290 resultados para Latent class growth analysis


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In this paper, a class of fractional advection-dispersion models (FADM) is investigated. These models include five fractional advection-dispersion models: the immobile, mobile/immobile time FADM with a temporal fractional derivative 0 < γ < 1, the space FADM with skewness, both the time and space FADM and the time fractional advection-diffusion-wave model with damping with index 1 < γ < 2. They describe nonlocal dependence on either time or space, or both, to explain the development of anomalous dispersion. These equations can be used to simulate regional-scale anomalous dispersion with heavy tails, for example, the solute transport in watershed catchments and rivers. We propose computationally effective implicit numerical methods for these FADM. The stability and convergence of the implicit numerical methods are analyzed and compared systematically. Finally, some results are given to demonstrate the effectiveness of our theoretical analysis.

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Structural health monitoring (SHM) refers to the procedure used to assess the condition of structures so that their performance can be monitored and any damage can be detected early. Early detection of damage and appropriate retrofitting will aid in preventing failure of the structure and save money spent on maintenance or replacement and ensure the structure operates safely and efficiently during its whole intended life. Though visual inspection and other techniques such as vibration based ones are available for SHM of structures such as bridges, the use of acoustic emission (AE) technique is an attractive option and is increasing in use. AE waves are high frequency stress waves generated by rapid release of energy from localised sources within a material, such as crack initiation and growth. AE technique involves recording these waves by means of sensors attached on the surface and then analysing the signals to extract information about the nature of the source. High sensitivity to crack growth, ability to locate source, passive nature (no need to supply energy from outside, but energy from damage source itself is utilised) and possibility to perform real time monitoring (detecting crack as it occurs or grows) are some of the attractive features of AE technique. In spite of these advantages, challenges still exist in using AE technique for monitoring applications, especially in the area of analysis of recorded AE data, as large volumes of data are usually generated during monitoring. The need for effective data analysis can be linked with three main aims of monitoring: (a) accurately locating the source of damage; (b) identifying and discriminating signals from different sources of acoustic emission and (c) quantifying the level of damage of AE source for severity assessment. In AE technique, the location of the emission source is usually calculated using the times of arrival and velocities of the AE signals recorded by a number of sensors. But complications arise as AE waves can travel in a structure in a number of different modes that have different velocities and frequencies. Hence, to accurately locate a source it is necessary to identify the modes recorded by the sensors. This study has proposed and tested the use of time-frequency analysis tools such as short time Fourier transform to identify the modes and the use of the velocities of these modes to achieve very accurate results. Further, this study has explored the possibility of reducing the number of sensors needed for data capture by using the velocities of modes captured by a single sensor for source localization. A major problem in practical use of AE technique is the presence of sources of AE other than crack related, such as rubbing and impacts between different components of a structure. These spurious AE signals often mask the signals from the crack activity; hence discrimination of signals to identify the sources is very important. This work developed a model that uses different signal processing tools such as cross-correlation, magnitude squared coherence and energy distribution in different frequency bands as well as modal analysis (comparing amplitudes of identified modes) for accurately differentiating signals from different simulated AE sources. Quantification tools to assess the severity of the damage sources are highly desirable in practical applications. Though different damage quantification methods have been proposed in AE technique, not all have achieved universal approval or have been approved as suitable for all situations. The b-value analysis, which involves the study of distribution of amplitudes of AE signals, and its modified form (known as improved b-value analysis), was investigated for suitability for damage quantification purposes in ductile materials such as steel. This was found to give encouraging results for analysis of data from laboratory, thereby extending the possibility of its use for real life structures. By addressing these primary issues, it is believed that this thesis has helped improve the effectiveness of AE technique for structural health monitoring of civil infrastructures such as bridges.

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Background Emergency department (ED) crowding caused by access block is an increasing public health issue and has been associated with impaired healthcare delivery, negative patient outcomes and increased staff workload. Aim To investigate the impact of opening a new ED on patient and healthcare service outcomes. Methods A 24-month time series analysis was employed using deterministically linked data from the ambulance service and three ED and hospital admission databases in Queensland, Australia. Results Total volume of ED presentations increased 18%, while local population growth increased by 3%. Healthcare service and patient outcomes at the two pre-existing hospitals did not improve. These outcomes included ambulance offload time: (Hospital A PRE: 10 min, POST: 10 min, P < 0.001; Hospital B PRE: 10 min, POST: 15 min, P < 0.001); ED length of stay: (Hospital A PRE: 242 min, POST: 246 min, P < 0.001; Hospital B PRE: 182 min, POST: 210 min, P < 0.001); and access block: (Hospital A PRE: 41%, POST: 46%, P < 0.001; Hospital B PRE: 23%, POST: 40%, P < 0.001). Time series modelling indicated that the effect was worst at the hospital furthest away from the new ED. Conclusions An additional ED within the region saw an increase in the total volume of presentations at a rate far greater than local population growth, suggesting it either provided an unmet need or a shifting of activity from one sector to another. Future studies should examine patient decision making regarding reasons for presenting to a new or pre-existing ED. There is an inherent need to take a ‘whole of health service area’ approach to solve crowding issues.

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Crop simulation models have the potential to assess the risk associated with the selection of a specific N fertilizer rate, by integrating the effects of soil-crop interactions on crop growth under different pedo-climatic and management conditions. The objective of this study was to simulate the environmental and economic impact (nitrate leaching and N2O emissions) of a spatially variable N fertilizer application in an irrigated maize field in Italy. The validated SALUS model was run with 5 nitrogen rates scenarios, 50, 100, 150, 200, and 250 kg N ha−1, with the latter being the N fertilization adopted by the farmer. The long-term (25 years) simulations were performed on two previously identified spatially and temporally stable zones, a high yielding and low yielding zone. The simulation results showed that N fertilizer rate can be reduced without affecting yield and net return. The marginal net return was on average higher for the high yield zone, with values ranging from 1550 to 2650 € ha−1 for the 200 N and 1485 to 2875 € ha−1 for the 250 N. N leaching varied between 16.4 and 19.3 kg N ha−1 for the 200 N and the 250 N in the high yield zone. In the low yield zone, the 250 N had a significantly higher N leaching. N2O emissions varied between 0.28 kg N2O ha−1 for the 50 kg N ha−1 rate to a maximum of 1.41 kg N2O ha−1 for the 250 kg N ha−1 rate.

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The construction industry is an industry of major strategic importance. Its level of productivity has a significant effect on national economic growth. Productivity indicators are examined. The indicators consist of labour productivity, capital productivity, labour competitiveness, capital intensity and added value content of data, which are obtained from the published census/biannual surveys of the construction industry between the years 1999 and 2011 from the Department of Statistics of Malaysia. The results indicated that there is an improvement in the labour productivity, but the value-added content is declining. The civil engineering and special trades subsectors are more productive than the residential and non-residential subsectors in terms of labour productivity because machine-for-labour substitution is a more important process in those subsectors. The capital-intensive characteristics of civil engineering and special trade works enable these subsectors to achieve higher added value per labour cost but not the capital productivity. The added value per labour cost is lower in larger organizations despite higher capital productivity. However, the capital intensity is lower and unit labour cost is higher in the larger organizations.

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Purpose: Myopia is a common eye disorder affecting up to 90% of children in South East Asia and 30% of the population worldwide. Myopia of high severity is a leading cause of blindness around the world (4th to 5th most common). Changes and remodelling of the sclera i.e. increase cellular proliferation & increase protein synthesis within scleral cells (↑ scleral DNA) and thinning and lose of extracellular matrix of sclera (↓ scleral GAG synthesis) have been linked to myopic eye growth in animal models. Signals acting on the sclera are thought to originate in the retina, and are modulated by the retinal pigment epithelium (RPE) with limited evidence suggesting that the RPE can modify scleral cell growth in culture. However, the mechanism of retinal signal transmission and the role of posterior eye cup tissue, including the RPE, in mediating changes in scleral fibroblast growth during myopia development are unclear. Retinal transmitter systems are critically involved in pathways regulating eye growth, which ultimately lead to alterations in the sclera if eye size is to change. A dopaminergic agonist and muscarinic antagonists decrease the proliferation of scleral chondrocytes when co-cultured with chick’s retinal pigment epithelium (RPE). GABA receptors have recently been localised to chick sclera. We therefore hypothesised that posterior eye cup tissue from myopic eyes would stimulate and from hyperopic eyes would inhibit growth of scleral fibroblasts in vitro and that GABAergic agents could directly interact with scleral cells or indirectly modify the effects of myopic and hyperopic posterior eye cup tissue on scleral fibroblast growth. Method: Fibroblastic cells obtained from 8-day-old chick sclera were used to establish cell banks. Two major experiments were performed. Experiment 1: To determine if posterior eye cup tissues from myopic eye stimulates and hyperopic eye inhibits scleral cell proliferation, when co-cultured with scleral cells in vitro. This study comprised two linked experiments, i) monocular visual treatments of FDM (form-deprivation myopia), LIM (lens-induced myopia) and LIH (lens-induced hyperopia) with assessment of the effect of full punch eye cup tissue on DNA and GAG synthesis by cultured chick scleral fibroblasts, and ii) binocular visual treatments comprising LIM and LIH with assessment of the effect of individual layers of eye cup tissues (neural retina, RPE and choroid) on cultured chick scleral fibroblasts. Visual treatment was applied for 3 days. Experiment 2: To determine the direct interaction of GABA agents on scleral cell growth and to establish whether GABA agents modify the stimulatory/inhibitory effect of myopic and hyperopic posterior eye cup tissues on cultured scleral cell growth in vitro. Two linked experiments were performed. i) GABA agonists (muscimol and baclofen) and GABA antagonists (bicuculine (-), CGP46381 and TPMPA) were added to scleral cell culture medium to determine their direct effect on scleral cells. ii) GABAergic agents (agonists and antagonists) were administered to scleral fibroblasts co-cultured with posterior eye cup tissue (retina, RPE, retina/RPE, RPE/choroid). Ocular tissues were obtained from chick eyes wearing +15D (LIH) or -15D lenses (LIM) for 3 days. In both experiments, tissues were added to hanging cell culture insert (pore size 1.0ìm) placed over each well of 24 well plates while scleral cells were cultured in DMEM/F12, Glutamax (Gibco) plus 10% FBS and penicillin/streptomycin (50U/ml)) and fungizone (1.25ug/ml) (Gibco), at seeding density of 30,000 cells/well at the bottom of the well and allowed to grow for 3 days. Scleral cells proliferation rate throughout the study was evaluated by determining GAG and DNA content of scleral cells using Dimethylmethylene blue (DMMB) dye and Quant-iTTm Pico Green® dsDNA reagent respectively. Results and analysis: Based on DNA and GAG content, there was no significant difference in tissue effect of LIM and LIH eyes on scleral fibroblast growth (DNA: 8.4 ± 1.1μg versus 9.3 ± 2.3 μg, p=0.23; GAG: 10.13 ± 1.4 μg versus 12.67 ± 1.2 μg, F2,23=6.16, p=0.0005) when tissues were obtained from monocularly treated chick eyes (FDM or +15D lens or -15D lens over right eyes with left eyes untreated) and co-cultured as full punch. When chick eyes were treated binocularly with -15D lens (LIM) right eye and +15D lens (LIH) left eyes and tissue layers were separated, the retina from LIM eyes did not stimulate scleral cell proliferation compared to LIH eyes (DNA: 27.2 ± 6.7 μg versus 23.2 ± 1.5 μg, p=0.23; GAG: 28.1 ±3.7 μg versus 28.7 ± 4.2 μg, p=0.21). Similarly, the LIH and LIM choroid did not produce a differential effect based on DNA (LIM 46.9 ± 6.4 μg versus LIH 53.5 ± 4.7 μg, p=0.18), however the choroid from LIH eyes induced higher scleral GAG content than from LIM eyes (32.5 ± 6.7 μg versus 18.9 ± 1.2 μg, p=0.023). In contrast, the RPE from LIM eyes caused a significant increase in fibroblast proliferation whereas the RPE from LIH eyes was relatively inhibitory (72.4 ± 6.3 μg versus 27.9 ± 2.3 μg, F1, 6=69.99, p=0.0005). GAG data were opposite to DNA data e.g. the RPE from LIH eyes increased (33.7 ± 7.9 μg) while the RPE from LIM eyes decreased (28.2 ± 3.0 μg) scleral cell growth (F1, 6=13.99, p=0.010). Based on DNA content, GABA agents had a small direct effect on scleral cell growth; GABA agonists increased (21.4 ± 1.0% and 18.3 ± 1.0% with muscimol and baclofen, p=0.0021), whereas GABA antagonists decreased fibroblast proliferation (-23.7 ± 0.9% with bicuculine & CGP46381 and -28.1 ± 0.5% with TPMPA, p=0.0004). GABA agents also modified the effect of LIM and LIH tissues (p=0.0005).The increase in proliferation rate of scleral fibroblasts co-cultured with tissues (RPE, retina, RPE/retina and RPE/choroid) from LIM treated eyes was enhanced by GABA agonists (muscimol: 27.4 ± 1.2%, 35.8 ± 1.6%, 8.4 ± 0.3% and 11.9 ± 0.6%; baclofen: 27.0 ± 1.0%, 15.8 ± 1.5%, 16.8 ± 1.2% and 15.4 ± 0.4%, p=0.014) whereas GABA antagonists further reduced scleral fibroblasts growth (bicuculine: -52.5 ± 2.5%, -36.9 ± 1.4%, -37.5 ± 0.6% and -53.7 ± 0.9%; TPMPA: 57.3 ± 1.3%, -15.7 ± 1.2%, -33.5 ± 0.4% and -45.9 ± 1.5%; CGP46381: -51.9 ± 1.6%, -28.5 ± 1.5%, -25.4 ± 2.0% and -45.5 ± 1.9% respectively, p=0.0034). GAG data were opposite to DNA data throughout the experiment e.g. GABA agonists further inhibited while antagonists relatively enhanced scleral fibroblasts growth for both LIM and LIH tissue co-culture. The effect of GABA agents was relatively lower (p=0.0004) for tissue from LIH versus LIM eyes but was in a similar direction. There was a significant drug effect on all four tissue types e.g. RPE, retina, RPE/retina and RPE/choroid for both LIM and LIH tissue co-culture (F20,92=3.928, p=0.0005). However, the effect of GABA agents was greatest in co-culture with RPE tissue (F18,36=4.865, p=0.0005). Summary and Conclusion: 1) Retinal defocus signals are transferred to RPE and choroid which then exert their modifying effect on scleral GAG and DNA synthesis either through growth stimulating factors or directly interacting with scleral cells in process of scleral remodeling during LIM and LIH visual conditions. 2) GABAergic agents affect the proliferation of scleral fibroblasts both directly and when co-cultured with ocular tissues in vitro.

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Barmah Forest virus (BFV) disease is one of the most widespread mosquito-borne diseases in Australia. The number of outbreaks and the incidence rate of BFV in Australia have attracted growing concerns about the spatio-temporal complexity and underlying risk factors of BFV disease. A large number of notifications has been recorded continuously in Queensland since 1992. Yet, little is known about the spatial and temporal characteristics of the disease. I aim to use notification data to better understand the effects of climatic, demographic, socio-economic and ecological risk factors on the spatial epidemiology of BFV disease transmission, develop predictive risk models and forecast future disease risks under climate change scenarios. Computerised data files of daily notifications of BFV disease and climatic variables in Queensland during 1992-2008 were obtained from Queensland Health and Australian Bureau of Meteorology, respectively. Projections on climate data for years 2025, 2050 and 2100 were obtained from Council of Scientific Industrial Research Organisation. Data on socio-economic, demographic and ecological factors were also obtained from relevant government departments as follows: 1) socio-economic and demographic data from Australian Bureau of Statistics; 2) wetlands data from Department of Environment and Resource Management and 3) tidal readings from Queensland Department of Transport and Main roads. Disease notifications were geocoded and spatial and temporal patterns of disease were investigated using geostatistics. Visualisation of BFV disease incidence rates through mapping reveals the presence of substantial spatio-temporal variation at statistical local areas (SLA) over time. Results reveal high incidence rates of BFV disease along coastal areas compared to the whole area of Queensland. A Mantel-Haenszel Chi-square analysis for trend reveals a statistically significant relationship between BFV disease incidence rates and age groups (ƒÓ2 = 7587, p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. A cluster analysis was used to detect the hot spots/clusters of BFV disease at a SLA level. Most likely spatial and space-time clusters are detected at the same locations across coastal Queensland (p<0.05). The study demonstrates heterogeneity of disease risk at a SLA level and reveals the spatial and temporal clustering of BFV disease in Queensland. Discriminant analysis was employed to establish a link between wetland classes, climate zones and BFV disease. This is because the importance of wetlands in the transmission of BFV disease remains unclear. The multivariable discriminant modelling analyses demonstrate that wetland types of saline 1, riverine and saline tidal influence were the most significant risk factors for BFV disease in all climate and buffer zones, while lacustrine, palustrine, estuarine and saline 2 and saline 3 wetlands were less important. The model accuracies were 76%, 98% and 100% for BFV risk in subtropical, tropical and temperate climate zones, respectively. This study demonstrates that BFV disease risk varied with wetland class and climate zone. The study suggests that wetlands may act as potential breeding habitats for BFV vectors. Multivariable spatial regression models were applied to assess the impact of spatial climatic, socio-economic and tidal factors on the BFV disease in Queensland. Spatial regression models were developed to account for spatial effects. Spatial regression models generated superior estimates over a traditional regression model. In the spatial regression models, BFV disease incidence shows an inverse relationship with minimum temperature, low tide and distance to coast, and positive relationship with rainfall in coastal areas whereas in whole Queensland the disease shows an inverse relationship with minimum temperature and high tide and positive relationship with rainfall. This study determines the most significant spatial risk factors for BFV disease across Queensland. Empirical models were developed to forecast the future risk of BFV disease outbreaks in coastal Queensland using existing climatic, socio-economic and tidal conditions under climate change scenarios. Logistic regression models were developed using BFV disease outbreak data for the existing period (2000-2008). The most parsimonious model had high sensitivity, specificity and accuracy and this model was used to estimate and forecast BFV disease outbreaks for years 2025, 2050 and 2100 under climate change scenarios for Australia. Important contributions arising from this research are that: (i) it is innovative to identify high-risk coastal areas by creating buffers based on grid-centroid and the use of fine-grained spatial units, i.e., mesh blocks; (ii) a spatial regression method was used to account for spatial dependence and heterogeneity of data in the study area; (iii) it determined a range of potential spatial risk factors for BFV disease; and (iv) it predicted the future risk of BFV disease outbreaks under climate change scenarios in Queensland, Australia. In conclusion, the thesis demonstrates that the distribution of BFV disease exhibits a distinct spatial and temporal variation. Such variation is influenced by a range of spatial risk factors including climatic, demographic, socio-economic, ecological and tidal variables. The thesis demonstrates that spatial regression method can be applied to better understand the transmission dynamics of BFV disease and its risk factors. The research findings show that disease notification data can be integrated with multi-factorial risk factor data to develop build-up models and forecast future potential disease risks under climate change scenarios. This thesis may have implications in BFV disease control and prevention programs in Queensland.

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Epidermal growth factor (EGF) activation of the EGF receptor (EGFR) is an important mediator of cell migration, and aberrant signaling via this system promotes a number of malignancies including ovarian cancer. We have identified the cell surface glycoprotein CDCP1 as a key regulator of EGF/EGFR-induced cell migration. We show that signaling via EGF/EGFR induces migration of ovarian cancer Caov3 and OVCA420 cells with concomitant up-regulation of CDCP1 mRNA and protein. Consistent with a role in cell migration CDCP1 relocates from cell-cell junctions to punctate structures on filopodia after activation of EGFR. Significantly, disruption of CDCP1 either by silencing or the use of a function blocking antibody efficiently reduces EGF/EGFR-induced cell migration of Caov3 and OVCA420 cells. We also show that up-regulation of CDCP1 is inhibited by pharmacological agents blocking ERK but not Src signaling, indicating that the RAS/RAF/MEK/ERK pathway is required downstream of EGF/EGFR to induce increased expression of CDCP1. Our immunohistochemical analysis of benign, primary, and metastatic serous epithelial ovarian tumors demonstrates that CDCP1 is expressed during progression of this cancer. These data highlight a novel role for CDCP1 in EGF/EGFR-induced cell migration and indicate that targeting of CDCP1 may be a rational approach to inhibit progression of cancers driven by EGFR signaling including those resistant to anti-EGFR drugs because of activating mutations in the RAS/RAF/MEK/ERK pathway.

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We develop a stochastic endogenous growth model to explain the diversity in growth and inequality patterns and the non-convergence of incomes in transitional economies where an underdeveloped financial sector imposes an implicit, fixed cost on the diversification of idiosyncratic risk. In the model endogenous growth occurs through physical and human capital deepening, with the latter being the more dominant element. We interpret the fixed cost as a ‘learning by doing’ cost for entrepreneurs who undertake risk in the absence of well developed financial markets and institutions that help diversify such risk. As such, this cost may be interpreted as the implicit returns foregone due to the lack of diversification opportunities that would otherwise have been available, had such institutions been present. The analytical and numerical results of the model suggest three growth outcomes depending on the productivity differences between the projects and the fixed cost associated with the more productive project. We label these outcomes as poverty trap, dual economy and balanced growth. Further analysis of these three outcomes highlights the existence of a diversity within diversity. Specifically, within the ‘poverty trap’ and ‘dual economy’ scenarios growth and inequality patterns differ, depending on the initial conditions. This additional diversity allows the model to capture a richer range of outcomes that are consistent with the empirical experience of several transitional economies.

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Modelling video sequences by subspaces has recently shown promise for recognising human actions. Subspaces are able to accommodate the effects of various image variations and can capture the dynamic properties of actions. Subspaces form a non-Euclidean and curved Riemannian manifold known as a Grassmann manifold. Inference on manifold spaces usually is achieved by embedding the manifolds in higher dimensional Euclidean spaces. In this paper, we instead propose to embed the Grassmann manifolds into reproducing kernel Hilbert spaces and then tackle the problem of discriminant analysis on such manifolds. To achieve efficient machinery, we propose graph-based local discriminant analysis that utilises within-class and between-class similarity graphs to characterise intra-class compactness and inter-class separability, respectively. Experiments on KTH, UCF Sports, and Ballet datasets show that the proposed approach obtains marked improvements in discrimination accuracy in comparison to several state-of-the-art methods, such as the kernel version of affine hull image-set distance, tensor canonical correlation analysis, spatial-temporal words and hierarchy of discriminative space-time neighbourhood features.

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The rapid growth of services available on the Internet and exploited through ever globalizing business networks poses new challenges for service interoperability. New services, from consumer “apps”, enterprise suites, platform and infrastructure resources, are vying for demand with quickly evolving and overlapping capabilities, and shorter cycles of extending service access from user interfaces to software interfaces. Services, drawn from a wider global setting, are subject to greater change and heterogeneity, demanding new requirements for structural and behavioral interface adaptation. In this paper, we analyze service interoperability scenarios in global business networks, and propose new patterns for service interactions, above those proposed over the last 10 years through the development of Web service standards and process choreography languages. By contrast, we reduce assumptions of design-time knowledge required to adapt services, giving way to run-time mismatch resolutions, extend the focus from bilateral to multilateral messaging interactions, and propose declarative ways in which services and interactions take part in long-running conversations via the explicit use of state.

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Background Non-fatal health outcomes from diseases and injuries are a crucial consideration in the promotion and monitoring of individual and population health. The Global Burden of Disease (GBD) studies done in 1990 and 2000 have been the only studies to quantify non-fatal health outcomes across an exhaustive set of disorders at the global and regional level. Neither effort quantified uncertainty in prevalence or years lived with disability (YLDs). Methods Of the 291 diseases and injuries in the GBD cause list, 289 cause disability. For 1160 sequelae of the 289 diseases and injuries, we undertook a systematic analysis of prevalence, incidence, remission, duration, and excess mortality. Sources included published studies, case notification, population-based cancer registries, other disease registries, antenatal clinic serosurveillance, hospital discharge data, ambulatory care data, household surveys, other surveys, and cohort studies. For most sequelae, we used a Bayesian meta-regression method, DisMod-MR, designed to address key limitations in descriptive epidemiological data, including missing data, inconsistency, and large methodological variation between data sources. For some disorders, we used natural history models, geospatial models, back-calculation models (models calculating incidence from population mortality rates and case fatality), or registration completeness models (models adjusting for incomplete registration with health-system access and other covariates). Disability weights for 220 unique health states were used to capture the severity of health loss. YLDs by cause at age, sex, country, and year levels were adjusted for comorbidity with simulation methods. We included uncertainty estimates at all stages of the analysis. Findings Global prevalence for all ages combined in 2010 across the 1160 sequelae ranged from fewer than one case per 1 million people to 350 000 cases per 1 million people. Prevalence and severity of health loss were weakly correlated (correlation coefficient −0·37). In 2010, there were 777 million YLDs from all causes, up from 583 million in 1990. The main contributors to global YLDs were mental and behavioural disorders, musculoskeletal disorders, and diabetes or endocrine diseases. The leading specific causes of YLDs were much the same in 2010 as they were in 1990: low back pain, major depressive disorder, iron-deficiency anaemia, neck pain, chronic obstructive pulmonary disease, anxiety disorders, migraine, diabetes, and falls. Age-specific prevalence of YLDs increased with age in all regions and has decreased slightly from 1990 to 2010. Regional patterns of the leading causes of YLDs were more similar compared with years of life lost due to premature mortality. Neglected tropical diseases, HIV/AIDS, tuberculosis, malaria, and anaemia were important causes of YLDs in sub-Saharan Africa. Interpretation Rates of YLDs per 100 000 people have remained largely constant over time but rise steadily with age. Population growth and ageing have increased YLD numbers and crude rates over the past two decades. Prevalences of the most common causes of YLDs, such as mental and behavioural disorders and musculoskeletal disorders, have not decreased. Health systems will need to address the needs of the rising numbers of individuals with a range of disorders that largely cause disability but not mortality. Quantification of the burden of non-fatal health outcomes will be crucial to understand how well health systems are responding to these challenges. Effective and affordable strategies to deal with this rising burden are an urgent priority for health systems in most parts of the world. Funding Bill & Melinda Gates Foundation.

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This work has led to the development of empirical mathematical models to quantitatively predicate the changes of morphology in osteocyte-like cell lines (MLO-Y4) in culture. MLO-Y4 cells were cultured at low density and the changes in morphology recorded over 11 hours. Cell area and three dimensional shape features including aspect ratio, circularity and solidity were then determined using widely accepted image analysis software (ImageJTM). Based on the data obtained from the imaging analysis, mathematical models were developed using the non-linear regression method. The developed mathematical models accurately predict the morphology of MLO-Y4 cells for different culture times and can, therefore, be used as a reference model for analyzing MLO-Y4 cell morphology changes within various biological/mechanical studies, as necessary.

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Clinical work with people who have survived trauma carries a risk of vicarious traumatisation for the service provider, but also the potential for vicarious posttraumatic growth. Despite growing interest in this area, the effects of working with survivors of refugee-related trauma have remained relatively unexplored. The aim of the current study was to examine the lived experiences of people working on a daily basis with survivors of torture and trauma who had sought refuge in Australia. Seventeen clinical, administrative, and managerial staff from a not-for-profit organisation participated in a semi-structured interview that was later analysed using interpretive phenomenological analysis. Analysis of the data demonstrated that the entire sample reported symptoms of vicarious trauma (e.g., strong emotional reactions, intrusive images, shattering of existing beliefs) as well as vicarious posttraumatic growth (e.g., forming new relationships, increased self-understanding, greater appreciation of life). Moreover, effortful meaning making processes appeared to facilitate such positive changes. Reduction in the risks associated with this work, enhancement of clinician well-being, and improvement of therapeutic outcomes is a shared responsibility of the organisation and clinician. Without negating the distress of trauma work, clinicians are encouraged to more deeply consider the unique positive outcomes that supporting survivors can provide.

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Standard differential equation–based models of collective cell behaviour, such as the logistic growth model, invoke a mean–field assumption which is equivalent to assuming that individuals within the population interact with each other in proportion to the average population density. Implementing such assumptions implies that the dynamics of the system are unaffected by spatial structure, such as the formation of patches or clusters within the population. Recent theoretical developments have introduced a class of models, known as moment dynamics models, which aim to account for the dynamics of individuals, pairs of individuals, triplets of individuals and so on. Such models enable us to describe the dynamics of populations with clustering, however, little progress has been made with regard to applying moment dynamics models to experimental data. Here, we report new experimental results describing the formation of a monolayer of cells using two different cell types: 3T3 fibroblast cells and MDA MB 231 breast cancer cells. Our analysis indicates that the 3T3 fibroblast cells are relatively motile and we observe that the 3T3 fibroblast monolayer forms without clustering. Alternatively, the MDA MB 231 cells are less motile and we observe that the MDA MB 231 monolayer formation is associated with significant clustering. We calibrate a moment dynamics model and a standard mean–field model to both data sets. Our results indicate that the mean–field and moment dynamics models provide similar descriptions of the 3T3 fibroblast monolayer formation whereas these two models give very different predictions for the MDA MD 231 monolayer formation. These outcomes indicate that standard mean–field models of collective cell behaviour are not always appropriate and that care ought to be exercised when implementing such a model.