194 resultados para Structured settlements


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In this work, we have developed a new efficient hole transport material (HTM) composite based on poly(3- hexylthiophene) (P3HT) and bamboo-structured carbon nanotubes (BCNs) for CH3NH3PbI3 (MAPbI3) based perovskite solar cells. Compared to pristine P3HT, it is found that the crystallinity of P3HT was significantly improved by addition of BCNs, which led to over one order of magnitude higher conductivity for the composite containing 1–2 wt% BCNs in P3HT. In the meantime, the interfacial charge transfer between the MAPbI3 light absorbing layer and the HTM composite layer based on P3HT/BCNs was two-fold faster than pristine P3HT. More importantly, the HTM film with a superior morphological structure consisting of closely compact large grains was achieved with the composite containing 1 wt% BCNs in P3HT. The study by electrochemical impedance spectroscopy has confirmed that the electron recombination in the solar cells was reduced nearly ten-fold with the addition of 1 wt% carbon nanotubes in the HTM composite. Owing to the superior HTM film morphology and the significantly reduced charge recombination, the energy conversion efficiency of the perovskite solar cells increased from 3.6% for pristine P3HT to 8.3% for P3HT/(1 wt% BCNs) with a significantly enhanced open circuit voltage (Voc) and fill factor (FF). The findings of this work are important for development of new HTM for high performance perovskite solar cells.

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Within online learning communities, receiving timely and meaningful insights into the quality of learning activities is an important part of an effective educational experience. Commonly adopted methods – such as the Community of Inquiry framework – rely on manual coding of online discussion transcripts, which is a costly and time consuming process. There are several efforts underway to enable the automated classification of online discussion messages using supervised machine learning, which would enable the real-time analysis of interactions occurring within online learning communities. This paper investigates the importance of incorporating features that utilise the structure of on-line discussions for the classification of "cognitive presence" – the central dimension of the Community of Inquiry framework focusing on the quality of students' critical thinking within online learning communities. We implemented a Conditional Random Field classification solution, which incorporates structural features that may be useful in increasing classification performance over other implementations. Our approach leads to an improvement in classification accuracy of 5.8% over current existing techniques when tested on the same dataset, with a precision and recall of 0.630 and 0.504 respectively.

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A new method for fabricating hydrogels with intricate control over hierarchical 3D porosity using micro-fiber porogens is presented. Melt electrospinning writing of poly(ε-caprolactone) is used to create the sacrificial template leading to hierarchical structuring consisting of pores inside the denser poly(2-oxazoline) hydrogel mesh. This versatile approach provides new opportunities to create well-defined multilevel control over interconnected pores with diameters in the lower micrometer range inside hydrogels with potential applications as cell scaffolds with tunable diffusion and transport of, e.g. nutrients, growth factors or therapeutics.

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The cost effectiveness of antimicrobial stewardship (AMS) programmes was reviewed in hospital settings of Organisation for Economic Co-operation and Development (OECD) countries, and limited to adult patient populations. In each of the 36 studies, the type of AMS strategy and the clinical and cost outcomes were evaluated. The main AMS strategy implemented was prospective audit with intervention and feedback (PAIF), followed by the use of rapid technology, including rapid polymerase chain reaction (PCR)-based methods and matrix-assisted laser desorption/ionisation time-of-flight (MALDI-TOF) technology, for the treatment of bloodstream infections. All but one of the 36 studies reported that AMS resulted in a reduction in pharmacy expenditure. Among 27 studies measuring changes to health outcomes, either no change was reported post-AMS, or the additional benefits achieved from these outcomes were not quantified. Only two studies performed a full economic evaluation: one on a PAIF-based AMS intervention; and the other on use of rapid technology for the selection of appropriate treatment for serious Staphylococcus aureus infections. Both studies found the interventions to be cost effective. AMS programmes achieved a reduction in pharmacy expenditure, but there was a lack of consistency in the reported cost outcomes making it difficult to compare between interventions. A failure to capture complete costs in terms of resource use makes it difficult to determine the true cost of these interventions. There is an urgent need for full economic evaluations that compare relative changes both in clinical and cost outcomes to enable identification of the most cost-effective AMS strategies in hospitals.

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This paper addresses the problem of discovering business process models from event logs. Existing approaches to this problem strike various tradeoffs between accuracy and understandability of the discovered models. With respect to the second criterion, empirical studies have shown that block-structured process models are generally more understandable and less error-prone than unstructured ones. Accordingly, several automated process discovery methods generate block-structured models by construction. These approaches however intertwine the concern of producing accurate models with that of ensuring their structuredness, sometimes sacrificing the former to ensure the latter. In this paper we propose an alternative approach that separates these two concerns. Instead of directly discovering a structured process model, we first apply a well-known heuristic technique that discovers more accurate but sometimes unstructured (and even unsound) process models, and then transform the resulting model into a structured one. An experimental evaluation shows that our “discover and structure” approach outperforms traditional “discover structured” approaches with respect to a range of accuracy and complexity measures.

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This research work analyses techniques for implementing a cell-centred finite-volume time-domain (ccFV-TD) computational methodology for the purpose of studying microwave heating. Various state-of-the-art spatial and temporal discretisation methods employed to solve Maxwell's equations on multidimensional structured grid networks are investigated, and the dispersive and dissipative errors inherent in those techniques examined. Both staggered and unstaggered grid approaches are considered. Upwind schemes using a Riemann solver and intensity vector splitting are studied and evaluated. Staggered and unstaggered Leapfrog and Runge-Kutta time integration methods are analysed in terms of phase and amplitude error to identify which method is the most accurate and efficient for simulating microwave heating processes. The implementation and migration of typical electromagnetic boundary conditions. from staggered in space to cell-centred approaches also is deliberated. In particular, an existing perfectly matched layer absorbing boundary methodology is adapted to formulate a new cell-centred boundary implementation for the ccFV-TD solvers. Finally for microwave heating purposes, a comparison of analytical and numerical results for standard case studies in rectangular waveguides allows the accuracy of the developed methods to be assessed.

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Teachers' failure to utilise MBL activities more widely may be due to not recognising their capacity to transform the nature of laboratory activities to be more consistent with contemporary constructivist theories of learning. This research aimed to increase understanding of how MBL activities specifically designed to be consistent with a constructivist theory of learning support or constrain student construction of understanding. The first author conducted the research with his Year 11 physics class of 29 students. Dyads completed nine tasks relating to kinematics using a Predict-Observe-Explain format. Data sources included video and audio recordings of students and teacher during four 70-minute sessions, students' display graphs and written notes, semi-structured student interviews, and the teacher's journal. The study identifies the actors and describes the patterns of interactions in the MBL. Analysis of students' discourse and actions identified many instances where students' initial understanding of kinematics were mediated in multiple ways. Students invented numerous techniques for manipulating data in the service of their emerging understanding. The findings are presented as eight assertions. Recommendations are made for developing pedagogical strategies incorporating MBL activities which will likely catalyse student construction of understanding.

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The ability of agents and services to automatically locate and interact with unknown partners is a goal for both the semantic web and web services. This, \serendipitous interoperability", is hindered by the lack of an explicit means of describing what services (or agents) are able to do, that is, their capabilities. At present, informal descriptions of what services can do are found in \documentation" elements; or they are somehow encoded in operation names and signatures. We show, by ref- erence to existing service examples, how ambiguous and imprecise capa- bility descriptions hamper the attainment of automated interoperability goals in the open, global web environment. In this paper we propose a structured, machine readable description of capabilities, which may help to increase the recall and precision of service discovery mechanisms. Our capability description draws on previous work in capability and process modeling and allows the incorporation of external classi¯cation schemes. The capability description is presented as a conceptual meta model. The model supports conceptual queries and can be used as an extension to the DAML-S Service Pro¯le.

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This paper reports on the design, implementation and outcomes of a mentoring program involving 18 employees in the IT Division of WorkCover Queensland. The paper provides some background information to the development of the program and the design and implementation phases including recruitment and matching of participants, orientation and training, and the mentoring process including transition and/or termination. The paper also outlines the quantitative and qualitative evaluation processes that occurred and the outcomes of that evaluation. Results indicated a wealth of positive individual, mentoring, and organisational outcomes. The organisation and semi-structured processes provided in the program are considered as major contributing factors to the successful outcomes of the program. These outcomes are likely to have long-term benefits for the individuals involved, the IT Division, and the broader organisation

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This paper presents a novel program annotation mechanism which enables students to obtain feedback from tutors on their programs in a far simpler and more efficient way than is possible with, for example, email. A common scenario with beginning students is to email tutors with copies of their malfunctioning programs. Unfortunately the emailed program often bears little resemblance to the program the student has been trying to make work; often it is incomplete, a different version and corrupted. We propose an annotation mechanism enabling students to simply and easily annotate their programs with comments asking for help. Similarly our mechanism enables tutors to view students’ programs and to reply to their comments in a simple and structured fashion. This means students can get frequent and timely feedback on their programs; tutors can provide such feedback efficiently, and hence students’ learning is greatly improved.

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As process management projects have increased in size due to globalised and company-wide initiatives, a corresponding growth in the size of process modeling projects can be observed. Despite advances in languages, tools and methodologies, several aspects of these projects have been largely ignored by the academic community. This paper makes a first contribution to a potential research agenda in this field by defining the characteristics of large-scale process modeling projects and proposing a framework of related issues. These issues are derived from a semi -structured interview and six focus groups conducted in Australia, Germany and the USA with enterprise and modeling software vendors and customers. The focus groups confirm the existence of unresolved problems in business process modeling projects. The outcomes provide a research agenda which directs researchers into further studies in global process management, process model decomposition and the overall governance of process modeling projects. It is expected that this research agenda will provide guidance to researchers and practitioners by focusing on areas of high theoretical and practical relevance.

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A computational framework for enhancing design in an evolutionary approach with a dynamic hierarchical structure is presented in this paper. This framework can be used as an evolutionary kernel for building computer-supported design systems. It provides computational components for generating, adapting and exploring alternative design solutions at multiple levels of abstraction with hierarchically structured design representations. In this paper, preliminary experimental results of using this framework in several design applications are presented.

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This paper describes a design game that we called 'Meaning in Movement'. The purpose was to explore notions of professional dental practice with dental practioners in terms of gestures, actions and movements. The game represents a first step towards involving gestures, actions and movements in a design dialog with practioners for the purpose of designing future interactive systems which are more appropriate to the type of skilful actions and richly structured environments of dentists and dental assistants.

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This paper explores the influence of emotional loyalty on music purchase behaviour. Specifically, it examines whether emotional attachment to an artist's music influences loyalty to that artist, and how emotional loyalty influences a consumer's decision to purchase music. Data collection involved fifteen semi-structured interviews with young (18-30) subjects recruited through non-probability convenience sampling. Findings show that consumers who are emotionally loyal to an artistes) are more inclined to purchase the music rather than download free of charge.