992 resultados para UNIFYING MODEL
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Documento de trabajo
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There is increasing evidence that parenting and feeding interact to influence children’s eating behaviour and weight status. Interpretation of existing research is complicated by the lack of consensus in the conceptualisation and measurement of both ‘parenting’ and ‘feeding’, particularly the distinction between ‘styles’, ‘dimensions’ and ‘practices’. In addition, the lack of validated tools to concurrently assess feeding practices in infancy limits the capacity to examine the relationships between parenting and feeding in infancy and their short- and long-term influence on weight status. In this paper we provide an overview of the constructs examined in this emerging area of research, highlight the conceptual, definitional and measurement challenges and propose a unifying model to aid design and the interpretation of intervention studies. Progress on these methodological issues will contribute to the robust evidence required to justify investment in interventions that focus on parenting and feeding in the context of child obesity prevention.
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This thesis presents theories, analyses, and algorithms for detecting and estimating parameters of geospatial events with today's large, noisy sensor networks. A geospatial event is initiated by a significant change in the state of points in a region in a 3-D space over an interval of time. After the event is initiated it may change the state of points over larger regions and longer periods of time. Networked sensing is a typical approach for geospatial event detection. In contrast to traditional sensor networks comprised of a small number of high quality (and expensive) sensors, trends in personal computing devices and consumer electronics have made it possible to build large, dense networks at a low cost. The changes in sensor capability, network composition, and system constraints call for new models and algorithms suited to the opportunities and challenges of the new generation of sensor networks. This thesis offers a single unifying model and a Bayesian framework for analyzing different types of geospatial events in such noisy sensor networks. It presents algorithms and theories for estimating the speed and accuracy of detecting geospatial events as a function of parameters from both the underlying geospatial system and the sensor network. Furthermore, the thesis addresses network scalability issues by presenting rigorous scalable algorithms for data aggregation for detection. These studies provide insights to the design of networked sensing systems for detecting geospatial events. In addition to providing an overarching framework, this thesis presents theories and experimental results for two very different geospatial problems: detecting earthquakes and hazardous radiation. The general framework is applied to these specific problems, and predictions based on the theories are validated against measurements of systems in the laboratory and in the field.
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Background: Career Choice in Medicine is an important and problematic topic. Medical education has been framed as professional identity development, yet career choice has not been viewed as a matter of identity. My primary aim was to offer new insights by exploring career choice using Figured Worlds theory, a socio-cultural theory of identity. Graduate retention is a challenge for many countries, including Ireland. My secondary aim was to address a gap in the data on postgraduate trainees in Ireland and to use the Irish case to illustrate points transferable to other contexts. Methodology & Methods: This was a predominantly qualitative Mixed Methods programme of research. My qualitative studies were oriented towards social constructionism. I collated existing data from the Royal College of Physicians of Ireland (RCPI) and HSE-MET to describe trainees and their career paths. I surveyed Basic Specialist Training trainees (n=333) about their career plans. I surveyed new trainees (n=527) about their expectations of training and all RCPI trainees about their experiences of training (n=1246). I conducted semi-structured interviews with 18 medical students and doctors. A subgroup (n=6) provided longitudinal data. Figured Worlds theory and Gee’s discourse tools were used for analysis. Results: I have used the case of medical training and career choice in Ireland to explain how social, political and cultural context, and day to day experiences in the cultural world of medicine, shaped doctors’ career choices. My qualitative findings described a unifying model of career choice, consisting of priming, exposure, positioning and open-endedness, which can guide the design of interventions to shape and support career choice. Conclusion: My original contribution has been to demonstrate the fruitfulness of framing career choice in terms of identity development. This represents a turn in the conversation about career choice, which brings new starting points and moves the dialogue forward.
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Background: To optimize patient functioning, rehabilitation professionals often rely on measurements of functioning as well as on classifications. Although the International Classification of Diseases (ICD) and the International Classification of Functioning, Disability and Health (ICF) are used, their joint use has yet to become an established practice. To encourage their joint use in daily practice, the World Health Organization (WHO) has invited all rehabilitation practitioners worldwide to support the ICD-11 revision process by identifying the ICF categories that correspond to specific rehabilitation-relevant health conditions. The first step in completing this task, generating the list of these health conditions, was taken at a February 2012 workshop in Sao Paulo, Brazil. Objectives: The objectives of this paper are to present the results of the Sao Paulo workshop, and to invite practitioners to participate in the ICD-ICF joint use initiative. Discussion: Alternating plenary and small working group sessions were held and 103 rehabilitation-relevant health conditions were identified. With this list available, WHO together with the International Society of Physical and Rehabilitation Medicine (ISPRM), is reaching out to clinicians of all rehabilitation disciplines to take on the challenge of identifying the ICF categories for at least one of the health conditions listed.
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A distinct feature of several recent models of contrast masking is that detecting mechanisms are divisively inhibited by a broadly tuned ‘gain pool’ of narrow-band spatial pattern mechanisms. The contrast gain control provided by this ‘cross-channel’ architecture achieves contrast normalisation of early pattern mechanisms, which is important for keeping them within the non-saturating part of their biological operating characteristic. These models superseded earlier ‘within-channel’ models, which had supposed that masking arose from direct stimulation of the detecting mechanism by the mask. To reveal the extent of masking, I measured the levels produced with large ranges of pattern spatial relationships that have not been explored before. Substantial interactions between channels tuned to different orientations and spatial frequencies were found. Differences in the masking levels produced with single and multiple component mask patterns provided insights into the summation rules within the gain pool. A widely used cross-channel masking model was tested on these data and was found to perform poorly. The model was developed and a version in which linear summation was allowed between all components within the gain pool but with the exception of the self-suppressing route typically provided the best account of the data. Subsequently, an adaptation paradigm was used to probe the processes underlying pooled responses in masking. This delivered less insight into the pooling than the other studies and areas were identified that require investigation for a new unifying model of masking and adaptation. In further experiments, levels of cross-channel masking were found to be greatly influenced by the spatio-temporal tuning of the channels involved. Old masking experiments and ideas relying on within-channel models were re-elevated in terms of contemporary cross-channel models (e.g. estimations of channel bandwidths from orientation masking functions) and this led to different conclusions than those originally arrived at. The investigation of effects with spatio-temporally superimposed patterns is focussed upon throughout this work, though it is shown how these enquiries might be extended to investigate effects across spatial and temporal position.
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To facilitate the implementation of workflows, enterprise and workflow system vendors typically provide workflow templates for their software. Each of these templates depicts a variant of how the software supports a certain business process, allowing the user to save the effort of creating models and links to system components from scratch by selecting and activating the appropriate template. A combination of the strengths from different templates is however only achievable by manually adapting the templates which is cumbersome. We therefore suggest in this paper to combine different workflow templates into a single configurable workflow template. Using the workflow modeling language of SAP’s WebFlow engine, we show how such a configurable workflow modeling language can be created by identifying the configurable elements in the original language. Requirements imposed on configurations inhibit invalid configurations. Based on a default configuration such configurable templates can be used as easy as the traditional templates. The suggested approach is also applicable to other workflow modeling languages
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We establish the importance of modified Einstein's gravity (MG) in white dwarfs (WDs) for the first time in the literature. We show that MG leads to significantly sub- and super-Chandrasekhar limiting mass WDs, depending on a single model parameter. However, conventional WDs on approaching Chandrasekhar's limit are expected to trigger Type Ia supernovae (SNeIa), a key to unravel the evolutionary history of the universe. Nevertheless, observations of several peculiar, under-and over-luminous SNeIa argue for the limiting mass widely different from Chandrasekhar's limit. Explosions of MG induced sub-and super-Chandrasekhar limiting mass WDs explain under-and over-luminous SNeIa respectively, thus unifying these two apparently disjoint sub-classes. Our discovery questions both the global validity of Einstein's gravity and the uniqueness of Chandrasekhar's limit.
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We present a model for early vision tasks such as denoising, super-resolution, deblurring, and demosaicing. The model provides a resolution-independent representation of discrete images which admits a truly rotationally invariant prior. The model generalizes several existing approaches: variational methods, finite element methods, and discrete random fields. The primary contribution is a novel energy functional which has not previously been written down, which combines the discrete measurements from pixels with a continuous-domain world viewed through continous-domain point-spread functions. The value of the functional is that simple priors (such as total variation and generalizations) on the continous-domain world become realistic priors on the sampled images. We show that despite its apparent complexity, optimization of this model depends on just a few computational primitives, which although tedious to derive, can now be reused in many domains. We define a set of optimization algorithms which greatly overcome the apparent complexity of this model, and make possible its practical application. New experimental results include infinite-resolution upsampling, and a method for obtaining subpixel superpixels. © 2012 IEEE.
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Eco-innovations, eco-efficiency and corporate social responsibility practices define much of the current industrial sustainability agenda. While important, they are insufficient in themselves to deliver the holistic changes necessary to achieve long-term social and environmental sustainability. How can we encourage corporate innovation that significantly changes the way companies operate to ensure greater sustainability? Sustainable business models (SBM) incorporate a triple bottom line approach and consider a wide range of stakeholder interests, including environment and society. They are important in driving and implementing corporate innovation for sustainability, can help embed sustainability into business purpose and processes, and serve as a key driver of competitive advantage. Many innovative approaches may contribute to delivering sustainability through business models, but have not been collated under a unifying theme of business model innovation. The literature and business practice review has identified a wide range of examples of mechanisms and solutions that can contribute to business model innovation for sustainability. The examples were collated and analysed to identify defining patterns and attributes that might facilitate categorisation. Sustainable business model archetypes are introduced to describe groupings of mechanisms and solutions that may contribute to building up the business model for sustainability. The aim of these archetypes is to develop a common language that can be used to accelerate the development of sustainable business models in research and practice. The archetypes are: Maximise material and energy efficiency; Create value from 'waste'; Substitute with renewables and natural processes; Deliver functionality rather than ownership; Adopt a stewardship role; Encourage sufficiency; Re-purpose the business for society/environment; and Develop scale-up solutions. © 2014 The Authors. Published by Elsevier Ltd. All rights reserved.
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What are the personality differences between individuals who commit crime and those who refrain from crime? The HEXACO model of personality combines facets of honesty and humility with those of emotionality, extraversion, conscientiousness, agreeableness, and openness to experience within a unifying framework of personality. We applied the HEXACO model to examine differences in personality between offenders and nonoffenders. Criminal offenders differed from nonoffenders on five of the six dimensions of personality proposed by the HEXACO model. Compared to nonoffenders, offenders exhibited stronger tendencies toward greed and unfairness, but were also more anxious and fearful. Conversely, the offenders scored lower than nonoffenders on a number of facets of sociability, liveliness, and social boldness. The present findings indicate that offenders may in part be characterized by increased negative emotions but decreased sociability and liveliness. The HEXACO model of personality provides a valuable tool for studying this unique and important population. © 2012 Copyright Taylor and Francis Group, LLC.
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Arabidopsis is a model plant used to study disease resistance; Solanum tuberosum or potato is a crop species. Both plants possess inducible defense mechanisms that are deployed upon recognition of pathogen invasion. Transcriptional reprogramming is crucial to the activation of defense responses. The Pathogenesis-Related (PR) genes are activated in these defense programs. Expression of Arabidopsis PR-l and potato PR-10a serve as markers for the deployment of defense responses in these plants. PR-l expression indicates induction of systemic acquired resistance (SAR). Activation of SAR requires accumulation of salicylic acid (SA), in addition to the interaction of the non-expressor of pathogenesis-related genes I (NPRI), with the TGA transcription factors. The PR-10a is activated in response to pathogen invasion, wounding and elicitor treatment. PR-10a induction requires recruitment of the Whirly I (Whyl) activator to the promoter. This locus is also negatively regulated by the silencer element binding factor (SEBF). We established that both the PR-l and PR-10a are occupied by repressors under non-inducing conditions. TGA2 was found to be a constitutive resident and repressor of PR-l, which mediates repression by forming an oligomeric complex on the promoter. The DNA-binding activity of this oligomer required the TGA2 N-terminus (NT). Under resting conditions we determined that the PR-10a is bound by a repressosome containing SEBF and curiously the activator Pto interacting protein 4 (Pti4). In the context of this repressosome, SEBF is responsible for PR-10a binding, yet rWe also showed that PR-l and PR-10a are activated by different means. In PR-l activation the NPRI NT domain alleviates TGA2-mediated repression by interacting with the TGA2 NT. TGA2 remains at the PR-l but adopts a dimeric conformation and forms an enhanceosome with NPRl. In contrast, the PR-10a is activated by evicting the repressosome and recruiting Why! to the promoter. These results advance our understanding of the mechanisms regulating PR-l and PR-10a expression under resting and inducing conditions. This study also revealed that the means of regulation for related genes can differ greatly between model and crop s
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OBJECTIVES: This contribution provides a unifying concept for meta-analysis integrating the handling of unobserved heterogeneity, study covariates, publication bias and study quality. It is important to consider these issues simultaneously to avoid the occurrence of artifacts, and a method for doing so is suggested here. METHODS: The approach is based upon the meta-likelihood in combination with a general linear nonparametric mixed model, which lays the ground for all inferential conclusions suggested here. RESULTS: The concept is illustrated at hand of a meta-analysis investigating the relationship of hormone replacement therapy and breast cancer. The phenomenon of interest has been investigated in many studies for a considerable time and different results were reported. In 1992 a meta-analysis by Sillero-Arenas et al. concluded a small, but significant overall effect of 1.06 on the relative risk scale. Using the meta-likelihood approach it is demonstrated here that this meta-analysis is due to considerable unobserved heterogeneity. Furthermore, it is shown that new methods are available to model this heterogeneity successfully. It is argued further to include available study covariates to explain this heterogeneity in the meta-analysis at hand. CONCLUSIONS: The topic of HRT and breast cancer has again very recently become an issue of public debate, when results of a large trial investigating the health effects of hormone replacement therapy were published indicating an increased risk for breast cancer (risk ratio of 1.26). Using an adequate regression model in the previously published meta-analysis an adjusted estimate of effect of 1.14 can be given which is considerably higher than the one published in the meta-analysis of Sillero-Arenas et al. In summary, it is hoped that the method suggested here contributes further to a good meta-analytic practice in public health and clinical disciplines.
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We develop and empirically test a continuous time equilibrium model for the pricing of oil futures. The model provides a link between no-arbitrage models and expectation oriented models. It highlights the role of inventories for the identification of different pricing regimes. In an empirical study the hedging performance of our model is compared with five other one- and two-factor pricing models. The hedging problem considered is related to Metallgesellschaft´s strategy to hedge long-term forward commitments with short-term futures. The results show that the downside risk distribution of our inventory based model stochastically dominates those of the other models.