842 resultados para good lives model


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One in five Australian workers believes that work doesn’t fit well with their family and social commitments. Concurrently, organisations are recognising that to stay competitive they need policies and practices that support the multiple aspects of employees’ lives. Many employees work in group environments yet there is currently little group level work-life balance research. This paper proposes a new theoretical framework developed to understand the design of work groups to better facilitate work-life balance. This new framework focuses on task and relational job designs, group structures and processes and workplace culture.

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A fractional differential equation is used to describe a fractal model of mobile/immobile transport with a power law memory function. This equation is the limiting equation that governs continuous time random walks with heavy tailed random waiting times. In this paper, we firstly propose a finite difference method to discretize the time variable and obtain a semi-discrete scheme. Then we discuss its stability and convergence. Secondly we consider a meshless method based on radial basis functions (RBFs) to discretize the space variable. In contrast to conventional FDM and FEM, the meshless method is demonstrated to have distinct advantages: calculations can be performed independent of a mesh, it is more accurate and it can be used to solve complex problems. Finally the convergence order is verified from a numerical example which is presented to describe a fractal model of mobile/immobile transport process with different problem domains. The numerical results indicate that the present meshless approach is very effective for modeling and simulating fractional differential equations, and it has good potential in the development of a robust simulation tool for problems in engineering and science that are governed by various types of fractional differential equations.

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One in five Australian workers believes that work doesn’t fit well with their family and social commitments. Concurrently, organisations are recognising that to stay competitive they need policies and practices that support the multiple aspects of employees’ lives. Many employees work in group environments yet there is currently little group level work-life balance research. This paper proposes a new theoretical framework developed to understand the design of work groups to better facilitate work-life balance. This new framework focuses on task and relational job designs, group structures and processes and workplace culture.

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Stagnation-point total heat transfer was measured on a 1:27.7 model of the Flight Investigation of Reentry Environment II flight vehicle. Experiments were performed in the X1 expansion tube at an equivalent flight velocity and static enthalpy of 11 km/s and 12.7 MJ/kg, respectively. Conditions were chosen to replicate the flight condition at a total flight time of 1639.5 s, where radiation contributed an estimated 17-36% of the total heat transfer. This contribution is theorized to reduce to <2% in the scaled experiments, and the heating environment on the test model was expected to be dominated by convection. A correlation between reported flight heating rates and expected experimental heating, referred to as the reduced flight value, was developed to predict the level of heating expected on the test model. At the given flow conditions, the reduced flight value was calculated to be 150 MW/m2. Average stagnation-point total heat transfer was measured to be 140 ± 7% W/m2, showing good agreement with the predicted value. Experimentally measured heat transfer was found to have good agreement of between 5 and 15% with a number of convective heating correlations, confirming that convection dominates the tunnel heating environment, and that useful experimental measurements could be made in weakly coupled radiating flow

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Travel time estimation and prediction on motorways has long been a topic of research. Prediction modeling generally assumes that the estimation is perfect. No matter how good is the prediction modeling- the errors in estimation can significantly deteriorate the accuracy and reliability of the prediction. Models have been proposed to estimate travel time from loop detector data. Generally, detectors are closely spaced (say 500m) and travel time can be estimated accurately. However, detectors are not always perfect, and even during normal running conditions few detectors malfunction, resulting in increase in the spacing between the functional detectors. Under such conditions, error in the travel time estimation is significantly large and generally unacceptable. This research evaluates the in-practice travel time estimation model during different traffic conditions. It is observed that the existing models fail to accurately estimate travel time during large detector spacing and congestion shoulder periods. Addressing this issue, an innovative Hybrid model that only considers loop data for travel time estimation is proposed. The model is tested using simulation and is validated with real Bluetooth data from Pacific Motorway Brisbane. Results indicate that during non free flow conditions and larger detector spacing Hybrid model provides significant improvement in the accuracy of travel time estimation.

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The concept of the lifelong learner—the idea that people should be active learners throughout the lifespan—has since the 1990s gained importance in public policy. Governments in relatively wealthy countries have made the argument that the economic future of nations is tied to the ongoing participation of citizens in learning opportunities that will assist them to participate fully in society and increase their chances of employment in changing workforce conditions. More recently, policy attention has focused on the other end of the lifespan, the first years of life. With the early years now recognised as crucial for later educational success, policy attention has also focused on the importance of parenting in the early years. In the UK and Australia, for example, the effects of state interventions to facilitate ‘good parenting’ and pre-school children’s ‘readiness’ for formal schooling have been felt in a range of settings including community health services, the home and the pre-school (Gillies, 2005; Nichols & Jurvansuu, 2008; Millei & Lee, 2007; Vincent, Ball & Braun, 2010). In Australia, government policy has explicitly proposed a model of parenting as a learning process, and has urged people to cultivate their identities as learners in order to carry out their responsibilities as parents. In part the policy objectives have been to support parents to ensure that all children get a healthy and successful start to life...

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Due to the health impacts caused by exposures to air pollutants in urban areas, monitoring and forecasting of air quality parameters have become popular as an important topic in atmospheric and environmental research today. The knowledge on the dynamics and complexity of air pollutants behavior has made artificial intelligence models as a useful tool for a more accurate pollutant concentration prediction. This paper focuses on an innovative method of daily air pollution prediction using combination of Support Vector Machine (SVM) as predictor and Partial Least Square (PLS) as a data selection tool based on the measured values of CO concentrations. The CO concentrations of Rey monitoring station in the south of Tehran, from Jan. 2007 to Feb. 2011, have been used to test the effectiveness of this method. The hourly CO concentrations have been predicted using the SVM and the hybrid PLS–SVM models. Similarly, daily CO concentrations have been predicted based on the aforementioned four years measured data. Results demonstrated that both models have good prediction ability; however the hybrid PLS–SVM has better accuracy. In the analysis presented in this paper, statistic estimators including relative mean errors, root mean squared errors and the mean absolute relative error have been employed to compare performances of the models. It has been concluded that the errors decrease after size reduction and coefficients of determination increase from 56 to 81% for SVM model to 65–85% for hybrid PLS–SVM model respectively. Also it was found that the hybrid PLS–SVM model required lower computational time than SVM model as expected, hence supporting the more accurate and faster prediction ability of hybrid PLS–SVM model.

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This report describes the key findings of a longitudinal study (2004—2008) investigating the experiences of settlement among a group of 120 recently arrived young people with refugee backgrounds settling in Melbourne, Australia. Each year, less than one per cent of the world’s refugees are offered resettlement in one of 18 countries participating in The Office of the United Nations High Commissioner for Refugees (UNHCR) resettlement programme. Australia offers places to around 13,500 people per year, of whom about 26 per cent are between the ages of 10 and 19. What are the experiences of these young people in their early settlement years? How do they negotiate the transition from childhood to adulthood given the traumas of their past and the challenges of their present and future in Australia? What are the key social determinants of wellbeing and good settlement and what can we learn from these young people about what social policies and services will most effectively support them to make successful lives in their new home? This study explores these questions, the overall aim being to identify the key social determinants of wellbeing and settlement and to describe the lived experiences of these young people as they shape their lives in Australia.

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Parabolic trough concentrator collector is the most matured, proven and widespread technology for the exploitation of the solar energy on a large scale for middle temperature applications. The assessment of the opportunities and the possibilities of the collector system are relied on its optical performance. A reliable Monte Carlo ray tracing model of a parabolic trough collector is developed by using Zemax software. The optical performance of an ideal collector depends on the solar spectral distribution and the sunshape, and the spectral selectivity of the associated components. Therefore, each step of the model, including the spectral distribution of the solar energy, trough reflectance, glazing anti-reflection coating and the absorber selective coating is explained and verified. Radiation flux distribution around the receiver, and the optical efficiency are two basic aspects of optical simulation are calculated using the model, and verified with widely accepted analytical profile and measured values respectively. Reasonably very good agreement is obtained. Further investigations are carried out to analyse the characteristics of radiation distribution around the receiver tube at different insolation, envelop conditions, and selective coating on the receiver; and the impact of scattered light from the receiver surface on the efficiency. However, the model has the capability to analyse the optical performance at variable sunshape, tracking error, collector imperfections including absorber misalignment with focal line and de-focal effect of the absorber, different rim angles, and geometric concentrations. The current optical model can play a significant role in understanding the optical aspects of a trough collector, and can be employed to extract useful information on the optical performance. In the long run, this optical model will pave the way for the construction of low cost standalone photovoltaic and thermal hybrid collector in Australia for small scale domestic hot water and electricity production.

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Parametric roll is a critical phenomenon for ships, whose onset may cause roll oscillations up to +-40 degrees, leading to very dangerous situations and possibly capsizing. Container ships have been shown to be particularly prone to parametric roll resonance when they are sailing in moderate to heavy head seas. A Matlab/Simulink parametric roll benchmark model for a large container ship has been implemented and validated against a wide set of experimental data. The model is a part of a Matlab/Simulink Toolbox (MSS, 2007). The benchmark implements a 3rd-order nonlinear model where the dynamics of roll is strongly coupled with the heave and pitch dynamics. The implemented model has shown good accuracy in predicting the container ship motions, both in the vertical plane and in the transversal one. Parametric roll has been reproduced for all the data sets in which it happened, and the model provides realistic results which are in good agreement with the model tank experiments.

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Plant tissue has a complex cellular structure which is an aggregate of individual cells bonded by middle lamella. During drying processes, plant tissue undergoes extreme deformations which are mainly driven by moisture removal and turgor loss. Numerical modelling of this problem becomes challenging when conventional grid-based modelling techniques such as Finite Element Methods (FEM) and Finite Difference Methods (FDM) have grid-based limitations. This work presents a meshfree approach to model and simulate the deformations of plant tissues during drying. This method demonstrates the fundamental capabilities of meshfree methods in handling extreme deformations of multiphase systems. A simplified 2D tissue model is developed by aggregating individual cells while accounting for the stiffness of the middle lamella. Each individual cell is simply treated as consisting of two main components: cell fluid and cell wall. The cell fluid is modelled using Smoothed Particle Hydrodynamics (SPH) and the cell wall is modelled using a Discrete Element Method (DEM). During drying, moisture removal is accounted for by reduction of cell fluid and wall mass, which causes local shrinkage of cells eventually leading to tissue scale shrinkage. The cellular deformations are quantified using several cellular geometrical parameters and a favourably good agreement is observed when compared to experiments on apple tissue. The model is also capable of visually replicating dry tissue structures. The proposed model can be used as a step in developing complex tissue models to simulate extreme deformations during drying.

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Motivated by the analysis of the Australian Grain Insect Resistance Database (AGIRD), we develop a Bayesian hurdle modelling approach to assess trends in strong resistance of stored grain insects to phosphine over time. The binary response variable from AGIRD indicating presence or absence of strong resistance is characterized by a majority of absence observations and the hurdle model is a two step approach that is useful when analyzing such a binary response dataset. The proposed hurdle model utilizes Bayesian classification trees to firstly identify covariates and covariate levels pertaining to possible presence or absence of strong resistance. Secondly, generalized additive models (GAMs) with spike and slab priors for variable selection are fitted to the subset of the dataset identified from the Bayesian classification tree indicating possibility of presence of strong resistance. From the GAM we assess trends, biosecurity issues and site specific variables influencing the presence of strong resistance using a variable selection approach. The proposed Bayesian hurdle model is compared to its frequentist counterpart, and also to a naive Bayesian approach which fits a GAM to the entire dataset. The Bayesian hurdle model has the benefit of providing a set of good trees for use in the first step and appears to provide enough flexibility to represent the influence of variables on strong resistance compared to the frequentist model, but also captures the subtle changes in the trend that are missed by the frequentist and naive Bayesian models.

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Radiosensitizing Effect of Electrochemotherapy in a Fractionated Radiation Regimen in Radiosensitive Murine Sarcoma and Radioresistant Adenocarcinoma Tumor Model. Electrochemotherapy can potentiate the radiosensitizing effect of bleomycin, as shown in our previous studies. To bring this treatment closer to use in clinical practice, we evaluated the interaction between electrochemotherapy with bleomycin and single-dose or fractionated radiation in two murine tumor models with different histology and radiosensitivity. Radiosensitive sarcoma SA-1 and radioresistant adenocarcinoma CaNT subcutaneous tumors grown in A/J and CBA mice, respectively, were used. The anti-tumor effect and skin damage around the treated tumors were evaluated after electrochemotherapy with bleomycin alone or combined with single-dose radiation or a fractionated radiation regimen. The anti-tumor effectiveness of electrochemotherapy was more pronounced in SA-1 than CaNT tumors. In both tumor models, the tumor response to radiation was not significantly influenced by bleomycin alone or by electroporation alone. However, electrochemotherapy before the first tumor irradiation potentiated the response to a single-dose or fractionated radiation regimen in both tumors. For the fractionated radiation regimen, normal skin around the treated tumors was damaged fourfold less than for the single-dose regimen. Electrochemotherapy prior to single-dose irradiation induced more damage to the skin around the treated tumors and greater loss of body weight compared to other irradiated groups, whereas electrochemotherapy combined with the fractionated radiation regimen did not. Electrochemotherapy with low doses of bleomycin can also be used safely for radiosensitization of different types of tumors in a fractionated radiation regimen, resulting in a good anti-tumor effect and no major potentiating effect on radiation-induced skin damage. © 2009 by Radiation Research Society.

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Fundamental understanding on microscopic physical changes of plant materials is vital to optimize product quality and processing techniques, particularly in food engineering. Although grid-based numerical modelling can assist in this regard, it becomes quite challenging to overcome the inherited complexities of these biological materials especially when such materials undergo critical processing conditions such as drying, where the cellular structure undergoes extreme deformations. In this context, a meshfree particle based model was developed which is fundamentally capable of handling extreme deformations of plant tissues during drying. The model is built by coupling a particle based meshfree technique: Smoothed Particle Hydrodynamics (SPH) and a Discrete Element Method (DEM). Plant cells were initiated as hexagons and aggregated to form a tissue which also accounts for the characteristics of the middle lamella. In each cell, SPH was used to model cell protoplasm and DEM was used to model the cell wall. Drying was incorporated by varying the moisture content, the turgor pressure, and cell wall contraction effects. Compared to the state of the art grid-based microscale plant tissue drying models, the proposed model can be used to simulate tissues under excessive moisture content reductions incorporating cell wall wrinkling. Also, compared to the state of the art SPH-DEM tissue models, the proposed model better replicates real tissues and the cell-cell interactions used ensure efficient computations. Model predictions showed good agreement both qualitatively and quantitatively with experimental findings on dried plant tissues. The proposed modelling approach is fundamentally flexible to study different cellular structures for their microscale morphological changes at dehydration.

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Until recently, the low-abundance (LA) range of the serum proteome was an unexplored reservoir of diagnostic information. Today it is increasingly appreciated that a diagnostic goldmine of LA biomarkers resides in the blood stream in complexed association with more abundant higher molecular weight carrier proteins such as albumin and immunoglobulins. As we now look to the possibility of harvesting these LA biomarkers more efficiently through engineered nano-scale particles, mathematical approaches are needed in order to reveal the mechanisms by which blood carrier proteins act as molecular 'mops' for LA diagnostic cargo, and the functional relationships between bound LA biomarker concentrations and other variables of interest such as biomarker intravasation and clearance rates and protein half-lives in the bloodstream. Here we show, by simple mathematical modeling, how the relative abundance of large carrier proteins and their longer half-lives in the bloodstream work together to amplify the total blood concentration of these tiny biomarkers. The analysis further suggests that alterations in the production of biomarkers lead to gradual rather than immediate changes in biomarker levels in the blood circulation. The model analysis also points to the characteristics of artificial nano-particles that would render them more efficient harvesters of tumor biomarkers in the circulation, opening up possibilities for the early detection of curable disease, rather than simply better detection of advanced disease.