4DCT radiotherapy for NSCLC: A review of planning methods

Purpose To establish whether the use of a passive or active technique of planning target volume (PTV) definition and treatment methods for non-small cell lung cancer (NSCLC) deliver the most effective results. This literature review assesses the advantages and disadvantages in recent studies of each, while assessing the validity of the two approaches for planning and treatment. Methods A systematic review of literature focusing on the planning and treatment of radiation therapy to NSCLC tumours. Different approaches which have been published in recent articles are subjected to critical appraisal in order to determine their relative efficacy. Results Free-breathing (FB) is the optimal method to perform planning scans for patients and departments, as it involves no significant increase in cost, workload or education. Maximum intensity projection (MIP) is the fastest form of delineation, however it is noted to be less accurate than the ten-phase overlap approach for computed tomography (CT). Although gating has proven to reduce margins and facilitate sparing of organs at risk, treatment times can be longer and planning time can be as much as 15 times higher for intensity modulated radiation therapy (IMRT). This raises issues with patient comfort and stabilisation, impacting on the chance of geometric miss. Stereotactic treatments can take up to 3 hours to treat, along with increases in planning and treatment, as well as the additional hardware, software and training required. Conclusion Four-dimensional computed tomography (4DCT) is superior to 3DCT, with the passive FB approach for PTV delineation and treatment optimal. Departments should use a combination of MIP with visual confirmation ensuring coverage for stage 1 disease. Stages 2-3 should be delineated using ten-phases overlaid. Stereotactic and gated treatments for early stage disease should be used accordingly; FB-IMRT is optimal for latter stage disease.

Predictors of mental health in midlife and older women : results from the Australian Healthy Aging of Women Study

Purpose: To examine the extent to which socio-demographic characteristics, modifiable lifestyle factors and health status influence the mental health of midlife and older Australian women from the Australian Healthy Aging of Women (HOW) study. Methods: Data on health status, chronic disease and modifiable lifestyle factors were collected from a random sample of 340 women aged 40-65 years, residing in Queensland, Australia in 2011. Structural equation modelling (SEM) was used to measure the effect of a range of socio-demographic characteristics (marital status, age, income), modifiable lifestyle factors (caffeine intake, alcohol consumption, exercise, physical activity, sleep), and health markers (self-reported physical health, history of chronic illness) on the latent construct, mental health. Mental health was evaluated using the Medical Outcomes Study Short Form 12 (SF-12®) and the Center for Epidemiologic Studies Depression Scale (CES-D). Results: The model was a good fit for the data (χ2 = 40.166, df =312, p 0.125, CFI = 0.976, TLI = 0.950, RMSEA = 0.030, 90% CI = 0.000-0.053); the model suggested mental health was negatively influenced by sleep disturbance (β = -0.628), sedentary lifestyle (β = -0.137), having been diagnosed with one or more chronic illnesses (β = -0.203), and poor self-reported physical health (β = - 0.161). While mental health was associated with sleep, it was not correlated with many other lifestyle factors (BMI (β = -0.050), alcohol consumption (β = 0.079), or cigarette smoking (β = 0.008)) or background socio-demographic characteristics (age (β = 0.078), or income (β = -0.039)). Conclusion: While research suggests that it is important to engage in a range health promoting behaviours to preserve good health, we found that only sleep disturbance, physical health, chronic illness and level of physical activity predicted current mental health. However, while socio-demographic characteristics and modifiable lifestyle factors seemed to have little direct impact on mental health, they probably had an indirect effect.

What predicts mental health in midlife and older women? Results from the Australian Healthy Aging of Women Study

Objectives: Previous research has linked unhealthy lifestyle with a range of negative health outcomes in women. As women age however, they may have fewer performance expectations, but may view their health more positively. Clearly, the experiences of midlife and older women in relation to health and wellbeing need further exploration. The purpose of this study is to examine the factors associated with poor health-related quality of life in midlife (HRQoL) and older Australian women. Methods: The Australian longitudinal Healthy Aging of Women (HOW) study prospectively examines HRQoL, chronic disease and modifiable lifestyle factors midlife and older women as they age. Random sampling was used to select rural and urban based women from South-East Queensland, Australia. Data were collected from 386 women at three time points over the last decade (2001, 2004 and 2011). Results: The average age of women in this study was 65 years (SD = 2.82). Almost three-quarters (73%, n = 248) of the sample were married or living as though married, nine per cent (n = 30) were separated or divorced and a small proportion were had never married (n = 13). Most (86%, n = 291) of the women sample reported being Australian born, around one quarter (34%, n = 114) had completed additional study since leaving school (university degree or diploma). Over half (55%, n = 186) of participants were retired, one quarter (25%, n = 85) were in paid employment and the remained were unemployed (1%, n = 4), unable to work because of illness (2%, n = 6) or worked within the home (17%, n = 56). Using data collected over time we examined the relationship between a range of modifiable lifestyle factors and mental health using structural equation modelling. The overall model exhibited a good fit with the data. Poor sleep quality was associated with reduced mental health while better mental health was reported in women who exercised regularly and satisfied with their currently weight. As hypothesized, past mental health was a significant mediator of current mental health. Conclusions: These findings demonstrate that the mental health of women is complex and needs to be understood not only in terms of current lifestyle but also in relation to previously reported health status.

World emissions and economic growth: Application of non-parametric methods

The Environmental Kuznets Curve (EKC) hypothesises an inverse U-shaped relationship between a measure of environmental pollution and per capita income levels. In this study, we apply non-parametric estimation of local polynomial regression (local quadratic fitting) to allow more flexibility in local estimation. This study uses a larger and globally representative sample of many local and global pollutants and natural resources including Biological Oxygen Demand (BOD) emission, CO2 emission, CO2 damage, energy use, energy depletion, mineral depletion, improved water source, PM10, particulate emission damage, forest area and net forest depletion. Copyright © 2009 Inderscience Enterprises Ltd.

Agent-based modelling of aircraft boarding methods

We implemented six different boarding strategies (Wilma, Steffen, Reverse Pyramid, Random, Blocks and By letter) in order to investigate boarding times for Boeing 777 and Airbus 380 aircraft. We also introduce three new boarding methods to find the optimum boarding strategy. Our models explicitly simulate the behaviour of groups of people travelling together and we explicitly simulate the timing to store their luggage as part of the boarding process. Results from the simulation demonstrates the Reverse Pyramid method is the best boarding method for Boeing 777, and the Steffen method is the best boarding method for Airbus 380. For the new suggested boarding methods, aisle first boarding method is the best boarding strategy for Boeing 777 and row arrangement method is the best boarding strategy for Airbus 380. Overall best boarding strategy is aisle first boarding method for Boeing 777 and Steffen method for Airbus 380.

An evaluation of crowd counting methods, features and regression models

Existing crowd counting algorithms rely on holistic, local or histogram based features to capture crowd properties. Regression is then employed to estimate the crowd size. Insufficient testing across multiple datasets has made it difficult to compare and contrast different methodologies. This paper presents an evaluation across multiple datasets to compare holistic, local and histogram based methods, and to compare various image features and regression models. A K-fold cross validation protocol is followed to evaluate the performance across five public datasets: UCSD, PETS 2009, Fudan, Mall and Grand Central datasets. Image features are categorised into five types: size, shape, edges, keypoints and textures. The regression models evaluated are: Gaussian process regression (GPR), linear regression, K nearest neighbours (KNN) and neural networks (NN). The results demonstrate that local features outperform equivalent holistic and histogram based features; optimal performance is observed using all image features except for textures; and that GPR outperforms linear, KNN and NN regression

Emotional climate and behavioral management during sleep time in early childhood education settings

The majority of children cease napping between 3 and 5 years of age yet, internationally, the allocation of a sleep time during the day for children of this age remains a practice in many early childhood education (ECE) settings. These dual circumstances present a disjuncture between children's sleep needs and center practices, that may cause conflict for staff, increase stress for children and escalate negative emotional climate in the room. Testing this hypothesis requires observation of both the emotional climate and behavioral management used in ECE rooms that extends into the sleep time. This study was the first to apply the Classroom Assessment and Scoring System (CLASS) Pre-K (Pianta, La Paro, & Hamre, 2008) to observe the emotional climate and behavioral management during sleep time. Pilot results indicated that the CLASS Pre-K functioned reliably to measure emotional climate and behavioral management in sleep time. However, new sleep-specific examples of the dimensions used were developed, to help orient fieldworkers to the CLASS Pre-K rating system in the sleep time context. The CLASS was then used to assess emotional climate and behavior management between the non-sleep and sleep time sessions, in 113 ECE rooms in Queensland, Australia. In these rooms 2.114 children were observed. Of these children, 71% did not sleep at any point during the allotted sleep times. There was a significant drop in emotional climate and behavioral management between the non-sleep and sleep-time sessions. Furthermore, the duration of mandated sleep time (a period of time where no activities are provided to non-sleeping children) accounted for significant independent variance in the observed emotional climate during sleep-time. The CLASS Pre-K presents a valuable tool to assess the emotional climate and behavior management during sleep-time and draws attention to the need for further studies of sleep time in ECE settings.

Application of meshfree methods to numerically simulate microscale deformations of different plant food materials during drying

Plant food materials have a very high demand in the consumer market and therefore, improved food products and efficient processing techniques are concurrently being researched in food engineering. In this context, numerical modelling and simulation techniques have a very high potential to reveal fundamentals of the underlying mechanisms involved. However, numerical modelling of plant food materials during drying becomes quite challenging, mainly due to the complexity of the multiphase microstructure of the material, which undergoes excessive deformations during drying. In this regard, conventional grid-based modelling techniques have limited applicability due to their inflexible grid-based fundamental limitations. As a result, meshfree methods have recently been developed which offer a more adaptable approach to problem domains of this nature, due to their fundamental grid-free advantages. In this work, a recently developed meshfree based two-dimensional plant tissue model is used for a comparative study of microscale morphological changes of several food materials during drying. The model involves Smoothed Particle Hydrodynamics (SPH) and Discrete Element Method (DEM) to represent fluid and solid phases of the cellular structure. Simulation are conducted on apple, potato, carrot and grape tissues and the results are qualitatively and quantitatively compared and related with experimental findings obtained from the literature. The study revealed that cellular deformations are highly sensitive to cell dimensions, cell wall physical and mechanical properties, middle lamella properties and turgor pressure. In particular, the meshfree model is well capable of simulating critically dried tissues at lower moisture content and turgor pressure, which lead to cell wall wrinkling. The findings further highlighted the potential applicability of the meshfree approach to model large deformations of the plant tissue microstructure during drying, providing a distinct advantage over the state of the art grid-based approaches.

Emerging methods in using GIS to analyse Barmah Forest virus disease in Queensland, Australia

Barmah Forest virus (BFV) disease is an emerging mosquito-borne disease in Australia. We aimed to outline some recent methods in using GIS for the analysis of BFV disease in Queensland, Australia. A large database of geocoded BFV cases has been established in conjunction with population data. The database has been used in recently published studies conducted by the authors to determine spatio-temporal BFV disease hotspots and spatial patterns using spatial autocorrelation and semi-variogram analysis in conjunction with the development of interpolated BFV disease standardised incidence maps. This paper briefly outlines spatial analysis methodologies using GIS tools used in those studies. This paper summarises methods and results from previous studies by the authors, and presents a GIS methodology to be used in future spatial analytical studies in attempt to enhance the understanding of BFV disease in Queensland. The methodology developed is useful in improving the analysis of BFV disease data and will enhance the understanding of the BFV disease distribution in Queensland, Australia.