An Implementation of a Decision Support Tool to Assess Treatment of Emerging Contaminants in India

This is the final version. Available on open access from Scientific Research Publishing via the DOI in this recordEmerging contaminants have been increasingly studied over the past decade to improve the understanding of their fate, occurrence and toxicological effects on the environment and human health. Originally wastewater treatment plants were not designed to remove these pollutants of emerging concern. However, research is now focusing on determining which existing treatment unit processes are suited to their removal. This research sets out to determine suitable treatment options for thirty nine emerging contaminants including various Pharmaceuticals and Personal Care products. The treatment options used in this study are taken from a developed decision support tool (WiSDOM) which formulates wastewater trains/packages for treatment of wastewater in India. The tool also evaluates the performance of each optimal solution in terms of removal of conventional pollutants (such as biochemical oxygen demand, chemical oxygen demand, total nitrogen, total phosphorous, faecal coliform etc.), using multi-objective genetic algorithms and multi-criteria decision analysis. An Excel Spreadsheet Program (ESP) was developed as an add-on to the tool, allowing the ESP to take an initial concentration of any of the thirty nine emerging contaminant and pass it through the treatment trains (generated/selected by the WiSDOM tool) to determine the removal efficiency. Three scenarios were developed to analyse the removal of emerging contaminants in India. The scenarios were designed to capture the influence of different socio-economic contexts and wastewater characteristics on the treatment technology selection. The tool generated results suggest that the use of constructed wetlands can remove a large proportion of emerging contaminants, resulting in low energy requirements and operational costs and wildlife habitats. However, the land requirement for this process is not always suited to urban areas in India. Advanced oxidation processes were also efficient at removing emerging contaminants. However, the energy requirements for this process were high. Emerging contaminants have different physical and chemical properties; therefore, future evaluations of each chemical should be monitored separately to generate suitable technologies suited to optimal removal.Engineering and Physical Sciences Research Council (EPSRC)European CommissionNatural Environment Research Council (NERC

Liquid crystal droplets under extreme confinement probed by a multiscale simulation approach

In this work, we computationally investigate liquid crystal (LC) droplets in the size range 0.03–1 μm, confined within shells of combined anchoring conditions. Two different types of surface were defined to promote homeotropic and planar degenerate anchoring, respectively. We identified the LC behaviour within the nanoscale droplets using a bespoke multiscale simulation approach. To study 30 nm droplets, we used coarse grained simulations within the dissipative particle dynamics formalism; to study 0.1 μm and larger droplets, we used a finite element method based on the Landau–de Gennes theory. Good agreement between the two methods was observed in our prior analysis and was confirmed in the present work. We explicitly study droplets of size 0.1 and 1 μm by using continuum mechanics calculations. Our results for the largest droplet are consistent with those available in the literature, suggesting that the extension to smaller droplets presented here is realistic, and therefore can be helpful for innovations in which device intensification could be achieved using LC nanodroplets

Engineered liquid crystal nano droplets: insights from multi-scale simulations

Liquid crystal (LC) droplets have been investigated for a wide range of applications, from displays to sensors. Over the years, a need has arisen for complete understanding of the behaviour of LCs in droplets under different conditions for the development of advanced devices, for which accurate modelling is necessary. We show here, for the first time, both qualitative and quantitative agreement between coarse-grained molecular models and Q-tensor theory calculations for liquid crystal (LC) droplets. The approach is demonstrated for two types of droplet surfaces, which possess strong planar degenerate and strong homeotropic anchoring, respectively. Once its reliability has been proven, our approach was used to identify defects due to changes in anchoring in a small region on the LC droplet surface, which could be triggered, for example, by the adsorption of a nano-particle or a protein. Both coarse-grained simulations and Q-tensor analysis show the appearance of defects in well-determined locations within the LC droplet, albeit sometimes affected by degeneracy due to the symmetry of the systems being investigated. These results suggest the possibility of using LC droplets, in the future, as platforms for advanced sensing as well as for signal intensification

Evaluation of Heavy Metal Concentrations in Surface and Ground Water Collected from River Challawa, Kumbotso Tannery Dumpsite and their Vicinity, Kano State, Nigeria.

A study was conducted to determine the concentration of heavy metals in surface and ground water collected from river Challawa and Kumbotso tannery dumpsite. The samples were analyzed for the levels of Co, Ni, Pb, Cr, Cu, Cd, Zn, and Fe using Atomic Absorption Spectroscopy (AAS). The result showed that all the metals exceeded the standard limit in the water. The estimated metal levels in the water were compared with the safe limits laid down by the World Health Organization (WHO).Keywords: AAS, Challawa Industrial Area Effluents, Heavy Metals, Tanner

History Matching with Subset Simulation

Computational cost often hinders the calibration of complex computer models. In this context, history matching (HM) is becoming a widespread calibration strategy, with applications in many disciplines. HM uses a statistical approximation, also known as an emulator, to the model output, in order to mitigate computational cost. The process starts with an observation of a physical system. It then produces progressively more accurate emulators to determine a non-implausible domain: a subset of the input space that provides a good agreement between the model output and the data, conditional on the model structure, the sources of uncertainty, and an implausibility measure. In HM, it is essential to generate samples from the nonimplausible domain, in order to run the model and train the emulator until a stopping condition is met. However, this sampling can be very challenging, since the nonimplausible domain can become orders of magnitude smaller than the original input space very quickly. This paper proposes a solution to this problem using subset simulation, a rare event sampling technique that works efficiently in high dimensions. The proposed approach is demonstrated via calibration and robust design examples from the field of aerospace engineering

International diversification with factor funds

We propose a new investment strategy employing "factor funds" to systematically enhance the meanvariance efficiency of international diversification. Our approach is motivated by the increasing evidence that size (SMB), book-to-market (HML), and momentum (MOM) factors, along with the market factor, adequately describe international stock returns, and by the direct link between investors' portfolio choice problems and international asset pricing theories and tests. Using data from 10 developed countries during the period 1981-2008, we show that the "augmented" optimal portfolio involving local factor funds substantially outperforms the "benchmark" optimal portfolio comprising country market indices only as measured by their portfolio Sharpe ratios. This strongly rejects the intersection hypothesis which posits that the local factor funds do not span investment opportunities beyond what country market indices do. Among the three classes of factor funds, HML funds contribute most to the efficiency gains. In addition, the local version of factor funds outperforms the global factor funds. The added gains from local factor diversification are significant for both in-sample and out-of-sample periods, and for a realistic range of additional investment costs for factor funds, and remain robust over time. Copyright © 2010 INFORMS.preprin

Dual Identities inside the Gluon and the Graviton Scattering Amplitudes

Recently, Bern, Carrasco and Johansson conjectured dual identities inside the gluon tree scattering amplitudes. In this paper, we use the properties of the heterotic string and open string tree scattering amplitudes to refine and derive these dual identities. These identities can be carried over to loop amplitudes using the unitarity method. Furthermore, given the $M$-gluon (as well as gluon-gluino) tree amplitudes, $M$-graviton (as well as graviton-gravitino) tree scattering amplitudes can be written down immediately, avoiding the derivation of Feynman rules and the evaluation of Feynman diagrams for graviton scattering amplitudes.Comment: 43 pages, 3 figures; typos corrected, a few points clarified

3D Modelling of Twist Wall at the Electrode Edge of Liquid Crystal Cells

Q-tensor simulation of the liquid crystal structure at the edge of electrodes has been carried out. The modeling shows a twist wall, which reverses direction to form a zig-zag structure. The results are compared with experiment. Also a defect loop is found in micro-lenses formed using a hole electrode structure