36 resultados para Inconsistency


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Aims/hypothesis Glomerular hyperfiltration is a well established phenomenon occurring early in some patients with type 1 diabetes. However, there is no consistent answer regarding whether hyperfiltration predicts later development of nephropathy. We performed a systematic review and meta-analysis of observational studies that compared the risk of developing diabetic nephropathy in patients with and without glomerular hyperfiltration and also explored the impact of baseline GFR.

Methods A systematic review and meta-analysis was carried out. Cohort studies in type 1 diabetic participants were included if they contained data on the development of incipient or overt nephropathy with baseline measurement
of GFR and presence or absence of hyperfiltration.

Results We included ten cohort studies following 780 patients. After a study median follow-up of 11.2 years, 130 patients had developed nephropathy. Using a random effects model, the pooled odds of progression to a minimum
of microalbuminuria in patients with hyperfiltration was 2.71 (95% CI 1.20–6.11) times that of patients with normofiltration. There was moderate heterogeneity (heterogeneity test p=0.05, measure of degree of inconsistency=48%) and some evidence of funnel plot asymmetry, possibly due to publication bias. The pooled weighted mean difference in baseline GFR was 13.8 ml min-1 1.73 m-2 (95% CI 5.0–22.7) greater in the group progressing to nephropathy than in those not progressing (heterogeneity test p<0.01).

Conclusions/interpretation In published studies, individuals with glomerular hyperfiltration were at increased risk of progression to diabetic nephropathy using study level data. Further larger studies are required to explore this relationship and the role of potential confounding variables.

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With the rapid growth in the quantity and complexity of scientific knowledge available for scientists, and allied professionals, the problems associated with harnessing this knowledge are well recognized. Some of these problems are a result of the uncertainties and inconsistencies that arise in this knowledge. Other problems arise from heterogeneous and informal formats for this knowledge. To address these problems, developments in the application of knowledge representation and reasoning technologies can allow scientific knowledge to be captured in logic-based formalisms. Using such formalisms, we can undertake reasoning with the uncertainty and inconsistency to allow automated techniques to be used for querying and combining of scientific knowledge. Furthermore, by harnessing background knowledge, the querying and combining tasks can be carried out more intelligently. In this paper, we review some of the significant proposals for formalisms for representing and reasoning with scientific knowledge.

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In this paper, I argue that there is an inconsistency between two presentist doctrines: that of ontological symmetry and asymmetry of fixity. The former refers to the presentist belief that the past and future are equally unreal. The latter refers to the A-Theoretic intuition that the past is closed or actual, and the future is open or potential. My position in this paper is that the presentist is unable to account for the temporal asymmetry that is so fundamentally a part of her theory. In Section I, I briefly outline a recent defence of presentism due to Craig, and argue that a flaw in this defence highlights the tension between the presentist's doctrines of ontological symmetry and asymmetry of fixity. In Section II, I undertake an investigation, on the presentist's behalf, in order to determine whether she is capable of reconciling these two doctrines. In the course of the investigation, I consider different asymmetries, other than that of ontology, which might be said fundamentally to constitute temporal asymmetry, and the asymmetry of fixity in particular. In Section III, I also consider whether the presentist is able to avail herself of some of the standard B-Theoretic accounts of the asymmetry of fixity, and argue that she cannot. Finally, I conclude that temporal asymmetry cannot be accounted for (or explained) other than through the postulation of an ontological asymmetry.

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Astrocytic tumors are the most common intracranial neoplasms. Their prognoses correlate with a conventional morphological grading system that suffers from diagnostic subjectivity and hence, inter-observer inconsistency. A molecular marker that provides an objective reference for classification and prognostication of astrocytic tumors would be useful in diagnostic pathology. RhoA, a GTPase protein involved in cell migration and adhesion has been shown to be upregulated in a variety of human cancers. Based on direct analysis of clinical materials, our study demonstrates increased expression of RhoA in high-grade astrocytomas. This observation may be relevant to astrocytoma biology and the development of potential therapeutics against high-grade astrocytomas. Of more immediate consequence, utilization of this marker may aid in the routine pathological grading (and hence prognostication) of astrocytomas. (c) 2006 Elsevier Ireland Ltd. All rights reserved.

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Background: Postal and electronic questionnaires are widely used for data collection in epidemiological studies but non-response reduces the effective sample size and can introduce bias. Finding ways to increase response to postal and electronic questionnaires would improve the quality of health research. Objectives: To identify effective strategies to increase response to postal and electronic questionnaires. Search strategy: We searched 14 electronic databases to February 2008 and manually searched the reference lists of relevant trials and reviews, and all issues of two journals. We contacted the authors of all trials or reviews to ask about unpublished trials. Where necessary, we also contacted authors to confirm methods of allocation used and to clarify results presented. We assessed the eligibility of each trial using pre-defined criteria. Selection criteria: Randomised controlled trials of methods to increase response to postal or electronic questionnaires. Data collection and analysis: We extracted data on the trial participants, the intervention, the number randomised to intervention and comparison groups and allocation concealment. For each strategy, we estimated pooled odds ratios (OR) and 95% confidence intervals (CI) in a random-effects model. We assessed evidence for selection bias using Egger's weighted regression method and Begg's rank correlation test and funnel plot. We assessed heterogeneity among trial odds ratios using a Chi 2 test and the degree of inconsistency between trial results was quantified using the I 2 statistic. Main results: Postal We found 481 eligible trials.The trials evaluated 110 different ways of increasing response to postal questionnaires.We found substantial heterogeneity among trial results in half of the strategies. The odds of response were at least doubled using monetary incentives (odds ratio 1.87; 95% CI 1.73 to 2.04; heterogeneity P < 0.00001, I 2 = 84%), recorded delivery (1.76; 95% CI 1.43 to 2.18; P = 0.0001, I 2 = 71%), a teaser on the envelope - e.g. a comment suggesting to participants that they may benefit if they open it (3.08; 95% CI 1.27 to 7.44) and a more interesting questionnaire topic (2.00; 95% CI 1.32 to 3.04; P = 0.06, I 2 = 80%). The odds of response were substantially higher with pre-notification (1.45; 95% CI 1.29 to 1.63; P < 0.00001, I 2 = 89%), follow-up contact (1.35; 95% CI 1.18 to 1.55; P < 0.00001, I 2 = 76%), unconditional incentives (1.61; 1.36 to 1.89; P < 0.00001, I 2 = 88%), shorter questionnaires (1.64; 95%CI 1.43 to 1.87; P < 0.00001, I 2 = 91%), providing a second copy of the questionnaire at follow up (1.46; 95% CI 1.13 to 1.90; P < 0.00001, I 2 = 82%), mentioning an obligation to respond (1.61; 95% CI 1.16 to 2.22; P = 0.98, I 2 = 0%) and university sponsorship (1.32; 95% CI 1.13 to 1.54; P < 0.00001, I 2 = 83%). The odds of response were also increased with non-monetary incentives (1.15; 95% CI 1.08 to 1.22; P < 0.00001, I 2 = 79%), personalised questionnaires (1.14; 95% CI 1.07 to 1.22; P < 0.00001, I 2 = 63%), use of hand-written addresses (1.25; 95% CI 1.08 to 1.45; P = 0.32, I 2 = 14%), use of stamped return envelopes as opposed to franked return envelopes (1.24; 95% CI 1.14 to 1.35; P < 0.00001, I 2 = 69%), an assurance of confidentiality (1.33; 95% CI 1.24 to 1.42) and first class outward mailing (1.11; 95% CI 1.02 to 1.21; P = 0.78, I 2 = 0%). The odds of response were reduced when the questionnaire included questions of a sensitive nature (0.94; 95% CI 0.88 to 1.00; P = 0.51, I 2 = 0%). Electronic: We found 32 eligible trials. The trials evaluated 27 different ways of increasing response to electronic questionnaires. We found substantial heterogeneity among trial results in half of the strategies. The odds of response were increased by more than a half using non-monetary incentives (1.72; 95% CI 1.09 to 2.72; heterogeneity P < 0.00001, I 2 = 95%), shorter e-questionnaires (1.73; 1.40 to 2.13; P = 0.08, I 2 = 68%), including a statement that others had responded (1.52; 95% CI 1.36 to 1.70), and a more interesting topic (1.85; 95% CI 1.52 to 2.26). The odds of response increased by a third using a lottery with immediate notification of results (1.37; 95% CI 1.13 to 1.65), an offer of survey results (1.36; 95% CI 1.15 to 1.61), and using a white background (1.31; 95% CI 1.10 to 1.56). The odds of response were also increased with personalised e-questionnaires (1.24; 95% CI 1.17 to 1.32; P = 0.07, I 2 = 41%), using a simple header (1.23; 95% CI 1.03 to 1.48), using textual representation of response categories (1.19; 95% CI 1.05 to 1.36), and giving a deadline (1.18; 95% CI 1.03 to 1.34). The odds of response tripled when a picture was included in an e-mail (3.05; 95% CI 1.84 to 5.06; P = 0.27, I 2 = 19%). The odds of response were reduced when "Survey" was mentioned in the e-mail subject line (0.81; 95% CI 0.67 to 0.97; P = 0.33, I 2 = 0%), and when the e-mail included a male signature (0.55; 95% CI 0.38 to 0.80; P = 0.96, I 2 = 0%). Authors' conclusions: Health researchers using postal and electronic questionnaires can increase response using the strategies shown to be effective in this systematic review. Copyright © 2009 The Cochrane Collaboration. Published by John Wiley & Sons, Ltd.


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Belief revision characterizes the process of revising an agent’s beliefs when receiving new evidence. In the field of artificial intelligence, revision strategies have been extensively studied in the context of logic-based formalisms and probability kinematics. However, so far there is not much literature on this topic in evidence theory. In contrast, combination rules proposed so far in the theory of evidence, especially Dempster rule, are symmetric. They rely on a basic assumption, that is, pieces of evidence being combined are considered to be on a par, i.e. play the same role. When one source of evidence is less reliable than another, it is possible to discount it and then a symmetric combination operation
is still used. In the case of revision, the idea is to let prior knowledge of an agent be altered by some input information. The change problem is thus intrinsically asymmetric. Assuming the input information is reliable, it should be retained whilst the prior information should be changed minimally to that effect. To deal with this issue, this paper defines the notion of revision for the theory of evidence in such a way as to bring together probabilistic and logical views. Several revision rules previously proposed are reviewed and we advocate one of them as better corresponding to the idea of revision. It is extended to cope with inconsistency between prior and input information. It reduces to Dempster
rule of combination, just like revision in the sense of Alchourron, Gardenfors, and Makinson (AGM) reduces to expansion, when the input is strongly consistent with the prior belief function. Properties of this revision rule are also investigated and it is shown to generalize Jeffrey’s rule of updating, Dempster rule of conditioning and a form of AGM revision.

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It is increasingly recognized that identifying the degree of blame or responsibility of each formula for inconsistency of a knowledge base (i.e. a set of formulas) is useful for making rational decisions to resolve inconsistency in that knowledge base. Most current techniques for measuring the blame of each formula with regard to an inconsistent knowledge base focus on classical knowledge bases only. Proposals for measuring the blames of formulas with regard to an inconsistent prioritized knowledge base have not yet been given much consideration. However, the notion of priority is important in inconsistency-tolerant reasoning. This article investigates this issue and presents a family of measurements for the degree of blame of each formula in an inconsistent prioritized knowledge base by using the minimal inconsistent subsets of that knowledge base. First of all, we present a set of intuitive postulates as general criteria to characterize rational measurements for the blames of formulas of an inconsistent prioritized knowledge base. Then we present a family of measurements for the blame of each formula in an inconsistent prioritized knowledge base under the guidance of the principle of proportionality, one of the intuitive postulates. We also demonstrate that each of these measurements possesses the properties that it ought to have. Finally, we use a simple but explanatory example in requirements engineering to illustrate the application of these measurements. Compared to the related works, the postulates presented in this article consider the special characteristics of minimal inconsistent subsets as well as the priority levels of formulas. This makes them more appropriate to characterizing the inconsistency measures defined from minimal inconsistent subsets for prioritized knowledge bases as well as classical knowledge bases. Correspondingly, the measures guided by these postulates can intuitively capture the inconsistency for prioritized knowledge bases.

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The rapid increase in electricity demand in Chile means a choice must be made between major investments in renewable or non-renewable sources for additional production. Current projects to develop large dams for hydropower in Chilean Patagonia impose an environmental price by damaging the natural environment. On the other hand, the increased use of fossil fuels entails an environmental price in terms of air pollution and greenhouse gas emissions contributing to climate change. This paper studies the debate on future electricity supply in Chile by investigating the preferences of households for a variety of different sources of electricity generation such as fossil fuels, large hydropower in Chilean Patagonia and other renewable energy sources. Using Double Bounded Dichotomous Choice Contingent Valuation, a novel advanced disclosure method and internal consistency test are used to elicit the willingness to pay for less environmentally damaging sources. Policy results suggest a strong preference for renewable energy sources with higher environmental prices imposed by consumers on electricity generated from fossil fuels than from large dams in Chilean Patagonia. Policy results further suggest the possibility of introducing incentives for renewable energy developments that would be supported by consumers through green tariffs or environmental premiums. Methodological findings suggest that advanced disclosure learning overcomes the problem of internal inconsistency in SB-DB estimates.

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Belief merging is an important but difficult problem in Artificial Intelligence, especially when sources of information are pervaded with uncertainty. Many merging operators have been proposed to deal with this problem in possibilistic logic, a weighted logic which is powerful for handling inconsistency and deal-ing with uncertainty. They often result in a possibilistic knowledge base which is a set of weighted formulas. Although possibilistic logic is inconsistency tolerant, it suffers from the well-known "drowning effect". Therefore, we may still want to obtain a consistent possibilistic knowledge base as the result of merging. In such a case, we argue that it is not always necessary to keep weighted information after merging. In this paper, we define a merging operator that maps a set of possibilistic knowledge bases and a formula representing the integrity constraints to a classical knowledge base by using lexicographic ordering. We show that it satisfies nine postulates that generalize basic postulates for propositional merging given in [11]. These postulates capture the principle of minimal change in some sense. We then provide an algorithm for generating the resulting knowledge base of our merging operator. Finally, we discuss the compatibility of our merging operator with propositional merging and establish the advantage of our merging operator over existing semantic merging operators in the propositional case.

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While WiFi monitoring networks have been deployed in previous research, to date none have assessed live network data from an open access, public environment. In this paper we describe the construction of a replicable, independent WLAN monitoring system and address some of the challenges in analysing the resultant traffic. Analysis of traffic from the system demonstrates that basic traffic information from open-access networks varies over time (temporal inconsistency). The results also show that arbitrary selection of Request-Reply intervals can have a significant effect on Probe and Association frame exchange calculations, which can impact on the ability to detect flooding attacks.

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Objectives: To access the cognitions of adults with type 2 diabetes whilst completing items on the Illness Perceptions Questionnaire – Revised (IPQ-R). To determine whether these cognitions are congruent with the meaning of items and subscales as interpreted by researchers and clinicians using the IPQ-R and to identify the nature and extent of problems that individuals experience when completing the IPQ-R.
Design: Participants (n=36) were recruited from a primary care diabetes clinic and a hospital diabetes clinic. They were asked to complete the IPQ-R using a ‘think-aloud’ methodology.
Main Outcome Measures: Transcripts were analysed to identify instances where participants expressed problems with item completion, or where there was inconsistency between verbal and written responses.
Results: The most problematic subscales were those of ‘personal control’ and ‘consequences’.
Conclusion: Generally, participants found the IPQ-R unproblematic. However, participants had problems with the concept of ‘cure’ and ‘symptoms’ in the context of type 2 diabetes, and with the negative phrasing used in some items. These findings have important implications for the interpretation of IPQ-R scores, particularly when the IPQ-R is used as the basis for individualised interventions among people with type 2 diabetes.

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Systematic reviews have considerable potential to provide evidence-based data to aid clinical decision-making. However, there is growing recognition that trials involving mechanical ventilation lack consistency in the definition and measurement of ventilation outcomes, creating difficulties in combining data for meta-analyses. To address the inconsistency in outcome definitions, international standards for trial registration and clinical trial protocols published recommendations, effectively setting the “gold standard” for reporting trial outcomes. In this Critical Care Perspective, we review the problems resulting from inconsistent outcome definitions and inconsistent reporting of outcomes (outcome sets). We present data highlighting the variability of the most commonly reported ventilation outcome definitions. Ventilation outcomes reported in trials over the last 6 years typically fall into four domains: measures of ventilator dependence; adverse outcomes; mortality; and resource use. We highlight the need, first, for agreement on outcome definitions and, second, for a minimum core outcome set for trials involving mechanical ventilation. A minimum core outcome set would not restrict trialists from measuring additional outcomes, but would overcome problems of variability in outcome selection, measurement, and reporting, thereby enhancing comparisons across trials.

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Currently there is extensive theoretical work on inconsistencies in logic-based systems. Recently, algorithms for identifying inconsistent clauses in a single conjunctive formula have demonstrated that practical application of this work is possible. However, these algorithms have not been extended for full knowledge base systems and have not been applied to real-world knowledge. To address these issues, we propose a new algorithm for finding the inconsistencies in a knowledge base using existing algorithms for finding inconsistent clauses in a formula. An implementation of this algorithm is then presented as an automated tool for finding inconsistencies in a knowledge base and measuring the inconsistency of formulae. Finally, we look at a case study of a network security rule set for exploit detection (QRadar) and suggest how these automated tools can be applied.

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Belief merging operators combine multiple belief bases (a profile) into a collective one. When the conjunction of belief bases is consistent, all the operators agree on the result. However, if the conjunction of belief bases is inconsistent, the results vary between operators. There is no formal manner to measure the results and decide on which operator to select. So, in this paper we propose to evaluate the result of merging operators by using three ordering relations (fairness, satisfaction and strength) over operators for a given profile. Moreover, a relation of conformity over operators is introduced in order to classify how well the operator conforms to the definition of a merging operator. By using the four proposed relations we provide a comparison of some classical merging operators and evaluate the results for some specific profiles.

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