Transonic Aeroelastic Stability Predictions Under the Influence of Structural Variability

Flutter prediction as currently practiced is almost always deterministic in nature, based on a single structural model that is assumed to represent a fleet of aircraft. However, it is also recognized that there can be significant structural variability, even for different flights of the same aircraft. The safety factor used for flutter clearance is in part meant to account for this variability. Simulation tools can, however, represent the consequences of structural variability in the flutter predictions, providing extra information that could be useful in planning physical tests and assessing risk. The main problem arising for this type of calculation when using high-fidelity tools based on computational fluid dynamics is the computational cost. The current paper uses an eigenvalue-based stability method together with Euler-level aerodynamics and different methods for propagating structural variability to stability predictions. The propagation methods are Monte Carlo, perturbation, and interval analysis. The feasibility of this type of analysis is demonstrated. Results are presented for the Goland wing and a generic fighter configuration.

Reducing Uncertainty in Aeroelastic Flutter Boundaries Using Experimental Data

Flutter prediction as currently practiced is usually deterministic, with a single structural model used to represent an aircraft. By using interval analysis to take into account structural variability, recent work has demonstrated that small changes in the structure can lead to very large changes in the altitude at which
utter occurs (Marques, Badcock, et al., J. Aircraft, 2010). In this follow-up work we examine the same phenomenon using probabilistic collocation (PC), an uncertainty quantification technique which can eficiently propagate multivariate stochastic input through a simulation code,
in this case an eigenvalue-based fluid-structure stability code. The resulting analysis predicts the consequences of an uncertain structure on incidence of
utter in probabilistic terms { information that could be useful in planning
flight-tests and assessing the risk of structural failure. The uncertainty in
utter altitude is confirmed to be substantial. Assuming that the structural uncertainty represents a epistemic uncertainty regarding the
structure, it may be reduced with the availability of additional information { for example aeroelastic response data from a flight-test. Such data is used to update the structural uncertainty using Bayes' theorem. The consequent
utter uncertainty is significantly reduced across the entire Mach number range.

Risk-informed decision-making in the presence of epistemic uncertainty

An important issue in risk analysis is the distinction between epistemic and aleatory uncertainties. In this paper, the use of distinct representation formats for aleatory and epistemic uncertainties is advocated, the latter being modelled by sets of possible values. Modern uncertainty theories based on convex sets of probabilities are known to be instrumental for hybrid representations where aleatory and epistemic components of uncertainty remain distinct. Simple uncertainty representation techniques based on fuzzy intervals and p-boxes are used in practice. This paper outlines a risk analysis methodology from elicitation of knowledge about parameters to decision. It proposes an elicitation methodology where the chosen representation format depends on the nature and the amount of available information. Uncertainty propagation methods then blend Monte Carlo simulation and interval analysis techniques. Nevertheless, results provided by these techniques, often in terms of probability intervals, may be too complex to interpret for a decision-maker and we, therefore, propose to compute a unique indicator of the likelihood of risk, called confidence index. It explicitly accounts for the decisionmaker’s attitude in the face of ambiguity. This step takes place at the end of the risk analysis process, when no further collection of evidence is possible that might reduce the ambiguity due to epistemic uncertainty. This last feature stands in contrast with the Bayesian methodology, where epistemic uncertainties on input parameters are modelled by single subjective probabilities at the beginning of the risk analysis process.

The role of private care in the interval between diagnosis and treatment of breast cancer in Northern Ireland: an analysis of Registry data

Objective: To examine the differences in the interval between diagnosis and initiation of treatment among women with breast cancer in Northern Ireland.

Design: A cross-sectional observational study.
Setting: All breast cancer care patients in the Northern Ireland Cancer Registry in 2006.
Participants: All women diagnosed and treated for breast cancer in Northern Ireland in 2006.
Main outcome measure: The number of days between diagnosis and initiation of treatment for breast cancer.

Results: The mean (median) interval between diagnosis and initiation of treatment among public patients was 19 (15) compared with 14 (12) among those whose care involved private providers. The differences between individual public providers were as marked as those between the public and private sector - the mean (median) ranging between 14 (12) and 25 (22) days. Multivariate models revealed that the differences were evident when a range of patient characteristics were controlled for including cancer stage.

Conclusions: A relatively small number of women received care privately in Northern Ireland but experienced shorter intervals between diagnosis and initiation of treatment than those who received care wholly in the public system. The variation among public providers was as great as that between the public and private providers. The impact of such differences on survival and in light of waiting time targets introduced in Northern Ireland warrants investigation.

A meta-analysis of the association between Caesarean section and childhood asthma

Background: Children born by Caesarean section have modified intestinal bacterial colonization and consequently may have an increased risk of developing asthma under the hygiene hypothesis. The results of previous studies that have investigated the association between Caesarean section and asthma have been conflicting.

Objective: To review published literature and perform a meta-analysis summarizing the evidence in support of an association between children born by Caesarean section and asthma.

Methods: MEDLINE, Web Science, Google Scholar and PubMed were searched to identify relevant studies. Odds ratio (OR) and 95% confidence interval (CI) were calculated for each study from the reported prevalence of asthma in children born by Caesarean section and in control children. Meta-analysis was then used to derive a combined OR and test for heterogeneity in the findings between studies.

Results: Twenty-three studies were identified. The overall meta-analysis revealed an increase in the risk of asthma in children delivered by Caesarean section (OR=1.22, 95% CI 1.14, 1.29). However, in this analysis, there was evidence of heterogeneity (I2=46%) that was statistically significant (P<0.001). Restricting the analysis to childhood studies, this heterogeneity was markedly decreased (I2=32%) and no longer attained statistical significance (P=0.08). In these studies, there was also evidence of an increase (P<0.001) in the risk of asthma after Caesarean section (OR=1.20, 95% CI 1.14, 12.6).

Conclusion: In this meta-analysis, we found a 20% increase in the subsequent risk of asthma in children who had been delivered by Caesarean section.

Positive dilations of piecewise monotonic Markov maps

We provide an explicit formula which gives natural extensions of piecewise monotonic Markov maps defined on an interval of the real line. These maps are exact endomorphisms and define chaotic discrete dynamical systems.

Homocysteine, Methylenetetrahydrofolate Reductase C677T Polymorphism, and Risk of Retnal Vein Occlusion: A Meta-analysis

Objective: To assess the role of plasma total homocysteine (tHcy) concentrations and homozygosity for the thermolabile variant of the methylenetetrahydrofolate reductase (MTHFR) C677T gene as risk factors for retinal vascular occlusive disease.

Design: Retinal vein occlusion (RVO) is an important cause of vision loss. Early meta-analyses showed that tHcy was associated with an increased risk of RVO, but a significant number of new studies have been published. Participants and/or Controls: RVO patients and controls.

Methods: Data sources included MEDLINE, Web of Science, and PubMed searches and searching reference lists of relevant articles and reviews. Reviewers searched the databases, selected the studies, and then extracted data. Results were pooled quantitatively using meta-analytic methods.

Main Outcome Measures: tHcy concentrations and MTHFR genotype.

Results: There were 25 case-control studies for tHcy (1533 cases and 1708 controls) and 18 case-control studies for MTHFR (1082 cases and 4706 controls). The mean tHcy was on average 2.8 mol/L (95% confidence
interval [CI], 1.8 –3.7) greater in the RVO cases compared with controls, but there was evidence of between-study heterogeneity (P0.001, I2 93%). There was funnel plot asymmetry suggesting publication bias. There was no evidence of association between homozygosity for the MTHFR C677T genotype and RVO (odds ratio [OR] 1.20; 95% CI, 0.84–1.71), but again marked heterogeneity (P 0.004, I2 53%) was observed.

Conclusions: There was some evidence that elevated tHcy was associated with RVO, but not homozygosity for the MTHFR C677T genotype. Both analyses should be interpreted cautiously because of marked heterogeneity between the study estimates and possible effect of publication bias on the tHcy findings.

Financial Disclosure(s): The author(s) have no proprietary or commercial interest in any materials discussed in this article.

Performing meta-analysis with incomplete statistical information in clinical trials

Background: Results from clinical trials are usually summarized in the form of sampling distributions. When full information (mean, SEM) about these distributions is given, performing meta-analysis is straightforward. However, when some of the sampling distributions only have mean values, a challenging issue is to decide how to use such distributions in meta-analysis. Currently, the most common approaches are either ignoring such trials or for each trial with a missing SEM, finding a similar trial and taking its SEM value as the missing SEM. Both approaches have drawbacks. As an alternative, this paper develops and tests two new methods, the first being the prognostic method and the second being the interval method, to estimate any missing SEMs from a set of sampling distributions with full information. A merging method is also proposed to handle clinical trials with partial information to simulate meta-analysis.

Query cost estimation through remote system contention states analysis over the Internet

Query processing over the Internet involving autonomous data sources is a major task in data integration. It requires the estimated costs of possible queries in order to select the best one that has the minimum cost. In this context, the cost of a query is affected by three factors: network congestion, server contention state, and complexity of the query. In this paper, we study the effects of both the network congestion and server contention state on the cost of a query. We refer to these two factors together as system contention states. We present a new approach to determining the system contention states by clustering the costs of a sample query. For each system contention state, we construct two cost formulas for unary and join queries respectively using the multiple regression process. When a new query is submitted, its system contention state is estimated first using either the time slides method or the statistical method. The cost of the query is then calculated using the corresponding cost formulas. The estimated cost of the query is further adjusted to improve its accuracy. Our experiments show that our methods can produce quite accurate cost estimates of the submitted queries to remote data sources over the Internet.

Analysis of Receiver Algorithms for LTE SC-FDMA Based Uplink MIMO Systems

This letter derives mathematical expressions for the received signal-to-interference-plus-noise ratio (SINR) of uplink Single Carrier (SC) Frequency Division Multiple Access (FDMA) multiuser MIMO systems. An improved frequency domain receiver algorithm is derived for the studied systems, and is shown to be significantly superior to the conventional linear MMSE based receiver in terms of SINR and bit error rate (BER) performance.