Abstract: In this article we quantify the effect of uncertainty of climate and environmental policies on transmission and generation investments, as well as on CO2 emissions in Chile. We use a two-stage stochastic planning model with recourse or corrective investment options to find optimal portfolios of infrastructure both under perfect information and uncertainty. Under a series of assumptions, this model is equivalent to the equilibrium of a much more complicated bi-level market model, where a transmission planner chooses investments first and generation firms invest afterwards. We find that optimal investment strategies present important differences depending on the policy scenario. By changing our assumption of how agents will react to this uncertainty we compute bounds on the cost that this uncertainty imposes on the system, which we estimate ranges between 3.2% and 5.7% of the minimum expected system cost of $57.6B depending on whether agents will consider or not uncertainty when choosing investments. We also find that, if agents choose investments using a stochastic planning model, uncertain climate policies can result in nearly 18% more CO2 emissions than the equilibrium levels observed under perfect information. Our results highlight the importance of credible and stable long-term regulations for investors in the electric power industry if the goal is to achieve climate and environmental targets in the most cost-effective manner and to minimize the risk of asset stranding. (C) 2018 Elsevier B.V. All rights reserved.

Abstract: Human performance enhancing drugs (PEDs), frequently used in sport competitions, are strictly prohibited by the World Anti-Doping Agency (WADA). Biological samples collected from ath-letes and regular patients are continuously tested regarding the identification and/or quantification of the banned substances. Current work is focused on the application of a new analytical method, molecularly imprinted nanoparticles (nanoMIPs), to detect and determine concentrations of certain prohibited drugs, such as B-blockers, in water and human urine samples. These medications are used in the treatment of cardiovascular conditions, negative effects of adrenaline (helping to relief stress), and hypertension (slowing down the pulse and softening the arteries). They can also significantly increase muscle relaxation and improve heart efficiency. The new method of the detection and quantification of B-blockers is based on synthesis, characterization, and implementation of nanoMIPs (so-called plastic antibodies). It offers numerous advantages over the traditional methods, including high binding capacity, affinity, and selectivity for target molecules. Additionally, the whole process is less complicated, cheaper, and better controlled. The size and shape of the nanoMIPs is evaluated by dynamic light scattering (DLS) and transmission electron microscope (TEM). The affinity and selectivity of the nanoparticles are investigated by competitive pseudo enzyme-linked immunosorbent assay (pseudo-ELISA) similar to common immunoassays employing natural antibodies. To provide reliable results towards either doping detection or therapeutic monitoring using the minimal invasive method, the qualitative and quantitative analysis of these drugs is performed in water and human urine samples. It is demonstrated that the assay can detect B-blockers in water within the linear range 1 nmolmiddotL(-1)-1 mmolmiddotL(-1) for atenolol with the detection limit 50.6 ng mL(-1), and the linear range 1 mmolmiddotL(-1)-10 mmolmiddotL(-1) for labetalol with the detection limit of 90.5 ngmiddotmL(-1). In human urine samples, the linear range is recorded in the concentration range 0.1 mmolmiddotL(-1)-10 nmolmiddotL(-1) for atenolol and 1 mmolmiddotL(-1)-10 nmolmiddotL(-1) for labetalol with a detection limit of 61.0 ngmiddotmL(-1)for atenolol and 99.4 ngmiddotmL(-1) for labetalol.

Abstract: This paper investigates the role of fast-acting energy storage systems in transmission expansion planning, by allowing higher transfers through the network during normal operation. This is achieved by considering the ability of energy storage systems to provide real and reactive power reserves after forced single-circuit outages to prevent line overloading and voltage level violations in post-contingency states, and by applying the corrective N – 1 security criterion. A computational tool is presented to solve the multi-year transmission expansion problem with multiple scenarios of availability of renewable energy sources. The model is solved using the FICO Xpress software. The 2022-2037 Chilean transmission expansion plan is used as a case study, given the high need for flexibility to integrate 29.5 GW of new solar and wind generation capacity several hundred kilometers from its load center, with a system peak demand of 16.5 GW. The results obtained show that fast-acting energy storage systems reduce the cost of the investment plan by USD 712 million (-18%) mainly because it requires 5 GWh less of conventional storage capacity (-19%), allowing the system operator to increase the usage of the existing transmission network, and providing the central planner with a deferral option for the construction of new transmission lines.

Abstract: We present a novel computational scheme to solve acoustic wave transmission problems over two-dimensional composite scatterers, i.e. penetrable obstacles possessing junctions or triple points. The continuous problem is cast as a local multiple traces time-domain boundary integral formulation. For discretization in time and space, we resort to convolution quadrature schemes coupled to a non-conforming spatial spectral discretization based on second kind Chebyshev polynomials displaying fast convergence. Computational experiments confirm convergence of multistep and multistage convolution quadrature for a variety of complex domains.

Abstract: Studies of exoplanetary atmospheres have found no definite correlations between observed high-altitude aerosols and other system parameters. This could be, in part, because of the lack of homogeneous exoplanet samples for which specific parameters can be isolated and inspected. Here, we present a set of seven exoplanets with very similar system parameters. We analyze existing photometric time series, Gaia parallax, and high-resolution spectroscopic data to produce a new set of homogeneous stellar, planetary, and orbital parameters for these systems. With this, we confirm that most measured parameters for all systems are very similar, except for the host stars' metallicities and possibly high-energy irradiation levels, which require UV and X-ray observations to constrain. From the sample, WASP-6b, WASP-96b, and WASP-110b have observed transmission spectra that we use to estimate their aerosol coverage levels using the Na i doublet 5892.9 angstrom. We find a tentative correlation between the metallicity of the host stars and the planetary aerosol levels. The trend we find with stellar metallicity can be tested by observing transmission spectra of the remaining planets in the sample. Based on our prediction, WASP-25b and WASP-55b should have higher levels of aerosols than WASP-124b and HATS-29b. Finally, we highlight how targeted surveys of alike planets similar to the ones presented here might prove key for identifying driving factors for atmospheric properties of exoplanets in the future and could be used as a sample selection criterion for future observations with, e.g., JWST, ARIEL, and the next generation of ground-based telescopes.

Abstract: We investigate the effects of risk aversion on optimal transmission and generation expansion planning in a competitive and complete market. To do so, we formulate a stochastic model that minimizes a weighted average of expected transmission and generation costs and their conditional value at risk (CVaR). We show that the solution of this optimization problem is equivalent to the solution of a perfectly competitive risk averse Stackelberg equilibrium, in which a risk-averse transmission planner maximizes welfare after which risk-averse generators maximize profits. This model is then applied to a 240-bus representation of the Western Electricity Coordinating Council, in which we examine the impact of risk aversion on levels and spatial patterns of generation and transmission investment. Although the impact of risk aversion remains small at an aggregate level, state-level impacts on generation and transmission investment can be significant, which emphasizes the importance of explicit consideration of risk aversion in planning models. (C) 2017 Elsevier B.V. All rights reserved.

Abstract: Transparent conducting materials (TCMs) are the heart of modern optoelectronic industries and the properties of TCMs could be improved by the introduction of 2D carbon materials. In this report, the influence of order layering on microstructural, transparency and emission characteristics of ZnO:rGO:ZnO:rGO:ZnO and rGO:ZnO: rGO:ZnO:rGO sandwich structures has been investigated. The layer-by-layer approach has been adopted for the fabrication of sandwich structured materials ZnO:rGO:ZnO:rGO:ZnO and rGO:ZnO:rGO:ZnO:rGO through the spin coating technique. The sandwich structures of ZnO and rGO exhibited hexagonal wurtzite structure of ZnO without any impurities were identified through XRD. The ordering of layer's influenced the microstructural parameters and were significantly altered. The spherical nature of the particles and the formation of the sand-wich structures were confirmed by using SEM micrograph. The reduction in an optical transparency and nar-rowing bandgap of the ZnO upon the order of layering were identified through transmission spectra. The lower energy shift of near band edge (NBE) emission and reduction in the emission intensity with respect to pure ZnO nanostructures was observed. The present work provides a simple layer-by-layer approach to fabricating sand-wich structures and improving the optical properties which have potential applications in various optoelectronic devices.

Abstract: When resources are limited, measures to control an incipient influenza pandemic must be carefully considered. Because several months are needed to mass-produce vaccines once a new pandemic strain has been identified, antiviral drugs are often considered the first line of defense in a pandemic situation. Here we use an SIR disease model with periodic transmission rate to assess the efficacy of control strategies via antiviral drug treatment during an outbreak of pandemic influenza. We show that in some situations, and independent of drug-resistance effects, antiviral treatment can have a detrimental impact on the final size of the pandemic. Antiviral treatment also has the potential to increase the size of the major peak of the pandemic, and cause it to occur earlier than it would have if treatment were not used. Our studies suggest that when a disease exhibits periodic patterns in transmission, decisions of public health policy will be particularly important as to how control measures such as drug treatment should be implemented, and to what end (i.e.; towards immediate control of a current epidemic peak, or towards potential delay and/or reduction of an anticipated autumn peak). (C) 2011 Elsevier Ltd. All rights reserved.