994 resultados para publication rates


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Venous leg ulceration is a serious condition affecting 1 – 3% of the population. Decline in the function of the calf muscle pump is correlated with venous ulceration. Many previous studies have reported an improvement in the function of the calf muscle pump, endurance of the calf muscle and increased range of ankle motion after structured exercise programs. However, there is a paucity of published research that assesses if these improvements result in an improvement in the healing rates of venous ulcers. The primary purpose of this pilot study was to establish the feasibility of a homebased progressive resistance exercise program and examine if there was any clinical significance or trend toward healing. The secondary aims were to examine the benefit of a home-based progressive resistance exercise program on calf muscle pump function and physical parameters. The methodology used was a randomised controlled trial where eleven participants were randomised into an intervention (n = 6) or control group (n = 5). Participants who were randomised to receive a 12-week home-based progressive resistance exercise program were instructed through weekly face-to-face consultations during their wound clinic appointment by the author. Control group participants received standard wound care and compression therapy. Changes in ulcer parameters were measured fortnightly at the clinic (number healed at 12 weeks, percentage change in area and pressure ulcer score healing score). An air plethysmography test was performed at baseline and following the 12 weeks of training to determine changes in calf muscle pump function. Functional measures included maximum number of heel raises (endurance), maximal isometric plantar flexion (strength) and range of ankle motion (ROAM); these tests were conducted at baseline, week 6 and week 12. The sample for the study was drawn from the Princess Alexandra Hospital in Brisbane, Australia. Participants with venous leg ulceration who met the inclusion criteria were recruited. The participants were screened via duplex scanning and ankle brachial pressure index (ABPI) to ensure they did not have any arterial complications. Participants were excluded if there was evidence of cellulitis. Demographic data were obtained from each participant and details regarding medical history, quality of life and geriatric depression scores were collected at baseline. Both the intervention and control group were required to complete a weekly exercise diary to monitor activity levels between groups. To test for the effect of the intervention over time, a repeated measures analysis of variance was conducted on the major outcome variables. Group (intervention versus control) was the between subject factor and time (baseline, week 6, week 12) was the within subject or repeated measures factor. Due to the small sample size, further tests were conducted to check the assumptions of the statistical test to be used. The results showed that Mauchly.s Test, the Sphericity assumptions of repeated measures for ANOVA were met. Further tests of homogeneity of variance assumptions also confirmed that this assumption was met. Data analysis was conducted using the software package SPSS for Windows Release 17.0. The pilot study proved feasible with all of the intervention (n=6) participants continuing with the resistance program for the 12 week duration and no deleterious effects noted. Clinical significance was observed in the intervention group with a 32% greater change in ulcer size (p= 0.26) than the control group, and a 10% (p = 0.74) greater difference between the numbers healed compared to the control group. Statistical significance was observed for the ejection fraction (p = 0.05), residual volume fraction (p = 0.04) and ROAM (p = 0.01), which all improved significantly in the intervention group over time. These results are encouraging, nevertheless, further investigations seem warranted to examine the effect exercise has on the healing rates of venous leg ulcers, with a multistudy site, larger sample size and longer follow up period.

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Isoindoline nitroxides are potentially useful probes for viable biological systems, exhibiting low cytotoxicity, moderate rates of biological reduction and favorable Electron Paramagnetic Resonance (EPR) characteristics. We have evaluated the anionic (5-carboxy-1,1,3,3-tetramethylisoindolin-2-yloxyl; CTMIO), cationic (5-(N,N,N-trimethylammonio)-1,1,3,3-tetramethylisoindolin-2-yloxyl iodide, QATMIO) and neutral (1,1,3,3-tetramethylisoindolin-2-yloxyl; TMIO) nitroxides and their isotopically labeled analogs ((2)H(12)- and/or (2)H(12)-(15)N-labeled) as potential EPR oximetry probes. An active ester analogue of CTMIO, designed to localize intracellularly, and the azaphenalene nitroxide 1,1,3,3-tetramethyl-2,3-dihydro-2-azaphenalen-2-yloxyl (TMAO) were also studied. While the EPR spectra of the unlabeled nitroxides exhibit high sensitivity to O(2) concentration, deuteration resulted in a loss of superhyperfine features and a subsequent reduction in O(2) sensitivity. Labeling the nitroxides with (15)N increased the signal intensity and this may be useful in decreasing the detection limits for in vivo measurements. The active ester nitroxide showed approximately 6% intracellular localization and low cytotoxicity. The EPR spectra of TMAO nitroxide indicated an increased rigidity in the nitroxide ring, due to dibenzo-annulation.

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There are approximately 92 million new chlamydial infections of the genital tract in humans diagnosed each year, costing health care systems billions of dollars in treatment not only of acute infections, but also of associated inflammatory sequelae, such as pelvic inflammatory disease (PID) and ectopic pregnancy. These numbers are increasing at a steady rate and, due to the asymptomatic nature of infections, the incidence may be underestimated and the costs of treatment therefore higher. Over the previous few decades there has been a large amount of research into the development of an efficacious vaccine against genital tract chlamydial infections. The majority of this research has focused on females, due to the high rate of development of associated diseases, including PID, which can lead to ectopic pregnancy and infertility. In light of the increasing infection rates that have occurred despite the availability of antibiotics, and the asymptomatic nature of chlamydial infections, it is imperative that an efficacious vaccine that protects against infection and associated pathology be developed.

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We consider complexity penalization methods for model selection. These methods aim to choose a model to optimally trade off estimation and approximation errors by minimizing the sum of an empirical risk term and a complexity penalty. It is well known that if we use a bound on the maximal deviation between empirical and true risks as a complexity penalty, then the risk of our choice is no more than the approximation error plus twice the complexity penalty. There are many cases, however, where complexity penalties like this give loose upper bounds on the estimation error. In particular, if we choose a function from a suitably simple convex function class with a strictly convex loss function, then the estimation error (the difference between the risk of the empirical risk minimizer and the minimal risk in the class) approaches zero at a faster rate than the maximal deviation between empirical and true risks. In this paper, we address the question of whether it is possible to design a complexity penalized model selection method for these situations. We show that, provided the sequence of models is ordered by inclusion, in these cases we can use tight upper bounds on estimation error as a complexity penalty. Surprisingly, this is the case even in situations when the difference between the empirical risk and true risk (and indeed the error of any estimate of the approximation error) decreases much more slowly than the complexity penalty. We give an oracle inequality showing that the resulting model selection method chooses a function with risk no more than the approximation error plus a constant times the complexity penalty.

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This paper examines changing patterns in the utilisation and geographic access to health services in Great Britain using National Travel Survey data (1985-2006). The utilisation rate was derived using the proportion of journeys made to access health services. Geographic access was analysed by separating the concept into its accessibility and mobility dimensions. Regression analyses were conducted to investigate the differences between different socio-spatial groups in these indicators over the period 1985-2006. This study found that journey distances to health facilities were significantly shorter and also gradually reduced over the period in question for Londoners, females, those without a car or on low incomes, and older people. However, most of their rates of utilisation of health services were found to be significantly lower because their journey times were significantly longer and also gradually increased over the periods. These findings indicate that the rate of utilisation of health services largely depends on mobility level although previous research studies have traditionally overlooked the mobility dimension.

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Vehicle emitted particles are of significant concern based on their potential to influence local air quality and human health. Transport microenvironments usually contain higher vehicle emission concentrations compared to other environments, and people spend a substantial amount of time in these microenvironments when commuting. Currently there is limited scientific knowledge on particle concentration, passenger exposure and the distribution of vehicle emissions in transport microenvironments, partially due to the fact that the instrumentation required to conduct such measurements is not available in many research centres. Information on passenger waiting time and location in such microenvironments has also not been investigated, which makes it difficult to evaluate a passenger’s spatial-temporal exposure to vehicle emissions. Furthermore, current emission models are incapable of rapidly predicting emission distribution, given the complexity of variations in emission rates that result from changes in driving conditions, as well as the time spent in driving condition within the transport microenvironment. In order to address these scientific gaps in knowledge, this work conducted, for the first time, a comprehensive statistical analysis of experimental data, along with multi-parameter assessment, exposure evaluation and comparison, and emission model development and application, in relation to traffic interrupted transport microenvironments. The work aimed to quantify and characterise particle emissions and human exposure in the transport microenvironments, with bus stations and a pedestrian crossing identified as suitable research locations representing a typical transport microenvironment. Firstly, two bus stations in Brisbane, Australia, with different designs, were selected to conduct measurements of particle number size distributions, particle number and PM2.5 concentrations during two different seasons. Simultaneous traffic and meteorological parameters were also monitored, aiming to quantify particle characteristics and investigate the impact of bus flow rate, station design and meteorological conditions on particle characteristics at stations. The results showed higher concentrations of PN20-30 at the station situated in an open area (open station), which is likely to be attributed to the lower average daily temperature compared to the station with a canyon structure (canyon station). During precipitation events, it was found that particle number concentration in the size range 25-250 nm decreased greatly, and that the average daily reduction in PM2.5 concentration on rainy days compared to fine days was 44.2 % and 22.6 % at the open and canyon station, respectively. The effect of ambient wind speeds on particle number concentrations was also examined, and no relationship was found between particle number concentration and wind speed for the entire measurement period. In addition, 33 pairs of average half-hourly PN7-3000 concentrations were calculated and identified at the two stations, during the same time of a day, and with the same ambient wind speeds and precipitation conditions. The results of a paired t-test showed that the average half-hourly PN7-3000 concentrations at the two stations were not significantly different at the 5% confidence level (t = 0.06, p = 0.96), which indicates that the different station designs were not a crucial factor for influencing PN7-3000 concentrations. A further assessment of passenger exposure to bus emissions on a platform was evaluated at another bus station in Brisbane, Australia. The sampling was conducted over seven weekdays to investigate spatial-temporal variations in size-fractionated particle number and PM2.5 concentrations, as well as human exposure on the platform. For the whole day, the average PN13-800 concentration was 1.3 x 104 and 1.0 x 104 particle/cm3 at the centre and end of the platform, respectively, of which PN50-100 accounted for the largest proportion to the total count. Furthermore, the contribution of exposure at the bus station to the overall daily exposure was assessed using two assumed scenarios of a school student and an office worker. It was found that, although the daily time fraction (the percentage of time spend at a location in a whole day) at the station was only 0.8 %, the daily exposure fractions (the percentage of exposures at a location accounting for the daily exposure) at the station were 2.7% and 2.8 % for exposure to PN13-800 and 2.7% and 3.5% for exposure to PM2.5 for the school student and the office worker, respectively. A new parameter, “exposure intensity” (the ratio of daily exposure fraction and the daily time fraction) was also defined and calculated at the station, with values of 3.3 and 3.4 for exposure to PN13-880, and 3.3 and 4.2 for exposure to PM2.5, for the school student and the office worker, respectively. In order to quantify the enhanced emissions at critical locations and define the emission distribution in further dispersion models for traffic interrupted transport microenvironments, a composite line source emission (CLSE) model was developed to specifically quantify exposure levels and describe the spatial variability of vehicle emissions in traffic interrupted microenvironments. This model took into account the complexity of vehicle movements in the queue, as well as different emission rates relevant to various driving conditions (cruise, decelerate, idle and accelerate), and it utilised multi-representative segments to capture the accurate emission distribution for real vehicle flow. This model does not only helped to quantify the enhanced emissions at critical locations, but it also helped to define the emission source distribution of the disrupted steady flow for further dispersion modelling. The model then was applied to estimate particle number emissions at a bidirectional bus station used by diesel and compressed natural gas fuelled buses. It was found that the acceleration distance was of critical importance when estimating particle number emission, since the highest emissions occurred in sections where most of the buses were accelerating and no significant increases were observed at locations where they idled. It was also shown that emissions at the front end of the platform were 43 times greater than at the rear of the platform. The CLSE model was also applied at a signalled pedestrian crossing, in order to assess increased particle number emissions from motor vehicles when forced to stop and accelerate from rest. The CLSE model was used to calculate the total emissions produced by a specific number and mix of light petrol cars and diesel passenger buses including 1 car travelling in 1 direction (/1 direction), 14 cars / 1 direction, 1 bus / 1 direction, 28 cars / 2 directions, 24 cars and 2 buses / 2 directions, and 20 cars and 4 buses / 2 directions. It was found that the total emissions produced during stopping on a red signal were significantly higher than when the traffic moved at a steady speed. Overall, total emissions due to the interruption of the traffic increased by a factor of 13, 11, 45, 11, 41, and 43 for the above 6 cases, respectively. In summary, this PhD thesis presents the results of a comprehensive study on particle number and mass concentration, together with particle size distribution, in a bus station transport microenvironment, influenced by bus flow rates, meteorological conditions and station design. Passenger spatial-temporal exposure to bus emitted particles was also assessed according to waiting time and location along the platform, as well as the contribution of exposure at the bus station to overall daily exposure. Due to the complexity of the interrupted traffic flow within the transport microenvironments, a unique CLSE model was also developed, which is capable of quantifying emission levels at critical locations within the transport microenvironment, for the purpose of evaluating passenger exposure and conducting simulations of vehicle emission dispersion. The application of the CLSE model at a pedestrian crossing also proved its applicability and simplicity for use in a real-world transport microenvironment.

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The emissions to water from a 1.9 kW two-stroke outboard engine were investigated in the laboratory and in the field, with the primary objective being to characterise and quantify the pollutants that remain within the water column. The emission rates of polycyclic aromatic hydrocarbons (PAHs) and volatile organic compounds (VOCs) were determined for the engine when using a mineral and an equivalent environmentally adapted lubricant (EAL). A comparison of the emission rates was conducted between the results from the fresh and sea water tests. The results showed that there was little difference in the emission rates of these pollutants when either of the lubricants was used in both the fresh and sea water. A further set of tests were done to find out the effect on pH of water due to the underwater emissions and these tests were done using both mineral and environmentally adapted lubricant. The results showed that the type of lubricant does not have any effect on the change in pH of the water.

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In recent years, the effect of ions and ultrafine particles on ambient air quality and human health has been well documented, however, knowledge about their sources, concentrations and interactions within different types of urban environments remains limited. This thesis presents the results of numerous field studies aimed at quantifying variations in ion concentration with distance from the source, as well as identifying the dynamics of the particle ionisation processes which lead to the formation of charged particles in the air. In order to select the most appropriate measurement instruments and locations for the studies, a literature review was also conducted on studies that reported ion and ultrafine particle emissions from different sources in a typical urban environment. The initial study involved laboratory experiments on the attachment of ions to aerosols, so as to gain a better understanding of the interaction between ions and particles. This study determined the efficiency of corona ions at charging and removing particles from the air, as a function of different particle number and ion concentrations. The results showed that particle number loss was directly proportional to particle charge concentration, and that higher small ion concentrations led to higher particle deposition rates in all size ranges investigated. Nanoparticles were also observed to decrease with increasing particle charge concentration, due to their higher Brownian mobility and subsequent attachment to charged particles. Given that corona discharge from high voltage powerlines is considered one of the major ion sources in urban areas, a detailed study was then conducted under three parallel overhead powerlines, with a steady wind blowing in a perpendicular direction to the lines. The results showed that large sections of the lines did not produce any corona at all, while strong positive emissions were observed from discrete components such as a particular set of spacers on one of the lines. Measurements were also conducted at eight upwind and downwind points perpendicular to the powerlines, spanning a total distance of about 160m. The maximum positive small and large ion concentrations, and DC electric field were observed at a point 20 m downwind from the lines, with median values of 4.4×103 cm-3, 1.3×103 cm-3 and 530 V m-1, respectively. It was estimated that, at this point, less than 7% of the total number of particles was charged. The electrical parameters decreased steadily with increasing downwind distance from the lines but remained significantly higher than background levels at the limit of the measurements. Moreover, vehicles are one of the most prevalent ion and particle emitting sources in urban environments, and therefore, experiments were also conducted behind a motor vehicle exhaust pipe and near busy motorways, with the aim of quantifying small ion and particle charge concentration, as well as their distribution as a function of distance from the source. The study found that approximately equal numbers of positive and negative ions were observed in the vehicle exhaust plume, as well as near motorways, of which heavy duty vehicles were believed to be the main contributor. In addition, cluster ion concentration was observed to decrease rapidly within the first 10-15 m from the road and ion-ion recombination and ion-aerosol attachment were the most likely cause of ion depletion, rather than dilution and turbulence related processes. In addition to the above-mentioned dominant ion sources, other sources also exist within urban environments where intensive human activities take place. In this part of the study, airborne concentrations of small ions, particles and net particle charge were measured at 32 different outdoor sites in and around Brisbane, Australia, which were classified into seven different groups as follows: park, woodland, city centre, residential, freeway, powerlines and power substation. Whilst the study confirmed that powerlines, power substations and freeways were the main ion sources in an urban environment, it also suggested that not all powerlines emitted ions, only those with discrete corona discharge points. In addition to the main ion sources, higher ion concentrations were also observed environments affected by vehicle traffic and human activities, such as the city centre and residential areas. A considerable number of ions were also observed in a woodland area and it is still unclear if they were emitted directly from the trees, or if they originated from some other local source. Overall, it was found that different types of environments had different types of ion sources, which could be classified as unipolar or bipolar particle sources, as well as ion sources that co-exist with particle sources. In general, fewer small ions were observed at sites with co-existing sources, however particle charge was often higher due to the effect of ion-particle attachment. In summary, this study quantified ion concentrations in typical urban environments, identified major charge sources in urban areas, and determined the spatial dispersion of ions as a function of distance from the source, as well as their controlling factors. The study also presented ion-aerosol attachment efficiencies under high ion concentration conditions, both in the laboratory and in real outdoor environments. The outcomes of these studies addressed the aims of this work and advanced understanding of the charge status of aerosols in the urban environment.

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Background: Room ventilation is a key determinant of airborne disease transmission. Despite this, ventilation guidelines in hospitals are not founded on robust scientific evidence related to prevention of airborne transmission. Methods: We sought to assess the effect of ventilation rates on influenza, tuberculosis (TB) and rhinovirus infection risk within three distinct rooms in a major urban hospital; a Lung Function Laboratory, Emergency Department (ED) Negative-pressure Isolation Room and an Outpatient Consultation Room were investigated. Air exchange rate measurements were performed in each room using CO2 as a tracer. Gammaitoni and Nucci’s model was employed to estimate infection risk. Results: Current outdoor air exchange rates in the Lung Function Laboratory and ED Isolation Room limited infection risks to between 0.1 and 3.6%. Influenza risk for individuals entering an Outpatient Consultation Room after an infectious individual departed ranged from 3.6 to 20.7%, depending on the duration for which each person occupied the room. Conclusions: Given the absence of definitive ventilation guidelines for hospitals, air exchange measurements combined with modelling afford a useful means of assessing, on a case-by-case basis, the suitability of room ventilation at preventing airborne disease transmission.

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In public places, crowd size may be an indicator of congestion, delay, instability, or of abnormal events, such as a fight, riot or emergency. Crowd related information can also provide important business intelligence such as the distribution of people throughout spaces, throughput rates, and local densities. A major drawback of many crowd counting approaches is their reliance on large numbers of holistic features, training data requirements of hundreds or thousands of frames per camera, and that each camera must be trained separately. This makes deployment in large multi-camera environments such as shopping centres very costly and difficult. In this chapter, we present a novel scene-invariant crowd counting algorithm that uses local features to monitor crowd size. The use of local features allows the proposed algorithm to calculate local occupancy statistics, scale to conditions which are unseen in the training data, and be trained on significantly less data. Scene invariance is achieved through the use of camera calibration, allowing the system to be trained on one or more viewpoints and then deployed on any number of new cameras for testing without further training. A pre-trained system could then be used as a ‘turn-key’ solution for crowd counting across a wide range of environments, eliminating many of the costly barriers to deployment which currently exist.

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Modelling an environmental process involves creating a model structure and parameterising the model with appropriate values to accurately represent the process. Determining accurate parameter values for environmental systems can be challenging. Existing methods for parameter estimation typically make assumptions regarding the form of the Likelihood, and will often ignore any uncertainty around estimated values. This can be problematic, however, particularly in complex problems where Likelihoods may be intractable. In this paper we demonstrate an Approximate Bayesian Computational method for the estimation of parameters of a stochastic CA. We use as an example a CA constructed to simulate a range expansion such as might occur after a biological invasion, making parameter estimates using only count data such as could be gathered from field observations. We demonstrate ABC is a highly useful method for parameter estimation, with accurate estimates of parameters that are important for the management of invasive species such as the intrinsic rate of increase and the point in a landscape where a species has invaded. We also show that the method is capable of estimating the probability of long distance dispersal, a characteristic of biological invasions that is very influential in determining spread rates but has until now proved difficult to estimate accurately.

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Methodological differences among studies of vasomotor symptoms limit rigorous comparison or systematic review. Vasomotor symptoms generally include hot flushes and night sweats although other associated symptoms exist. Prevalence rates vary between and within populations, but different studies collect data on frequency, bothersomeness, and/or severity using different outcome measures and scales, making comparisons difficult. We reviewed only cross-cultural studies of menopausal symptoms that explicitly examined symptoms in general populations of women in different countries or different ethnic groups in the same country. This resulted in the inclusion of nine studies: Australian/Japanese Midlife Women's Health Study (AJMWHS), Decisions At Menopause Study (DAMeS), Four Major Ethnic Groups (FMEG), Hilo Women's Health Survey (HWHS), Mid-Aged Health in Women from the Indian Subcontinent (MAHWIS), Penn Ovarian Aging Study (POAS), Study of Women's Health Across the Nation (SWAN), Women's Health in Midlife National Study (WHiMNS), and Women's International Study of Health and Sexuality (WISHeS). These studies highlight the methodological challenges involved in conducting multi-population studies, particularly when languages differ, but also highlight the importance of performing multivariate and factor analyses. Significant cultural differences in one or more vasomotor symptoms were observed in 8 of 9 studies, and symptoms were influenced by the following determinants: menopausal status, hormones (and variance), age (or actually, the square of age, age2), BMI, depression, anxiety, poor physical health, perceived stress, lifestyle factors (hormone therapy use, smoking and exposure to passive smoke), and acculturation (in immigrant populations). Recommendations are made to improve methodological rigor and facilitate comparisons in future cross-cultural menopause studies.

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The effect of sample geometry on the melting rates of burning iron rods was assessed. Promoted-ignition tests were conducted with rods having cylindrical, rectangular, and triangular cross-sectional shapes over a range of cross-sectional areas. The regression rate of the melting interface (RRMI) was assessed using a statistical approach which enabled the quantification of confidence levels for the observed differences in RRMI. Statistically significant differences in RRMI were observed for rods with the same cross-sectional area but different cross-sectional shape. The magnitude of the proportional difference in RRMI increased with the cross-sectional area. Triangular rods had the highest RRMI, followed by rectangular rods, and then cylindrical rods. The dependence of RRMI on rod shape is shown to relate to the action of molten metal at corners. The corners of the rectangular and triangular rods melted faster than the faces due to their locally higher surface area to volume ratios. This phenomenon altered the attachment geometry between liquid and solid phases, increasing the surface area available for heat transfer, causing faster melting. Findings relating to the application of standard flammability test results in industrial situations are also presented.

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Continuum, partial differential equation models are often used to describe the collective motion of cell populations, with various types of motility represented by the choice of diffusion coefficient, and cell proliferation captured by the source terms. Previously, the choice of diffusion coefficient has been largely arbitrary, with the decision to choose a particular linear or nonlinear form generally based on calibration arguments rather than making any physical connection with the underlying individual-level properties of the cell motility mechanism. In this work we provide a new link between individual-level models, which account for important cell properties such as varying cell shape and volume exclusion, and population-level partial differential equation models. We work in an exclusion process framework, considering aligned, elongated cells that may occupy more than one lattice site, in order to represent populations of agents with different sizes. Three different idealizations of the individual-level mechanism are proposed, and these are connected to three different partial differential equations, each with a different diffusion coefficient; one linear, one nonlinear and degenerate and one nonlinear and nondegenerate. We test the ability of these three models to predict the population level response of a cell spreading problem for both proliferative and nonproliferative cases. We also explore the potential of our models to predict long time travelling wave invasion rates and extend our results to two dimensional spreading and invasion. Our results show that each model can accurately predict density data for nonproliferative systems, but that only one does so for proliferative systems. Hence great care must be taken to predict density data for with varying cell shape.