We demonstrate that it is possible to derive an approximate analytical expression to characterize the spasing (L-L) curve of a coherently enhanced spaser with 3-level gain-medium chromophores. The utility of this solution stems from the fact that it enables optimization of the large parameter space associated with spaser designing, a functionality not offered by the methods currently available in the literature. This is vital for the advancement of spaser technology towards the level of device realization. Owing to the compact nature of the analytical expressions, our solution also facilitates the grouping and identification of key processes responsible for the spasing action, whilst providing significant physical insights. Furthermore, we show that our expression generates results within 0.1% error compared to numerically obtained results for pumping rates higher than the spasing threshold, thereby drastically reducing the computational cost associated with spaser designing. Published by AIP Publishing. https://doi.

The maintenance and renewal of water mains demand substantial financial investments, and direct inspection of all water mains in a distribution system is extremely expensive. Therefore, a cost effective break mitigation technique such as a failure forecasting model that allows one to predict the water mains failure likelihood, would reduce the negative social impact and the cost to serve. We introduce a semiparametric Bayesian model for pipeline failure forecasting. The model is centred on a nonparametric Gaussian Process Regression (GPR), and uses a parametric survival model to capture the long-term survival probability using domain knowledge. The parametric element in our model allows the inclusion of survival probability, while the nonparametric part allows us to handle covariates and to employ incomplete prior knowledge about pipe failures. We apply our model to the proactive maintenance problem using a real dataset from a water utility in Australia. The results demonstrate that, our model performs better than competing models such as Support Vector Regression, Poisson regression, Weibull, Gradient Boosting, and GPR, leading to substantial savings on reactive repairs and maintenance. Our water pipeline failure prediction models have been deployed in three states across Australia, and are being monitored by each water authority.

Since the 1960s, the world has witnessed the rise of several East Asian nations as economic powerhouses. One of the main contributing factors of their success is their decision to create policies that allowed them to enter high-tech global production networks. Today, other countries are attempting to do the same by replicating the success of these East Asian nations, but they have had considerably less success. Thus, a study that investigates the drivers of developing countries entering global production networks would be of great use to policymakers in other countries. Hence, with the support of evidence from Vietnam, Malaysia, and Taiwan, this study proposes policy options (government support, science parks, tax, and other incentives, high- and semi-skilled labor, infrastructure development roadmaps, and free trade agreements) that are necessary to initiate and drive the entrance of a developing country into high-tech global production networks. Government support was identified as the main driver that determines the outcome of an effort to enter. Infrastructure development roadmap and free trade agreements were identified as optional. However, it is recommended that governments consider the two optional factors during policy formation, as they could complement the other factors.