Reducing Parametric Uncertainty in Limit Cycle Oscillations

The assimilation of discrete higher fidelity data points with model predictions can be used to achieve a reduction in the uncertainty of the model input parameters which generate accurate predictions. The problem investigated here involves the prediction of limit-cycle oscillations using a High-Dimensional Harmonic Balance method (HDHB). The efficiency of the HDHB method is exploited to enable calibration of structural input parameters using a Bayesian inference technique. Markov-chain Monte Carlo is employed to sample the posterior distributions. Parameter estimation is carried out on both a pitch/plunge aerofoil and Goland wing configuration. In both cases significant refinement was achieved in the distribution of possible structural parameters allowing better predictions of their
true deterministic values.

Analysing Web-Orchestrations Under Stress Using Uncertainty Profiles

An orchestration is a multi-threaded computation that invokes a number of remote services. In practice, the responsiveness of a web-service fluctuates with demand; during surges in activity service responsiveness may be degraded, perhaps even to the point of failure. An uncertainty profile formalizes a user's perception of the effects of stress on an orchestration of web-services; it describes a strategic situation, modelled by a zero-sum angel–daemon game. Stressed web-service scenarios are analysed, using game theory, in a realistic way, lying between over-optimism (services are entirely reliable) and over-pessimism (all services are broken). The ‘resilience’ of an uncertainty profile can be assessed using the valuation of its associated zero-sum game. In order to demonstrate the validity of the approach, we consider two measures of resilience and a number of different stress models. It is shown how (i) uncertainty profiles can be ordered by risk (as measured by game valuations) and (ii) the structural properties of risk partial orders can be analysed.

Uncertainty in the Cloud: An Angel-Daemon Approach to Modelling Performance

Uncertainty profiles are used to study the effects of contention within cloud and service-based environments. An uncertainty profile provides a qualitative description of an environment whose quality of service (QoS) may fluctuate unpredictably. Uncertain environments are modelled by strategic games with two agents; a daemon is used to represent overload and high resource contention; an angel is used to represent an idealised resource allocation situation with no underlying contention. Assessments of uncertainty profiles are useful in two ways: firstly, they provide a broad understanding of how environmental stress can effect an application’s performance (and reliability); secondly, they allow the effects of introducing redundancy into a computation to be assessed

Artificial neural network model to predict compositional viscosity over a broad range of temperatures

The objective of this study is to provide an alternative model approach, i.e., artificial neural network (ANN) model, to predict the compositional viscosity of binary mixtures of room temperature ionic liquids (in short as ILs) [C _n-mim] [NTf ₂] with n=4, 6, 8, 10 in methanol and ethanol over the entire range of molar fraction at a broad range of temperatures from T=293.0328.0K. The results show that the proposed ANN model provides alternative way to predict compositional viscosity successfully with highly improved accuracy and also show its potential to be extensively utilized to predict compositional viscosity over a wide range of temperatures and more complex viscosity compositions, i.e., more complex intermolecular interactions between components in which it would be hard or impossible to establish the analytical model. © 2010 IEEE.

Loss of exudates from the roots of perennial ryegrass inoculated with a range of micro-organisms

To determine the effect of microbial metabolites on the release of root exudates from perennial ryegrass, seedlings were pulse labelled with [¹⁴C]-CO₂ in the presence of a range of soil micro-organisms. Microbial inoculants were spatially separated from roots by Millipore membranes so that root infection did not occur. Using this technique, only microbial metabolites affected root exudation. The effect of microbial metabolites on carbon assimilation and distribution and root exudation was determined for 15 microbial species. Assimilation of a pulse label varied by over 3.5 fold, dependent on inoculant. Distribution of the label between roots and shoots also varied with inoculant, but the carbon pool that was most sensitive to inoculation was root exudation. In the absence of a microbial inoculant only 1% of assimilated label was exuded. Inoculation of the microcosms always caused an increase in exudation but the percentage exuded varied greatly, within the range of 3-34%. © 1995 Kluwer Academic Publishers.

Suppression of the high affinity phosphate uptake system:A mechanism of arsenate tolerance in Holcus lanatus L.

In Holcus lanatus L. phosphate and arsenate are taken up by the same transport system. Short-term uptake kinetics of the high affinity arsenate transport system were determined in excised roots of arsenate-tolerant and non-tolerant genotypes. In tolerant plants the V_max of ion uptake in plants grown in phosphate-free media was decreased compared to non-tolerant plants, and the affinity of the uptake system was lower than in the non-tolerant plants. Both the reduction in V_max and the increase in K_m led to reduced arsenate influx into tolerant roots. When the two genotypes were grown in nutrient solution containing high levels of phosphate, there was little change in the uptake kinetics in tolerant plants. In non-tolerant plants, however, there was a marked decrease in the V_max to the level of the tolerant plants but with little change in the K_m. This suggests that the low rate of arsenate uptake over a wide range of differing root phosphate status is due to loss of induction of the synthesis of the arsenate (phosphate) carrier. © 1992 Oxford University Press.

Wilms' tumor gene 1 (WT1) expression in childhood acute lymphoblastic leukemia:a wide range of WT1 expression levels, its impact on prognosis and minimal residual disease monitoring

Wilms' tumor gene 1 (WT1) is overexpressed in the majority (70-90%) of acute leukemias and has been identified as an independent adverse prognostic factor, a convenient minimal residual disease (MRD) marker and potential therapeutic target in acute leukemia. We examined WT1 expression patterns in childhood acute lymphoblastic leukemia (ALL), where its clinical implication remains unclear. Using a real-time quantitative PCR designed according to Europe Against Cancer Program recommendations, we evaluated WT1 expression in 125 consecutively enrolled patients with childhood ALL (106 BCP-ALL, 19 T-ALL) and compared it with physiologic WT1 expression in normal and regenerating bone marrow (BM). In childhood B-cell precursor (BCP)-ALL, we detected a wide range of WT1 levels (5 logs) with a median WT1 expression close to that of normal BM. WT1 expression in childhood T-ALL was significantly higher than in BCP-ALL (P<0.001). Patients with MLL-AF4 translocation showed high WT1 overexpression (P<0.01) compared to patients with other or no chromosomal aberrations. Older children (> or =10 years) expressed higher WT1 levels than children under 10 years of age (P<0.001), while there was no difference in WT1 expression in patients with peripheral blood leukocyte count (WBC) > or =50 x 10(9)/l and lower. Analysis of relapsed cases (14/125) indicated that an abnormal increase or decrease in WT1 expression was associated with a significantly increased risk of relapse (P=0.0006), and this prognostic impact of WT1 was independent of other main risk factors (P=0.0012). In summary, our study suggests that WT1 expression in childhood ALL is very variable and much lower than in AML or adult ALL. WT1, thus, will not be a useful marker for MRD detection in childhood ALL, however, it does represent a potential independent risk factor in childhood ALL. Interestingly, a proportion of childhood ALL patients express WT1 at levels below the normal physiological BM WT1 expression, and this reduced WT1 expression appears to be associated with a higher risk of relapse.