet particle emissions in 2026. It was found that heavy duty vehicles (HDVs) in the study region were major emitters of particulate matter pollution, and although they contributed only around 6% of total regional vehicle kilometres travelled, they contributed more than 50% of the region’s particle number (ultrafine particles) and PM1 emissions. With the freight task in the region predicted to double over the next 20 years, this suggests that HDVs need to be a major focus of mitigation efforts. HDVs dominated particle number (ultrafine particles) and PM1 emissions; and LDV PM2.5 and PM10 emissions. Buses contributed approximately 1-2% of regional particle emissions.

Uncertainty budget in the measurement of typical airborne number, surface area and mass particle distributions

The effects of particulate matter on environment and public health have been widely studied in recent years. A number of studies in the medical field have tried to identify the specific effect on human health of particulate exposure, but agreement amongst these studies on the relative importance of the particles’ size and its origin with respect to health effects is still lacking. Nevertheless, air quality standards are moving, as the epidemiological attention, towards greater focus on the smaller particles. Current air quality standards only regulate the mass of particulate matter less than 10 μm in aerodynamic diameter (PM10) and less than 2.5 μm (PM2.5). The most reliable method used in measuring Total Suspended Particles (TSP), PM10, PM2.5 and PM1 is the gravimetric method since it directly measures PM concentration, guaranteeing an effective traceability to international standards. This technique however, neglects the possibility to correlate short term intra-day variations of atmospheric parameters that can influence ambient particle concentration and size distribution (emission strengths of particle sources, temperature, relative humidity, wind direction and speed and mixing height) as well as human activity patterns that may also vary over time periods considerably shorter than 24 hours. A continuous method to measure the number size distribution and total number concentration in the range 0.014 – 20 μm is the tandem system constituted by a Scanning Mobility Particle Sizer (SMPS) and an Aerodynamic Particle Sizer (APS). In this paper, an uncertainty budget model of the measurement of airborne particle number, surface area and mass size distributions is proposed and applied for several typical aerosol size distributions. The estimation of such an uncertainty budget presents several difficulties due to i) the complexity of the measurement chain, ii) the fact that SMPS and APS can properly guarantee the traceability to the International System of Measurements only in terms of number concentration. In fact, the surface area and mass concentration must be estimated on the basis of separately determined average density and particle morphology. Keywords: SMPS-APS tandem system, gravimetric reference method, uncertainty budget, ultrafine particles.

CTCombine : rotating and combining CT data with an accurate detector model, to simulate radiotherapy portal imaging at non-zero beam angles

Established Monte Carlo user codes BEAMnrc and DOSXYZnrc permit the accurate and straightforward simulation of radiotherapy experiments and treatments delivered from multiple beam angles. However, when an electronic portal imaging detector (EPID) is included in these simulations, treatment delivery from non-zero beam angles becomes problematic. This study introduces CTCombine, a purpose-built code for rotating selected CT data volumes, converting CT numbers to mass densities, combining the results with model EPIDs and writing output in a form which can easily be read and used by the dose calculation code DOSXYZnrc. The geometric and dosimetric accuracy of CTCombine’s output has been assessed by simulating simple and complex treatments applied to a rotated planar phantom and a rotated humanoid phantom and comparing the resulting virtual EPID images with the images acquired using experimental measurements and independent simulations of equivalent phantoms. It is expected that CTCombine will be useful for Monte Carlo studies of EPID dosimetry as well as other EPID imaging applications.

Dwell-time and run-time control for DC mass rapid transit railways

Dwell times at stations and inter-station run times are the two major operational parameters to maintain train schedule in railway service. Current practices on dwell-time and run-time control are that they are only optimal with respect to certain nominal traffic conditions, but not necessarily the current service demand. The advantages of dwell-time and run-time control on trains are therefore not fully considered. The application of a dynamic programming approach, with the aid of an event-based model, to devise an optimal set of dwell times and run times for trains under given operational constraints over a regional level is presented. Since train operation is interactive and of multi-attributes, dwell-time and run-time coordination among trains is a multi-dimensional problem. The computational demand on devising trains' instructions, a prime concern in real-time applications, is excessively high. To properly reduce the computational demand in the provision of appropriate dwell times and run times for trains, a DC railway line is divided into a number of regions and each region is controlled by a dwell- time and run-time controller. The performance and feasibility of the controller in formulating the dwell-time and run-time solutions for real-time applications are demonstrated through simulations.