726 resultados para Dispersion Model
Resumo:
Background: The current model of care for breast cancer is focused on disease treatment followed by ongoing recurrence surveillance. This approach lacks attention to the patients’ physical and functional well-being. Breast cancer treatment sequelae can lead to physical impairments and functional limitations. Common impairments include pain, fatigue, upper extremity dysfunction, lymphedema, weakness, joint arthralgia, neuropathy, weight gain, cardiovascular effects, and osteoporosis. Evidence supports prospective surveillance for early identification and treatment as a means to prevent or mitigate many of these concerns. Purpose: This paper proposes a prospective surveillance model for physical rehabilitation and exercise that can be integrated with disease treatment to create a more comprehensive approach to survivorship health care. The goals of the model are to promote surveillance for common physical impairments and functional limitations associated with breast cancer treatment, to provide education to facilitate early identification of impairments, to introduce rehabilitation and exercise intervention when physical impairments are identified and to promote and support physical activity and exercise behaviors through the trajectory of disease treatment and survivorship. Methods: The model is the result of a multi-disciplinary meeting of research and clinical experts in breast cancer survivorship and representatives of relevant professional and advocacy organizations. Outcomes: The proposed model identifies time points during breast cancer care for assessment of and education about physical impairments. Ultimately, implementation of the model may influence incidence and severity of breast cancer treatment related physical impairments. As such, the model seeks to optimize function during and following treatment and positively influence a growing survivorship community.
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In this paper, we examine the use of a Kalman filter to aid in the mission planning process for autonomous gliders. Given a set of waypoints defining the planned mission and a prediction of the ocean currents from a regional ocean model, we present an approach to determine the best, constant, time interval at which the glider should surface to maintain a prescribed tracking error, and minimizing time on the ocean surface. We assume basic parameters for the execution of a given mission, and provide the results of the Kalman filter mission planning approach. These results are compared with previous executions of the given mission scenario.
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A simple phenomenological model for the relationship between structure and composition of the high Tc cuprates is presented. The model is based on two simple crystal chemistry principles: unit cell doping and charge balance within unit cells. These principles are inspired by key experimental observations of how the materials accommodate large deviations from stoichiometry. Consistent explanations for significant HTSC properties can be explained without any additional assumptions while retaining valuable insight for geometric interpretation. Combining these two chemical principles with a review of Crystal Field Theory (CFT) or Ligand Field Theory (LFT), it becomes clear that the two oxidation states in the conduction planes (typically d8 and d9) belong to the most strongly divergent d-levels as a function of deformation from regular octahedral coordination. This observation offers a link to a range of coupling effects relating vibrations and spin waves through application of Hund’s rules. An indication of this model’s capacity to predict physical properties for HTSC is provided and will be elaborated in subsequent publications. Simple criteria for the relationship between structure and composition in HTSC systems may guide chemical syntheses within new material systems.
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Many academic researchers have conducted studies on the selection of design-build (DB) delivery method; however, there are few studies on the selection of DB operational variations, which poses challenges to many clients. The selection of DB operational variation is a multi-criteria decision making process that requires clients to objectively evaluate the performance of each DB operational variation with reference to the selection criteria. This evaluation process is often characterized by subjectivity and uncertainty. In order to resolve this deficiency, the current investigation aimed to establish a fuzzy multicriteria decision-making (FMCDM) model for selecting the most suitable DB operational variation. A three-round Delphi questionnaire survey was conducted to identify the selection criteria and their relative importance. A fuzzy set theory approach, namely the modified horizontal approach with the bisector error method, was applied to establish the fuzzy membership functions, which enables clients to perform quantitative calculations on the performance of each DB operational variation. The FMCDM was developed using the weighted mean method to aggregate the overall performance of DB operational variations with regard to the selection criteria. The proposed FMCDM model enables clients to perform quantitative calculations in a fuzzy decision-making environment and provides a useful tool to cope with different project attributes.
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The paper investigates train scheduling problems when prioritised trains and non-prioritised trains are simultaneously traversed in a single-line rail network. In this case, no-wait conditions arise because the prioritised trains such as express passenger trains should traverse continuously without any interruption. In comparison, non-prioritised trains such as freight trains are allowed to enter the next section immediately if possible or to remain in a section until the next section on the routing becomes available, which is thought of as a relaxation of no-wait conditions. With thorough analysis of the structural properties of the No-Wait Blocking Parallel-Machine Job-Shop-Scheduling (NWBPMJSS) problem that is originated in this research, an innovative generic constructive algorithm (called NWBPMJSS_Liu-Kozan) is proposed to construct the feasible train timetable in terms of a given order of trains. In particular, the proposed NWBPMJSS_Liu-Kozan constructive algorithm comprises several recursively-used sub-algorithms (i.e. Best-Starting-Time-Determination Procedure, Blocking-Time-Determination Procedure, Conflict-Checking Procedure, Conflict-Eliminating Procedure, Tune-up Procedure and Fine-tune Procedure) to guarantee feasibility by satisfying the blocking, no-wait, deadlock-free and conflict-free constraints. A two-stage hybrid heuristic algorithm (NWBPMJSS_Liu-Kozan-BIH) is developed by combining the NWBPMJSS_Liu-Kozan constructive algorithm and the Best-Insertion-Heuristic (BIH) algorithm to find the preferable train schedule in an efficient and economical way. Extensive computational experiments show that the proposed methodology is promising because it can be applied as a standard and fundamental toolbox for identifying, analysing, modelling and solving real-world scheduling problems.
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There has been much written about the Internet’s potential to enhance international market growth opportunities for SME’s. However, the literature is vague as to how Internet usage and the application of Internet marketing also known as Internet marketing intensity has an impact on firm international market growth. This paper examines the level and role of the Internet in the international operations of a sample of 218 Australian SMEs with international customers. This study shows evidence of a statistical relationship between Internet usage and Internet marketing intensity, which in turn leads to international market growth, in terms of increased sales from new customers in new countries, new customers in existing countries and from existing customers.
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Enterprise architecture (EA) management has be-come an intensively discussed approach to manage enterprise transformations. While there is a strong interest in EA frameworks and EA modeling, a lack of knowledge remains about the theoretical foundation of EA benefits. In this paper, we identify EA success factors and EA benefits through a literature review, and integrate these findings with the DeLone & McLean IS success model to propose a theoretical model explaining the realization of EA benefits. In addition, we con-ducted semi-structured interviews with EA experts for a preliminary validation and further exploration of the model. We see this model as a first step to gain insights in and start a discussion on the theory of EA benefit realization. In future research, we plan to empirically validate the proposed model.
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Discovering factors that help or impede business model change is an important quest, both for researchers and practitioners. In this study we present preliminary findings based on the CAUSEE survey of young and nascent firms in Australia. In particular, we seek to determine an association between business model adaptation and external orientation among young and nascent firms within the random sample and amongst an oversample of high potential firms. The concept of external orientation is made operational by asking respondents whether, and to what extent, they rely on certain sources of advice and information. We find that high potential firms are more likely to have made at least some change to their business model, that greater use of external sources of advice is generally significantly associated with business model adaptation, but also that there appear to be different patterns of behaviour between the random sample and the over sample.
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This study examined the effect that temporal order within the entrepreneurial discovery exploitation process has on the outcomes of venture creation. Consistent with sequential theories of discovery-exploitation, the general flow of venture creation was found to be directed from discovery toward exploitation in a random sample of nascent ventures. However, venture creation attempts which specifically follow this sequence derive poor outcomes. Moreover, simultaneous discovery-exploitation was the most prevalent temporal order observed, and venture attempts that proceed in this manner more likely become operational. These findings suggest that venture creation is a multi-scale phenomenon that is at once directional in time, and simultaneously driven by symbiotically coupled discovery and exploitation.
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Discrete Markov random field models provide a natural framework for representing images or spatial datasets. They model the spatial association present while providing a convenient Markovian dependency structure and strong edge-preservation properties. However, parameter estimation for discrete Markov random field models is difficult due to the complex form of the associated normalizing constant for the likelihood function. For large lattices, the reduced dependence approximation to the normalizing constant is based on the concept of performing computationally efficient and feasible forward recursions on smaller sublattices which are then suitably combined to estimate the constant for the whole lattice. We present an efficient computational extension of the forward recursion approach for the autologistic model to lattices that have an irregularly shaped boundary and which may contain regions with no data; these lattices are typical in applications. Consequently, we also extend the reduced dependence approximation to these scenarios enabling us to implement a practical and efficient non-simulation based approach for spatial data analysis within the variational Bayesian framework. The methodology is illustrated through application to simulated data and example images. The supplemental materials include our C++ source code for computing the approximate normalizing constant and simulation studies.
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Arguably, the most common patient seen in contact lens practice in our communities is the young adult white myope. The incidence of eye disease in this group of patients is very low, particularly if the genetically determined problems are excluded. However, there is one condition that should always be anticipated and searched for, especially in males. In fact, it affects 2-4% of these individuals and is known as pigment dispersion syndrome. This is important because 25-50% of these patients will get secondary or pigmentary glaucoma because of the pigment dispersion. It can be inherited as an autosomal dominant trait and has been mapped to chromosome 7. It is usually bilateral and is rarely encountered in patients of darker skin such as Asians and African-Americans.
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Nonhealing wounds are a major burden for health care systems worldwide. In addition, a patient who suffers from this type of wound usually has a reduced quality of life. While the wound healing process is undoubtedly complex, in this paper we develop a deterministic mathematical model, formulated as a system of partial differential equations, that focusses on an important aspect of successful healing: oxygen supply to the wound bed by a combination of diffusion from the surrounding unwounded tissue and delivery from newly formed blood vessels. While the model equations can be solved numerically, the emphasis here is on the use of asymptotic methods to establish conditions under which new blood vessel growth can be initiated and wound-bed angiogenesis can progress. These conditions are given in terms of key model parameters including the rate of oxygen supply and its rate of consumption in the wound. We use our model to discuss the clinical use of treatments such as hyperbaric oxygen therapy, wound bed debridement, and revascularisation therapy that have the potential to initiate healing in chronic, stalled wounds.
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Aims Multi-method study including two parts: Study One: three sets of observations in two regional areas of Queensland Study Two: two sets of parent intercept interviews conducted in Toowoomba, Queensland. The aim of Study Two is to determine parents’ views, opinions and knowledge of child restraint practices and the Queensland legislative amendment.
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Background: Trauma resulting from traffic crashes poses a significant problem in highly motorised countries. Over a million people worldwide are killed annually and 50 million are critically injured as a result of traffic collisions. In Australia, road crashes cost an average of $17 billion annually in personal loss of income and quality of life, organisational losses in productivity and workplace quality, and health care costs. Driver aggression has been identified as a key factor contributing to crashes, and many motorists report experiencing mild forms of aggression (e.g., rude gestures, horn honking). However despite this concern, driver aggression has received relatively little attention in empirical research, and existing research has been hampered by a number of methodological and conceptual shortcomings. Specifically, there has been substantial disagreement regarding what constitutes aggressive driving and a failure to examine both the situational factors and the emotional and cognitive processes underlying driver aggression. To enhance current understanding of aggressive driving, a model of driver aggression that highlights the cognitive and emotional processes at play in aggressive driving incidents is proposed. Aims: The research aims to improve current understanding of the complex nature of driver aggression by testing and refining a model of aggressive driving that incorporates the person-related and situational factors and the cognitive and emotional appraisal processes fundamental to driver aggression. In doing so, the research will assist to provide a clear definition of what constitutes aggressive driving, assist to identify on-road incidents that trigger driver aggression, and identify the emotional and cognitive appraisal processes that underlie driver aggression. Methods: The research involves three studies. Firstly, to contextualise the model and explore the cognitive and emotional aspects of driver aggression, a diary-based study using self-reports of aggressive driving events will be conducted with a general population of drivers. This data will be supplemented by in-depth follow-up interviews with a sub-sample of participants. Secondly, to test generalisability of the model, a large sample of drivers will be asked to respond to video-based scenarios depicting driving contexts derived from incidents identified in Study 1 as inciting aggression. Finally, to further operationalise and test the model an advanced driving simulator will be used with sample of drivers. These drivers will be exposed to various driving scenarios that would be expected to trigger negative emotional responses. Results: Work on the project has commenced and progress on the first study will be reported.
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The improvement and optimization of business processes is one of the top priorities in an organization. Although process analysis methods are mature today, business analysts and stakeholders are still hampered by communication issues. That is, analysts cannot effectively obtain accurate business requirements from stakeholders, and stakeholders are often confused about analytic results offered by analysts. We argue that using a virtual world to model a business process can benefit communication activities. We believe that virtual worlds can be used as an efficient model-view approach, increasing the cognition of business requirements and analytic results, as well as the possibility of business plan validation. A healthcare case study is provided as an approach instance, illustrating how intuitive such an approach can be. As an exploration paper, we believe that this promising research can encourage people to investigate more research topics in the interdisciplinary area of information system, visualization and multi-user virtual worlds.