107 resultados para individual circumstances.
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ESA’s first multi-satellite mission Cluster is unique in its concept of 4 satellites orbiting in controlled formations. This will give an unprecedented opportunity to study structure and dynamics of the magnetosphere. In this paper we discuss ways in which ground-based remote-sensing observations of the ionosphere can be used to support the multipoint in-situ satellite measurements. There are a very large number of potentially useful configurations between the satellites and any one ground-based observatory; however, the number of ideal occurrences for any one configuration is low. Many of the ground-based instruments cannot operate continuously and Cluster will take data only for a part of each orbit, depending on how much high-resolution (‘burst-mode’) data are acquired. In addition, there are a great many instrument modes and the formation, size and shape of the cluster of the four satellites to consider. These circumstances create a clear and pressing need for careful planning to ensure that the scientific return from Cluster is maximised by additional coordinated ground-based observations. For this reason, ESA established a working group to coordinate the observations on the ground with Cluster. We will give a number of examples how the combined spacecraft and ground-based observations can address outstanding questions in magnetospheric physics. An online computer tool has been prepared to allow for the planning of conjunctions and advantageous constellations between the Cluster spacecraft and individual or combined ground-based systems. During the mission a ground-based database containing index and summary data will help to identify interesting datasets and allow to select intervals for coordinated studies. We illustrate the philosophy of our approach, using a few important examples of the many possible configurations between the satellite and the ground-based instruments.
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Speaking of the public response to the deaths of children at the Bristol Royal Infirmary before 2001, the BMJ commented that the NHS would be 'all changed, changed utterly'. Today, two inquiries into the Mid Staffordshire Foundation Trust suggest nothing changed at all. Many patients died as a result of their care and the stories of indifference and neglect there are harrowing. Yet Bristol and Mid Staffordshire are not isolated reports. In 2011, the Health Services Ombudsman reported on the care of elderly and frail patients in the NHS and found a failure to recognise their humanity and individuality and to respond to them with sensitivity, compassion and professionalism. Likewise, the Care Quality Commission and Healthcare Commission received complaints from patients and relatives about the quality of nursing care. These included patients not being fed, patients left in soiled bedding, poor hygiene practices, and general disregard for privacy and dignity. Why is there such tolerance of poor clinical standards? We need a better understanding of the circumstances that can lead to these outcomes and how best to respond to them. We discuss the findings of these and other reports and consider whether attention should be devoted to managing individual behaviour, or focus on the systemic influences which predispose hospital staff to behave in this way. Lastly, we consider whether we should look further afield to cognitive psychology to better understand how clinicians and managers make decisions?
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BACKGROUND: Monitoring of fruit and vegetable (F&V) intake is fraught with difficulties. Available dietary assessment methods are associated with considerable error, and the use of biomarkers offers an attractive alternative. Few studies to date have examined the use of plasma biomarkers to monitor or predict the F&V intake of volunteers consuming a wide range of intakes from both habitual F&V and manipulated diets. OBJECTIVE: This study tested the hypothesis that an integrated biomarker calculated from a combination of plasma vitamin C, cholesterol-adjusted carotenoid concentration and Ferric Reducing Antioxidant Power (FRAP) had more power to predict F&V intake than each individual biomarker. METHODS: Data from a randomized controlled dietary intervention study [FLAVURS (Flavonoids University of Reading Study); n = 154] in which the test groups observed sequential increases of 2.3, 3.2, and 4.2 portions of F&Vs every 6 wk across an 18-wk period were used in this study. RESULTS: An integrated plasma biomarker was devised that included plasma vitamin C, total cholesterol-adjusted carotenoids, and FRAP values, which better correlated with F&V intake (r = 0.47, P < 0.001) than the individual biomarkers (r = 0.33, P < 0.01; r = 0.37, P < 0.001; and r = 0.14, respectively; P = 0.099). Inclusion of urinary potassium concentration did not significantly improve the correlation. The integrated plasma biomarker predicted F&V intake more accurately than did plasma total cholesterol-adjusted carotenoid concentration, with the difference being significant at visit 2 (P < 0.001) and with a tendency to be significant at visit 1 (P = 0.07). CONCLUSION: Either plasma total cholesterol-adjusted carotenoid concentration or the integrated biomarker could be used to distinguish between high- and moderate-F&V consumers. This trial was registered at www.controlled-trials.com as ISRCTN47748735.
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More and more households are purchasing electric vehicles (EVs), and this will continue as we move towards a low carbon future. There are various projections as to the rate of EV uptake, but all predict an increase over the next ten years. Charging these EVs will produce one of the biggest loads on the low voltage network. To manage the network, we must not only take into account the number of EVs taken up, but where on the network they are charging, and at what time. To simulate the impact on the network from high, medium and low EV uptake (as outlined by the UK government), we present an agent-based model. We initialise the model to assign an EV to a household based on either random distribution or social influences - that is, a neighbour of an EV owner is more likely to also purchase an EV. Additionally, we examine the effect of peak behaviour on the network when charging is at day-time, night-time, or a mix of both. The model is implemented on a neighbourhood in south-east England using smart meter data (half hourly electricity readings) and real life charging patterns from an EV trial. Our results indicate that social influence can increase the peak demand on a local level (street or feeder), meaning that medium EV uptake can create higher peak demand than currently expected.
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This article proposes an auction model where two firms compete for obtaining the license for a public project and an auctioneer acting as a public official representing the political power, decides the winner of the contest. Players as firms face a social dilemma in the sense that the higher is the bribe offered, the higher would be the willingness of a pure monetary maximizer public official to give her the license. However, it implies inducing a cost of reducing all players’ payoffs as far as our model includes an endogenous externality, which depends on bribe. All players’ payoffs decrease with the bribe (and increase with higher quality). We find that the presence of bribe aversion in either the officials’ or the firms’ utility function shifts equilibrium towards more pro-social behavior. When the quality and bribe-bid strategy space is discrete, multiple equilibria emerge including more pro-social bids than would be predicted under a continuous strategy space.
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The aim of this paper is to examine the differences and similarities in housing policies in the four Latin American countries of Argentina, Brazil, Chile and Colombia. The article uses the welfare regime approach, modified by a recognition of path dependence, to identify a number of phases that each country has passed through. However, attention is drawn to the substantial differences in the circumstances in each country and the extent and duration of the different phases. It is concluded that it can be beneficial to use the concept of a Latin American housing regime, but that this general picture has to be used with an understanding of the path dependence caused by the different context in the individual countries.
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This paper investigates the feasibility of using approximate Bayesian computation (ABC) to calibrate and evaluate complex individual-based models (IBMs). As ABC evolves, various versions are emerging, but here we only explore the most accessible version, rejection-ABC. Rejection-ABC involves running models a large number of times, with parameters drawn randomly from their prior distributions, and then retaining the simulations closest to the observations. Although well-established in some fields, whether ABC will work with ecological IBMs is still uncertain. Rejection-ABC was applied to an existing 14-parameter earthworm energy budget IBM for which the available data consist of body mass growth and cocoon production in four experiments. ABC was able to narrow the posterior distributions of seven parameters, estimating credible intervals for each. ABC’s accepted values produced slightly better fits than literature values do. The accuracy of the analysis was assessed using cross-validation and coverage, currently the best available tests. Of the seven unnarrowed parameters, ABC revealed that three were correlated with other parameters, while the remaining four were found to be not estimable given the data available. It is often desirable to compare models to see whether all component modules are necessary. Here we used ABC model selection to compare the full model with a simplified version which removed the earthworm’s movement and much of the energy budget. We are able to show that inclusion of the energy budget is necessary for a good fit to the data. We show how our methodology can inform future modelling cycles, and briefly discuss how more advanced versions of ABC may be applicable to IBMs. We conclude that ABC has the potential to represent uncertainty in model structure, parameters and predictions, and to embed the often complex process of optimizing an IBM’s structure and parameters within an established statistical framework, thereby making the process more transparent and objective.
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Even though Africa has constantly emphasized the need to reduce deficit financing through mobilization of more internal revenues, this has not been achieved. Perhaps encouraging voluntary tax compliance can improve internal revenue mobilization. This study explores the relationship between ethical orientation and tax compliance and finds that ethical persons are generally more tax compliant than unethical persons but are more influenced by considerations of tax rate and withholding positions compared to unethical persons. The findings of this study differ from Reckers et al. in a number of ways and contribute to the literature by providing a possible explanation of the cause(s) of tax non- compliance.
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Increasing prominence of the psychological ownership (PO) construct in management studies raises questions about how PO manifests at the level of the individual. In this article, we unpack the mechanism by which individuals use PO to express aspects of their identity and explore how PO manifestations can display congruence as well as incongruence between layers of self. As a conceptual foundation, we develop a dynamic model of individual identity that differentiates between four layers of self, namely, the “core self,” “learned self,” “lived self,” and “perceived self.” We then bring identity and PO literatures together to suggest a framework of PO manifestation and expression viewed through the lens of the four presented layers of self. In exploring our framework, we develop a number of propositions that lay the foundation for future empirical and conceptual work and discuss implications for theory and practice.
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Individual-based models (IBMs) can simulate the actions of individual animals as they interact with one another and the landscape in which they live. When used in spatially-explicit landscapes IBMs can show how populations change over time in response to management actions. For instance, IBMs are being used to design strategies of conservation and of the exploitation of fisheries, and for assessing the effects on populations of major construction projects and of novel agricultural chemicals. In such real world contexts, it becomes especially important to build IBMs in a principled fashion, and to approach calibration and evaluation systematically. We argue that insights from physiological and behavioural ecology offer a recipe for building realistic models, and that Approximate Bayesian Computation (ABC) is a promising technique for the calibration and evaluation of IBMs. IBMs are constructed primarily from knowledge about individuals. In ecological applications the relevant knowledge is found in physiological and behavioural ecology, and we approach these from an evolutionary perspective by taking into account how physiological and behavioural processes contribute to life histories, and how those life histories evolve. Evolutionary life history theory shows that, other things being equal, organisms should grow to sexual maturity as fast as possible, and then reproduce as fast as possible, while minimising per capita death rate. Physiological and behavioural ecology are largely built on these principles together with the laws of conservation of matter and energy. To complete construction of an IBM information is also needed on the effects of competitors, conspecifics and food scarcity; the maximum rates of ingestion, growth and reproduction, and life-history parameters. Using this knowledge about physiological and behavioural processes provides a principled way to build IBMs, but model parameters vary between species and are often difficult to measure. A common solution is to manually compare model outputs with observations from real landscapes and so to obtain parameters which produce acceptable fits of model to data. However, this procedure can be convoluted and lead to over-calibrated and thus inflexible models. Many formal statistical techniques are unsuitable for use with IBMs, but we argue that ABC offers a potential way forward. It can be used to calibrate and compare complex stochastic models and to assess the uncertainty in their predictions. We describe methods used to implement ABC in an accessible way and illustrate them with examples and discussion of recent studies. Although much progress has been made, theoretical issues remain, and some of these are outlined and discussed.
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The papers in this volume were presented at a Mellon-Sawyer Seminar held at the University of Oxford in 2009-2010, which sought to investigate side by side the two important movements of conversion that frame late antiquity: to Christianity at its start, and to Islam at the other end. Challenging the opposition between the two stereotypes of Islamic conversion as an intrinsically violent process, and Christian conversion as a fundamentally spiritual one, the papers seek to isolate the behaviours and circumstances that made conversion both such a common and such a contested phenomenon. The spread of Buddhism in Asia in broadly the same period serves as an external comparator that was not caught in the net of the Abrahamic religions. The volume is organised around several themes, reflecting the concerns of the initial project with the articulation between norm and practice, the role of authorities and institutions, and the social and individual fluidity on the ground. Debates, discussions, and the expression of norms and principles about conversion conversion are not rare in societies experiencing religious change, and the first section of the book examines some of the main issues brought up by surviving sources. This is followed by three sections examining different aspects of how those principles were - or were not - put into practice: how conversion was handled by the state, how it was continuously redefined by individual ambivalence and cultural fluidity, and how it was enshrined through different forms of institutionalization. Finally, a topographical coda examines the effects of religious change on the iconic holy city of Jerusalem.
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The present longitudinal study examines the interaction of learner variables (gender, motivation, self-efficacy and first language literacy) and their influence on second language learning outcomes. The study follows English learners of French from Year 5 in primary school (aged 9-10) to the first year in secondary school (Year 7 aged 11-12). Language outcomes were measured by two oral production tasks; a sentence repetition task and a photo description task both of which were administered at three time points. Longitudinal data on learner attitudes and motivation were collected via questionnaires. Teacher assessment data for general first language literacy attainment were also provided. The results show a great deal of variation in learner attitudes and outcomes and that there is a complex relationship between first language literacy, self-efficacy, gender and attainment. For example, in general, girls held more positive attitudes to boys and were more successful. However, the inclusion of first language ability, which explained 30-40% of variation, shows that gender differences in attitudes and outcomes are likely mediated by first language literacy and prior learning experience.
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Purpose - this paper focuses on reducing the margin for leadership error in meeting strategic aims by forming a more robust approach to developing a broader and more reliable set of leadership skills to provide a greater likelihood of strategic alignment between corporate and individual need, increasing both of their respective shelve lives.