Data-driven optimal filtering for phase and frequency of noisy oscillations: Application to vortex flow metering

A method for measuring the phase of oscillations from noisy time series is proposed. To obtain the phase, the signal is filtered in such a way that the filter output has minimal relative variation in the amplitude over all filters with complex-valued impulse response. The argument of the filter output yields the phase. Implementation of the algorithm and interpretation of the result are discussed. We argue that the phase obtained by the proposed method has a low susceptibility to measurement noise and a low rate of artificial phase slips. The method is applied for the detection and classification of mode locking in vortex flow meters. A measure for the strength of mode locking is proposed.

Rule Britannia!: British Stock Market Returns, 1825-1870

This article presents a new series of monthly equity returns for the British stock market for the period 1825-1870. In addition to calculating capital appreciation and dividend yields, the article also estimates the effect of survivorship bias on returns. Three notable findings emerge from this study. First, stock market returns in the 1825-1870 period are broadly similar for Britain and the United States, although the British market is less risky. Second, real returns in the 1825-1870 period are higher than in subsequent epochs of British history. Third, unlike the modern era, dividends are the most important component of returns.

'Rule of Law and Politics of Anti-Corruption Campaigns in a Post-Authoritarian State- The Nigerian Case'

This article evaluates the anti-corruption campaign instituted in Nigeria following on the post-authoritarian transition in the country, with specific focus on political corruption. The anti-corruption campaign is being prosecuted within a context where law is as critical a factor as politics. This article examines whether the judiciary, in view of its accountability deficit, can offer legitimacy to the campaign. How has its questionable credentials impacted on its involvement in the campaign to sanitise public life? What has been the impact of the judicial role on the rule of law? These are some of the important questions this article seeks to answer. The inquiry in this article demonstrates how the guardian institution of the rule of law faces an uphill task in the performance of that role in a post-authoritarian context.

Optimal glycaemic control, pre-eclampsia and gestational hypertension in women with type 1 diabetes in the Diabetes and Pre-Eclampsia Intervention Trial

OBJECTIVE
To assess the relationship between glycemic control, pre-eclampsia, and gestational hypertension in women with type 1 diabetes.

RESEARCH DESIGN AND METHODS
Pregnancy outcome (pre-eclampsia or gestational hypertension) was assessed prospectively in 749 women from the randomized controlled Diabetes and Pre-eclampsia Intervention Trial (DAPIT). HbA1c (A1C) values were available up to 6 months before pregnancy (n = 542), at the first antenatal visit (median 9 weeks) (n = 721), at 26 weeks’ gestation (n = 592), and at 34 weeks’ gestation (n = 519) and were categorized as optimal (<6.1%: referent), good (6.1–6.9%), moderate (7.0–7.9%), and poor (=8.0%) glycemic control, respectively.

RESULTS
Pre-eclampsia and gestational hypertension developed in 17 and 11% of pregnancies, respectively. Women who developed pre-eclampsia had significantly higher A1C values before and during pregnancy compared with women who did not develop pre-eclampsia (P < 0.05, respectively). In early pregnancy, A1C =8.0% was associated with a significantly increased risk of pre-eclampsia (odds ratio 3.68 [95% CI 1.17–11.6]) compared with optimal control. At 26 weeks’ gestation, A1C values =6.1% (good: 2.09 [1.03–4.21]; moderate: 3.20 [1.47–7.00]; and poor: 3.81 [1.30–11.1]) and at 34 weeks’ gestation A1C values =7.0% (moderate: 3.27 [1.31–8.20] and poor: 8.01 [2.04–31.5]) significantly increased the risk of pre-eclampsia compared with optimal control. The adjusted odds ratios for pre-eclampsia for each 1% decrement in A1C before pregnancy, at the first antenatal visit, at 26 weeks’ gestation, and at 34 weeks’ gestation were 0.88 (0.75–1.03), 0.75 (0.64–0.88), 0.57 (0.42–0.78), and 0.47 (0.31–0.70), respectively. Glycemic control was not significantly associated with gestational hypertension.

CONCLUSIONS
Women who developed pre-eclampsia had significantly higher A1C values before and during pregnancy. These data suggest that optimal glycemic control both early and throughout pregnancy may reduce the risk of pre-eclampsia in women with type 1 diabetes.

Numerical Investigation of Optimal Pin Actuator Location on a Supersonic Projectile

The flowfield around a supersonic projectile using a pin actuator control method has been predicted using computational fluid dynamics. It has been predicted using both viscous and inviscid methods for a number of positions. Both methods showed that an optimal longitudinal position exists. However, the inviscid model over-predicted the lateral acceleration due to the difference in shock formation around the pin between the two approaches. The optimal location was predicted independent of solver, however the higher-fidelity solver predicted lower achievable lateral accelerations. This is due to the viscous interactions caused by the pin. The effect of projectile orientation has shown that shielding the pin leads to reduced effectiveness due to the wake of the fin enveloping the pin. When the pin is exposed to onset flow, the forces achieved are increased. There is also an increase in the achievable forces and moments with increasing Mach number.

Optimal control of atom transport for quantum gates in optical lattices

By means of optimal control techniques we model and optimize the manipulation of the external quantum state (center-of-mass motion) of atoms trapped in adjustable optical potentials. We consider in detail the cases of both noninteracting and interacting atoms moving between neighboring sites in a lattice of a double-well optical potentials. Such a lattice can perform interaction-mediated entanglement of atom pairs and can realize two-qubit quantum gates. The optimized control sequences for the optical potential allow transport faster and with significantly larger fidelity than is possible with processes based on adiabatic transport.

A heterosynaptic learning rule for neural networks

In this article we intoduce a novel stochastic Hebb-like learning rule for neural networks that is neurobiologically motivated. This learning rule combines features of unsupervised (Hebbian) and supervised (reinforcement) learning and is stochastic with respect to the selection of the time points when a synapse is modified. Moreover, the learning rule does not only affect the synapse between pre- and postsynaptic neuron, which is called homosynaptic plasticity, but effects also further remote synapses of the pre-and postsynaptic neuron. This more complex form of synaptic plasticity has recently come under investigations in neurobiology and is called heterosynaptic plasticity. We demonstrate that this learning rule is useful in training neural networks by learning parity functions including the exclusive-or (XOR) mapping in a multilayer feed-forward network. We find, that our stochastic learning rule works well, even in the presence of noise. Importantly, the mean leaxning time increases with the number of patterns to be learned polynomially, indicating efficient learning.

Measuring Inconsistency in a Network Intrusion Detection Rule Set Based on Snort

In this preliminary study, we investigate how inconsistency in a network intrusion detection rule set can be measured. To achieve this, we first examine the structure of these rules which are based on Snort and incorporate regular expression (Regex) pattern matching. We then identify primitive elements in these rules in order to translate the rules into their (equivalent) logical forms and to establish connections between them. Additional rules from background knowledge are also introduced to make the correlations among rules more explicit. We measure the degree of inconsistency in formulae of such a rule set (using the Scoring function, Shapley inconsistency values and Blame measure for prioritized knowledge) and compare the informativeness of these measures. Finally, we propose a new measure of inconsistency for prioritized knowledge which incorporates the normalized number of atoms in a language involved in inconsistency to provide a deeper inspection of inconsistent formulae. We conclude that such measures are useful for the network intrusion domain assuming that introducing expert knowledge for correlation of rules is feasible.