910 resultados para KNOWLEDGE OF RESULTS


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Aim: To examine the causes of prescribing and monitoring errors in English general practices and provide recommendations for how they may be overcome. Design: Qualitative interview and focus group study with purposive sampling and thematic analysis informed by Reason’s accident causation model. Participants: General practice staff participated in a combination of semi-structured interviews (n=34) and six focus groups (n=46). Setting: Fifteen general practices across three primary care trusts in England. Results: We identified seven categories of high-level error-producing conditions: the prescriber, the patient, the team, the task, the working environment, the computer system, and the primary-secondary care interface. Each of these was further broken down to reveal various error-producing conditions. The prescriber’s therapeutic training, drug knowledge and experience, knowledge of the patient, perception of risk, and their physical and emotional health, were all identified as possible causes. The patient’s characteristics and the complexity of the individual clinical case were also found to have contributed to prescribing errors. The importance of feeling comfortable within the practice team was highlighted, as well as the safety of general practitioners (GPs) in signing prescriptions generated by nurses when they had not seen the patient for themselves. The working environment with its high workload, time pressures, and interruptions, and computer related issues associated with mis-selecting drugs from electronic pick-lists and overriding alerts, were all highlighted as possible causes of prescribing errors and often interconnected. Conclusion: This study has highlighted the complex underlying causes of prescribing and monitoring errors in general practices, several of which are amenable to intervention.

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The nonlinearity of high-power amplifiers (HPAs) has a crucial effect on the performance of multiple-input-multiple-output (MIMO) systems. In this paper, we investigate the performance of MIMO orthogonal space-time block coding (OSTBC) systems in the presence of nonlinear HPAs. Specifically, we propose a constellation-based compensation method for HPA nonlinearity in the case with knowledge of the HPA parameters at the transmitter and receiver, where the constellation and decision regions of the distorted transmitted signal are derived in advance. Furthermore, in the scenario without knowledge of the HPA parameters, a sequential Monte Carlo (SMC)-based compensation method for the HPA nonlinearity is proposed, which first estimates the channel-gain matrix by means of the SMC method and then uses the SMC-based algorithm to detect the desired signal. The performance of the MIMO-OSTBC system under study is evaluated in terms of average symbol error probability (SEP), total degradation (TD) and system capacity, in uncorrelated Nakagami-m fading channels. Numerical and simulation results are provided and show the effects on performance of several system parameters, such as the parameters of the HPA model, output back-off (OBO) of nonlinear HPA, numbers of transmit and receive antennas, modulation order of quadrature amplitude modulation (QAM), and number of SMC samples. In particular, it is shown that the constellation-based compensation method can efficiently mitigate the effect of HPA nonlinearity with low complexity and that the SMC-based detection scheme is efficient to compensate for HPA nonlinearity in the case without knowledge of the HPA parameters.

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In Britain, substantial cuts in police budgets alongside controversial handling of incidents such as politically sensitive enquiries, public disorder and relations with the media have recently triggered much debate about public knowledge and trust in the police. To date, however, little academic research has investigated how knowledge of police performance impacts citizens’ trust. We address this long-standing lacuna by exploring citizens’ trust before and after exposure to real performance data in the context of a British police force. The results reveal that being informed of performance data affects citizens’ trust significantly. Furthermore, direction and degree of change in trust are related to variations across the different elements of the reported performance criteria. Interestingly, the volatility of citizens’ trust is related to initial performance perceptions (such that citizens with low initial perceptions of police performance react more significantly to evidence of both good and bad performance than citizens with high initial perceptions), and citizens’ intentions to support the police do not always correlate with their cognitive and affective trust towards the police. In discussing our findings, we explore the implications of how being transparent with performance data can both hinder and be helpful in developing citizens’ trust towards a public organisation such as the police. From our study, we pose a number of ethical challenges that practitioners face when deciding what data to highlight, to whom, and for what purpose.

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Knowledge of the molecular biological changes underlying the process of embryogenesis is important for the improvement of somatic embryogenesis of coconut. Among the transcription factors that control the transition from vegetative to embryogenic growth, members of APETALA2/Ethylene-responsive element binding protein domain family play an important role in promoting embryo development. Significant insights into the role of AP2 genes have been obtained by the ectopic expression of AP2 sub family genes in transgenic Arabidopsis. A homolog of the AINTEGUMENTA-like gene that encodes the two AP2 domains and the linker region was identified in the coconut genome. Phylogenetic analysis showed that this gene, CnANT, encodes a protein that branched with BABY BOOM/PLETHORA clade in the AINTEGUMENTA-like major clade and was similar to the oil palm EgAP2-1 protein. According to real time RT-PCR results, higher expression of CnANT was observed in more mature zygotic embryos. Also, high CnANT expression was recorded in embryogenic callus compared to other stages of somatic embryogenesis. We examined the effect of ectopic CnANT expression on the development and regenerative capacity of transgenic Arabidopsis. Overexpression of CnANT in Arabidopsis induced hormone free regeneration of explants. Furthermore, ectopic expression of CnANT enhanced regeneration in vitro and suggested a role for this gene in cell proliferation during in vitro culture.

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Genes play an important role in the development of diabetes mellitus. Putative susceptibility genes could be the key to the development of diabetes. Type 1 diabetes mellitus is one of the most common chronic diseases of childhood. A combination of genetic and environmental factors is most likely the cause of Type 1 diabetes. The pathogenetic sequence leading to the selective autoimmune destruction of islet beta-cells and development of Type 1 diabetes involves genetic factors, environmental factors, immune regulation and chemical mediators. Unlike Type 1 diabetes mellitus, Type 2 diabetes is often considered a polygenic disorder with multiple genes located on different chromosomes being associated with this condition. This is further complicated by numerous environmental factors which also contribute to the clinical manifestation of the disorder in genetically predisposed persons. Only a minority of cases of type 2 diabetes are caused by single gene defects such as maturity onset diabetes of the young (MODY), syndrome of insulin resistance (insulin receptor defect) and maternally inherited diabetes and deafness (mitochondrial gene defect). Although Type 2 diabetes mellitus appears in almost epidemic proportions our knowledge of the mechanism of this disease is limited. More information about insulin secretion and action and the genetic variability of the various factors involved will contribute to better understanding and classification of this group of diseases. This article discusses the results of various genetic studies on diabetes with special reference to Indian population.

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Earth system models (ESMs) are increasing in complexity by incorporating more processes than their predecessors, making them potentially important tools for studying the evolution of climate and associated biogeochemical cycles. However, their coupled behaviour has only recently been examined in any detail, and has yielded a very wide range of outcomes. For example, coupled climate–carbon cycle models that represent land-use change simulate total land carbon stores at 2100 that vary by as much as 600 Pg C, given the same emissions scenario. This large uncertainty is associated with differences in how key processes are simulated in different models, and illustrates the necessity of determining which models are most realistic using rigorous methods of model evaluation. Here we assess the state-of-the-art in evaluation of ESMs, with a particular emphasis on the simulation of the carbon cycle and associated biospheric processes. We examine some of the new advances and remaining uncertainties relating to (i) modern and palaeodata and (ii) metrics for evaluation. We note that the practice of averaging results from many models is unreliable and no substitute for proper evaluation of individual models. We discuss a range of strategies, such as the inclusion of pre-calibration, combined process- and system-level evaluation, and the use of emergent constraints, that can contribute to the development of more robust evaluation schemes. An increasingly data-rich environment offers more opportunities for model evaluation, but also presents a challenge. Improved knowledge of data uncertainties is still necessary to move the field of ESM evaluation away from a "beauty contest" towards the development of useful constraints on model outcomes.

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It is increasingly important to know about when energy is used in the home, at work and on the move. Issues of time and timing have not featured strongly in energy policy analysis and in modelling, much of which has focused on estimating and reducing total average annual demand per capita. If smarter ways of balancing supply and demand are to take hold, and if we are to make better use of decarbonised forms of supply, it is essential to understand and intervene in patterns of societal synchronisation. This calls for detailed knowledge of when, and on what occasions many people engage in the same activities at the same time, of how such patterns are changing, and of how might they be shaped. In addition, the impact of smart meters and controls partly depends on whether there is, in fact scope for shifting the timing of what people do, and for changing the rhythm of the day. Is the scheduling of daily life an arena that policy can influence, and if so how? The DEMAND Centre has been linking time use, energy consumption and travel diary data as a means of addressing these questions and in this working paper we present some of the issues and results arising from that exercise.

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Initial phase of all Enterprise Architecture (EA) initiatives is important. One of the most crucial tasks in that phase is to sell EA to the top management by explaining its purpose. In this paper, by using semiotic framework we show that there is a clear gap between the definition of EA and its purpose. Contribution of this paper is a taxonomy that expands knowledge of pragmatics of EA, and that can be used as a tool for explaining the purpose of EA. Grounded theory is used to form the taxonomy. Data is collected from a discussion group used by EA practitioners. Results indicate that the purpose of EA is to meet organisations‟ stakeholder‟s goals and to create value to organisation. Results are in line with current literature. Most interesting result is that EA practitioners seem to realise that technical solutions are not the purpose of EA, but means for fulfilling it.

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In this study of the structure of self-knowledge, we examined priming effects for the recall of personal episodes in order to investigate whether abstract trait knowledge and personal episodes are independent mental representations. We found that accessing similar abstract representations of traits facilitated a faster recall of related personal episodes than did accessing irrelevant abstract representations of traits (Experiments 1 and 2), reading a nonword prime (Experiments 2 and 3), accessing knowledge of one's mother (Experiment 3), or accessing semantic knowledge (Experiment 3). Contrary to previous findings, which indicated that abstract trait knowledge is represented independently of related personal episodes (e.g., Klein & Loftus, 1993, our results suggest that abstract trait knowledge is associated with personal episodes, and therefore that semantic self-knowledge is associated with episodic self-knowledge in long-term self-knowledge.

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Background: Stable-isotope ratios of carbon (13C/12C, expressed as δ13C) and nitrogen (15N/14N, or δ15N) have been proposed as potential nutritional biomarkers to distinguish between meat, fish, and plant-based foods. Objective: The objective was to investigate dietary correlates of δ13C and δ15N and examine the association of these biomarkers with incident type 2 diabetes in a prospective study. Design: Serum δ13C and δ15N (‰) were measured by using isotope ratio mass spectrometry in a case-cohort study (n = 476 diabetes cases; n = 718 subcohort) nested within the European Prospective Investigation into Cancer and Nutrition (EPIC)–Norfolk population-based cohort. We examined dietary (food-frequency questionnaire) correlates of δ13C and δ15N in the subcohort. HRs and 95% CIs were estimated by using Prentice-weighted Cox regression. Results: Mean (±SD) δ13C and δ15N were −22.8 ± 0.4‰ and 10.2 ± 0.4‰, respectively, and δ13C (r = 0.22) and δ15N (r = 0.20) were positively correlated (P < 0.001) with fish protein intake. Animal protein was not correlated with δ13C but was significantly correlated with δ15N (dairy protein: r = 0.11; meat protein: r = 0.09; terrestrial animal protein: r = 0.12, P ≤ 0.013). δ13C was inversely associated with diabetes in adjusted analyses (HR per tertile: 0.74; 95% CI: 0.65, 0.83; P-trend < 0.001], whereas δ15N was positively associated (HR: 1.23; 95% CI: 1.09, 1.38; P-trend = 0.001). Conclusions: The isotope ratios δ13C and δ15N may both serve as potential biomarkers of fish protein intake, whereas only δ15N may reflect broader animal-source protein intake in a European population. The inverse association of δ13C but a positive association of δ15N with incident diabetes should be interpreted in the light of knowledge of dietary intake and may assist in identifying dietary components that are associated with health risks and benefits.