240 resultados para retirement support model


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This study applied the affect heuristic model to investigate key psychological factors (affective associations, perceived benefits, and costs of wood heating) contributing to public support for three distinct types of wood smoke mitigation policies: education, incentives, and regulation. The sample comprised 265 residents of Armidale, an Australian regional community adversely affected by winter wood smoke pollution. Our results indicate that residents with stronger positive affective associations with wood heating expressed less support for wood smoke mitigation policies involving regulation. This relationship was fully mediated by expected benefits and costs associated with wood heating. Affective associations were unrelated to public support for policies involving education and incentives, which were broadly endorsed by all segments of the community, and were more strongly associated with rational considerations. Latent profile analysis revealed no evidence to support the proposition that some community members experience internal “heart versus head” conflicts in which their positive affective associations with wood heating would be at odds with their risk judgments about the dangers of wood smoke pollution. Affective associations and cost/benefit judgments were very consistent with each other.

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Occupational stress research has consistently demonstrated negative effects for employees. Research also describes potential moderators of this relationship. While research has revealed some positive effects of emotional intelligence (EI) on employee adjustment, it has neglected investigation of their potential stress buffering effects. Based on the Job-Demand Resources model, it was predicted that higher trait emotional intelligence would act as a buffer to the potential negative effects of stressors on employee adjustment. Hierarchical multiple regression analyses with a sample of 306 nurses found no main effects of EI but revealed eight moderating effects. While some interactions support the buffering hypothesis, others revealed buffering for those with low EI. Findings are discussed in terms of theoretical and practical implications.

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This paper proposes a new multi-resource multi-stage scheduling problem for optimising the open-pit drilling, blasting and excavating operations under equipment capacity constraints. The flow process is analysed based on the real-life data from an Australian iron ore mine site. The objective of the model is to maximise the throughput and minimise the total idle times of equipment at each stage. The following comprehensive mining attributes and constraints have been considered: types of equipment; operating capacities of equipment; ready times of equipment; speeds of equipment; block-sequence-dependent movement times of equipment; equipment-assignment-dependent operation times of blocks; distances between each pair of blocks; due windows of blocks; material properties of blocks; swell factors of blocks; and slope requirements of blocks. It is formulated by mixed integer programming and solved by ILOG-CPLEX optimiser. The proposed model is validated with extensive computational experiments to improve mine production efficiency at the operational level. The model also provides an intelligent decision support tool to account for the availability and usage of equipment units for drilling, blasting and excavating stages.

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Background Extracorporeal membrane oxygenation (ECMO) circuits have been shown to sequester circulating blood compounds such as drugs based on their physicochemical properties. This study aimed to describe the disposition of macro- and micronutrients in simulated ECMO circuits. Methods Following baseline sampling, known quantities of macro- and micronutrients were injected post oxygenator into ex vivo ECMO circuits primed with the fresh human whole blood and maintained under standard physiologic conditions. Serial blood samples were then obtained at 1, 30 and 60 min and at 6, 12 and 24 h after the addition of nutrients, to measure the concentrations of study compounds using validated assays. Results Twenty-one samples were tested for thirty-one nutrient compounds. There were significant reductions (p < 0.05) in circuit concentrations of some amino acids [alanine (10%), arginine (95%), cysteine (14%), glutamine (25%) and isoleucine (7%)], vitamins [A (42%) and E (6%)] and glucose (42%) over 24 h. Significant increases in circuit concentrations (p < 0.05) were observed over time for many amino acids, zinc and vitamin C. There were no significant reductions in total proteins, triglycerides, total cholesterol, selenium, copper, manganese and vitamin D concentrations within the ECMO circuit over a 24-h period. No clear correlation could be established between physicochemical properties and circuit behaviour of tested nutrients. Conclusions Significant alterations in macro- and micronutrient concentrations were observed in this single-dose ex vivo circuit study. Most significantly, there is potential for circuit loss of essential amino acid isoleucine and lipid soluble vitamins (A and E) in the ECMO circuit, and the mechanisms for this need further exploration. While the reductions in glucose concentrations and an increase in other macro- and micronutrient concentrations probably reflect cellular metabolism and breakdown, the decrement in arginine and glutamine concentrations may be attributed to their enzymatic conversion to ornithine and glutamate, respectively. While the results are generally reassuring from a macronutrient perspective, prospective studies in clinical subjects are indicated to further evaluate the influence of ECMO circuit on micronutrient concentrations and clinical outcomes.

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This paper presents a layered framework for the purposes of integrating different Socio-Technical Systems (STS) models and perspectives into a whole-of-systems model. Holistic modelling plays a critical role in the engineering of STS due to the interplay between social and technical elements within these systems and resulting emergent behaviour. The framework decomposes STS models into components, where each component is either a static object, dynamic object or behavioural object. Based on existing literature, a classification of the different elements that make up STS, whether it be a social, technical or a natural environment element, is developed; each object can in turn be classified according to the STS elements it represents. Using the proposed framework, it is possible to systematically decompose models to an extent such that points of interface can be identified and the contextual factors required in transforming the component of one model to interface into another is obtained. Using an airport inbound passenger facilitation process as a case study socio-technical system, three different models are analysed: a Business Process Modelling Notation (BPMN) model, Hybrid Queue-based Bayesian Network (HQBN) model and an Agent Based Model (ABM). It is found that the framework enables the modeller to identify non-trivial interface points such as between the spatial interactions of an ABM and the causal reasoning of a HQBN, and between the process activity representation of a BPMN and simulated behavioural performance in a HQBN. Such a framework is a necessary enabler in order to integrate different modelling approaches in understanding and managing STS.

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Design deals with improving the lives of people. As such interactions with products, interfaces, and systems should facilitate not only usable and practical concerns but also mediate emotionally meaningful experiences. This paper presents an integrated and comprehensive model of experience, labeled 'Unified User Experience Model', covering the most prominent perspectives from across the design field. It is intended to support designers from different disciplines to consider the complexity of user experience. The vision of the model is to support both the analysis of existing products, interfaces, and systems, as well as the development of new designs that take into account this complexity. In essence, we hope the model can enable designers to develop more marketable, appropriate, and enhanced products to improve experiences and ultimately the lives of people.

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Energy efficient embedded computing enables new application scenarios in mobile devices like software-defined radio and video processing. The hierarchical multiprocessor considered in this work may contain dozens or hundreds of resource efficient VLIW CPUs. Programming this number of CPU cores is a complex task requiring compiler support. The stream programming paradigm provides beneficial properties that help to support automatic partitioning. This work describes a compiler for streaming applications targeting the self-build hierarchical CoreVA-MPSoC multiprocessor platform. The compiler is supported by a programming model that is tailored to fit the streaming programming paradigm. We present a novel simulated-annealing (SA) based partitioning algorithm, called Smart SA. The overall speedup of Smart SA is 12.84 for an MPSoC with 16 CPU cores compared to a single CPU implementation. Comparison with a state of the art partitioning algorithm shows an average performance improvement of 34.07%.

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This chapter provides an introduction to the use of pedagogical patterns in capturing and sharing educational design experience. In higher education, helping students to learn to engage in productive reflection presents a complex set of challenges. Delicate balances must be found: too little structure and support for students’ reflective work can leave them floundering; too much, and some will remain dependent. Moreover, this is a dynamic teaching problem – scaffolding needs to be adjusted as students develop confidence and capability, which they will do at different rates. The model presented in this chapter embraces the three main elements that teachers can legitimately design, or help set in place, to support their students’ reflective activity: good tasks, the right tools, and appropriate divisions of labour. It delineates a complex, shifting architecture of tasks, tools and people, activities and outcomes associated with reflective learning. It shows how the designable elements of this complex mix can be described in patterns and pattern languages, which then become design resources for teachers’ own action, reflection and professional development.

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Introduction Hydrogels prepared from poly(ethylene glycol) (PEG) and maleimide-functionalized heparin provide a potential matrix for use in developing three dimensional (3D) models. We have previously demonstrated that these hydrogels support the cultivation of human umbilical vein endothelial cells (HUVECs) (1). We extend this body of work to study the ability to create an extracellular matrix (ECM)-like model to study breast and prostate cancer cell growth in 3D. Also, we investigate the ability to produce a tri-culture mimicking tumour angiogenesis with cancer spheroids, HUVECs and mesenchymal stem cells (MSC). Materials and Methods The breast cancer cell lines, MCF-7 and MDA-MB-231, and prostate cancer cell lines, LNCaP and PC3, were seeded into starPEG-heparin hydrogels and grown for 14 Days to analyse the effects of varying hydrogel stiffness on spheroid development. Resulting hydrogel constructs were analyzed via Alamar Blue assays, light microscopy, and immunofluorescence staining for cytokeratin 8/18, Ki67 and E-Cadherin. Cancer cell lines were then pre-grown in hydrogels for 5-7 days and then re-seeded into starPEG-heparin hydrogels functionalised with RGD, SDF-1, bFGF and VEGF as spheroids with HUVECs and MSC and grown for 14 days as a tri-culture in Endothelial Cell Growth Medium (ECGM; Promocell). Cell lines were also seeded as a single cell suspension into the functionalised tri-culture system. Cultures were fixed in 4% paraformaldehyde and analysed via immunostaining for Von Willebrand Factor and CD31, as well as the above mentioned markers, and observed using confocal microscopy. Results Cultures prepared in MMP-cleavable starPEG-heparin hydrogels display spheroid formation in contrast to adherent growth on tissue culture plastic. Small differences were visualised in cancer spheroid growth between different gel stiffness across the range of cell lines. Cancer cell lines were able to be co-cultivated with HUVECs and MSC. HUVEC tube formation and cancer line spheroid formation occured after 3-4 days. Interaction was visualised between tumours and HUVECs via confocal microscopy. Slightly increased interaction was seen between cancer tumours and micro-vascular tubes when seeded as single cells compared with the pre-formed spheroid approach. Further studies intend to utilise cytokine gradients to further optimise the ECM environment of in situ tumour angiogenesis. Discussion and Conclusions Our results confirm the suitability of hydrogels constructed from starPEG-heparin for HUVECs and MSC co-cultivation with cancer cell lines to study cell-cell and cell-matrix interactions in a 3D environment. This represents a step forward in the development of 3D culture models to study the pathomechanisms of breast and prostate cancer. References 1. Tsurkan MV, Chwalek K, Prokoph S, Zieris A, Levental KR, Freudenberg U, Werner C. Advanced Materials. 25, 2606-10, 2013. Disclosures The authors declare no conflicts of interest

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A FitzHugh-Nagumo monodomain model has been used to describe the propagation of the electrical potential in heterogeneous cardiac tissue. In this paper, we consider a two-dimensional fractional FitzHugh-Nagumo monodomain model on an irregular domain. The model consists of a coupled Riesz space fractional nonlinear reaction-diffusion model and an ordinary differential equation, describing the ionic fluxes as a function of the membrane potential. Secondly, we use a decoupling technique and focus on solving the Riesz space fractional nonlinear reaction-diffusion model. A novel spatially second-order accurate semi-implicit alternating direction method (SIADM) for this model on an approximate irregular domain is proposed. Thirdly, stability and convergence of the SIADM are proved. Finally, some numerical examples are given to support our theoretical analysis and these numerical techniques are employed to simulate a two-dimensional fractional Fitzhugh-Nagumo model on both an approximate circular and an approximate irregular domain.

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Tumour microenvironment greatly influences the development and metastasis of cancer progression. The development of three dimensional (3D) culture models which mimic that displayed in vivo can improve cancer biology studies and accelerate novel anticancer drug screening. Inspired by a systems biology approach, we have formed 3D in vitro bioengineered tumour angiogenesis microenvironments within a glycosaminoglycan-based hydrogel culture system. This microenvironment model can routinely recreate breast and prostate tumour vascularisation. The multiple cell types cultured within this model were less sensitive to chemotherapy when compared with two dimensional (2D) cultures, and displayed comparative tumour regression to that displayed in vivo. These features highlight the use of our in vitro culture model as a complementary testing platform in conjunction with animal models, addressing key reduction and replacement goals of the future. We anticipate that this biomimetic model will provide a platform for the in-depth analysis of cancer development and the discovery of novel therapeutic targets.

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This paper investigates a five-factor model of mentoring for effective teaching. A survey was administered to 218 student teachers after student teaching to provide insights into their mentoring experience. Results indicated the five factors, namely, personal attributes, system requirements, pedagogical knowledge, modeling, and feedback, had Cronbach alpha scores of .93, .81, .95, .91, and .91, respectively with mean scale scores ranging from 4.20 to 4.60 (p< .001). Items associated with each factor were analyzed; the lowest percentage response was reviewing lesson plans (71%) and the highest percentage was modeling effective teaching practices (96%). Triangulated data from the survey results suggested that the practices implemented by the mentor teachers were perceived to have supported the student teachers’ development during student teaching. Implications of this study suggest that actively engaging mentor teachers who apply the principles outlined by the five factor areas will serve to ensure highly effective support for the development of student teachers.

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Reflective thinking is an important skill in psychology, both as a tool in the therapeutic process and in professional development. The adapted 4Rs Model provides reflective writing structure and highlights the importance of Reporting & Responding, Relating, Reasoning and Reconstructing to students who are new to writing reflections. This chapter presents a case in which the 4Rs model (modified from the 5Rs model in Chap. 2 of this edition) was adopted to support reflective writing skills of undergraduate psychology students in a first year unit and in a final year unit. Although all students reflected on their learning within the units, the support activities leading up to the reflective tasks were adjusted to account for differences in the abilities of the cohorts and the focus of the units. In an evaluation survey, both groups of students endorsed statements about the importance of reflections and the utility of using the model. First year students also reported some difficulties understanding the 4Rs. This chapter will explore how first and final year students can be supported to develop reflection skills through scaffolding and modification of the same approaches and model.

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This paper introduces the smooth transition logit (STL) model that is designed to detect and model situations in which there is structural change in the behaviour underlying the latent index from which the binary dependent variable is constructed. The maximum likelihood estimators of the parameters of the model are derived along with their asymptotic properties, together with a Lagrange multiplier test of the null hypothesis of linearity in the underlying latent index. The development of the STL model is motivated by the desire to assess the impact of deregulation in the Queensland electricity market and ascertain whether increased competition has resulted in significant changes in the behaviour of the spot price of electricity, specifically with respect to the occurrence of periodic abnormally high prices. The model allows the timing of any change to be endogenously determined and also market participants' behaviour to change gradually over time. The main results provide clear evidence in support of a structural change in the nature of price events, and the endogenously determined timing of the change is consistent with the process of deregulation in Queensland.