City University London

About: City University London is a education organization based out in London, United Kingdom. It is known for research contribution in the topics: Population & Health care. The organization has 5735 authors who have published 17285 publications receiving 453290 citations.

Managing Demand Risk in Tactical Supply Chain Planning for a Global Consumer Electronics Company

Abstract: We consider the problem of managing demand risk in tactical supply chain planning for a particular global consumer electronics company. The company follows a deterministic replenishment-and-planning process despite considerable demand uncertainty. As a possible way to formally address uncertainty, we provide two risk measures, “demand-at-risk” (DaR) and “inventory-at-risk” (IaR) and two linear programming models to help manage demand uncertainty. The first model is deterministic and can be used to allocate the replenishment schedule from the plants among the customers as per the existing process. The other model is stochastic and can be used to determine the “ideal” replenishment request from the plants under demand uncertainty. The gap between the output of the two models as regards requested replenishment and the values of the risk measures can be used by the company to reallocate capacity among different products and to thus manage demand/inventory risk.

Optimizing microsurgical skills with EEG neurofeedback.

Abstract: Background: By enabling individuals to self-regulate their brainwave activity in the field of optimal performance in healthy individuals, neurofeedback has been found to improve cognitive and artistic performance. Here we assessed whether two distinct EEG neurofeedback protocols could develop surgical skill, given the important role this skill plays in medicine. Results: National Health Service trainee ophthalmic microsurgeons (N = 20) were randomly assigned to either Sensory Motor Rhythm-Theta (SMR) or Alpha-Theta (AT) groups, a randomized subset of which were also part of a wait-list 'no-treatment' control group (N = 8). Neurofeedback groups received eight 30-minute sessions of EEG training. Pre-post assessment included a skills lab surgical procedure with timed measures and expert ratings from video-recordings by consultant surgeons, together with state/trait anxiety self-reports. SMR training demonstrated advantages absent in the control group, with improvements in surgical skill according to 1) the expert ratings: overall technique (d = 0.6, p < 0.03) and suture task (d = 0.9, p < 0.02) (judges' intraclass correlation coefficient = 0.85); and 2) with overall time on task (d = 0.5, p = 0.02), while everyday anxiety (trait) decreased (d = 0.5, p < 0.02). Importantly the decrease in surgical task time was strongly associated with SMR EEG training changes (p < 0.01), especially with continued reduction of theta (4–7 Hz) power. AT training produced marginal improvements in technique and overall performance time, which were accompanied by a standard error indicative of large individual differences. Notwithstanding, successful within session elevation of the theta-alpha ratio correlated positively with improvements in overall technique (r = 0.64, p = 0.047). Conclusion: SMR-Theta neurofeedback training provided significant improvement in surgical technique whilst considerably reducing time on task by 26%. There was also evidence that AT training marginally reduced total surgery time, despite suboptimal training efficacies. Overall, the data set provides encouraging evidence of optimised learning of a complex medical specialty via neurofeedback training.

Nonlinearity in Deviations from Uncovered Interest Parity: An Explanation of the Forward Bias Puzzle

Abstract: We provide empirical evidence that deviations from the uncovered interest rate parity (UIP) condition display significant nonlinearities, consistent with theories based on transactions costs or limits to speculation. This evidence suggests that the forward bias documented in the literature may be less indicative of major market inefficiencies than previously thought. Monte Carlo experiments allow us to reconcile these results with the large empirical literature on the forward bias puzzle since we show that, if the true process of UIP deviations were of the nonlinear form we consider, estimation of conventional spot-forward regressions would generate the anomalies documented in previous research.

Estimating the costs of school closure for mitigating an influenza pandemic

Abstract: School closure is a key component of many countries' plans to mitigate the effect of an influenza pandemic. Although a number of studies have suggested that such a policy might reduce the incidence, there are no published studies of the cost of such policies. This study attempts to fill this knowledge gap School closure is expected to lead to significant work absenteeism of working parents who are likely to be the main care givers to their dependent children at home. The cost of absenteeism due to school closure is calculated as the paid productivity loss of parental absenteeism during the period of school closure. The cost is estimated from societal perspective using a nationally representative survey. The results show that overall about 16% of the workforce is likely to be the main caregiver for dependent children and therefore likely to take absenteeism. This rises to 30% in the health and social care sector, as a large proportion of the workforce are women. The estimated costs of school closure are significant, at £0.2 bn – £1.2 bn per week. School closure is likely to significantly exacerbate the pressures on the health system through staff absenteeism. The estimates of school closure associated absenteeism and the projected cost would be useful for pandemic planning for business continuity, and for cost effectiveness evaluation of different pandemic influenza mitigation strategies.