
Reus, L., Pincheira, P., & Carrasco, J. A. (2020). Do it with a Smile: Forecasting Volatility of Currency Options. Fin. Res. Let., to appear.
Abstract: We show that traditional measures of curvature and symmetry of the “smiles” improve volatility predictions in forex markets. We consider post crisis data at a daily basis for seven currencies vis a vis the American dollar: the British pound, the Euro, the Australian dollar, the Japanese yen, the Brazilian real and the Mexican and Chilean peso. While our results are robust to the option currency and maturity, they are particularly strong for latinamerican currencies and options with longer maturity. We find that the simultaneous inclusion of skewness and kurtosis to a forecasting model significantly improves its predictive accuracy.



ArayaLetelier, G., Maturana, P., Carrasco, M., Antico, F. C., & Gomez, M. S. (2019). MechanicalDamage Behavior of Mortars Reinforced with Recycled Polypropylene Fibers. Sustainability, 11(8), 17 pp.
Abstract: Commercial polypropylene fibers are incorporated as reinforcement of cementbased materials to improve their mechanical and damage performances related to properties such as tensile and flexural strength, toughness, spalling and impact resistance, delay formation of cracks and reducing crack widths. Yet, the production of these polypropylene fibers generates economic costs and environmental impacts and, therefore, the use of alternative and more sustainable fibers has become more popular in the research materials community. This paper addresses the characterization of recycled polypropylene fibers (RPFs) obtained from discarded domestic plastic sweeps, whose morphological, physical and mechanical properties are provided in order to assess their implementation as fiberreinforcement in cementbased mortars. An experimental program addressing the incorporation of RPFs on the mechanicaldamage performance of mortars, including a sensitivity analysis on the volumes and lengths of fiber, is developed. Using analysis of variance, this paper shows that RPFs statistically enhance flexural toughness and impact strength for high dosages and long fiber lengths. On the contrary, the latter properties are not statistically modified by the incorporation of low dosages and short lengths of RPFs, but still in these cases the incorporation of RPFs in mortars have the positive environmental impact of waste encapsulation. In the case of average compressive and flexural strength of mortars, these properties are not statistically modified when adding RPFs.



Navarro, H., Marco, L. M., Araneda, A. A., & Bennun, L. (2019). Spatial distribution of Si in Pinus Insigne (Pinus radiata) Wood using micro XRF by Synchrotron Radiation. J. Wood Chem. Technol., 39(3), 187–198.
Abstract: Silicon, while not an essential element, is known to have positive roles in certain vegetable species. For instance, it has been recognized to protect them from biotic and abiotic stress. Due to the fact that certain species accumulate the aforementioned element in their tissues, the determination of its concentration is of importance in different disciplines, such as dendrology, plant physiology, forest management, agroecology, and also in the wood industry. Usually, its quantification is preceded by a series of digestion steps that, aside from been timeconsuming, and contaminationprone, prevents from conducting a spatial distribution of the element on the sample. In this research, samples of Pinus radiata wood were studied using a synchrotron radiation source that allowed direct scanning of its surface without any treatment, and the determination of silicon as a function of the position and the tree rings, using micro Xray fluorescence (mu XRF). A quantification method based in the fundamental parameters approach was evaluated. It was found that silicon concentration increases near the latewood ring zones, showing a periodical behavior, related to seasonal environmental events.



Asenjo, F. A., & Mahajan, S. M. (2019). Diamagnetic field states in cosmological plasmas. Phys. Rev. E, 99(5), 7 pp.
Abstract: Using a generally covariant electrovortic (magnetofluid) formalism for relativistic plasmas, the dynamical evolution of a generalized vorticity (a combination of the magnetic and kinematic parts) is studied in a cosmological context. We derive macroscopic vorticity and magnetic field structures that can emerge in spatial equilibrium configurations of the relativistic plasma. These fields, however, evolve in time. These magnetic and velocity fields, selfconsistently sustained in a plasma with arbitrary thermodynamics, constitute a diamagnetic state in the expanding universe. In particular, we explore a special class of magnetic and velocity field structures supported by a plasma in which the generalized vorticity vanishes. We derive a highly interesting characteristic of such “superconductorlike” fields in a cosmological plasmas in the radiation era in the early universe. In that case, the fields grow proportional to the scale factor, establishing a deep connection between the expanding universe and the primordial magnetic fields.



VeraDamian, Y., Vidal, C., & GonzalezOlivares, E. (2019). Dynamics and bifurcations of a modified LeslieGowertype model considering a BeddingtonDeAngelis functional response. Math. Meth. Appl. Sci., 42(9), 3179–3210.
Abstract: In this paper, a planar system of ordinary differential equations is considered, which is a modified LeslieGower model, considering a BeddingtonDeAngelis functional response. It generates a complex dynamics of the predatorprey interactions according to the associated parameters. From the system obtained, we characterize all the equilibria and its local behavior, and the existence of a trapping set is proved. We describe different types of bifurcations (such as Hopf, BogdanovTakens, and homoclinic bifurcation), and the existence of limit cycles is shown. Analytic proofs are provided for all results. Ecological implications and a set of numerical simulations supporting the mathematical results are also presented.



Bravo, M., Cominetti, R., & PavezSigne, M. (2019). Rates of convergence for inexact Krasnosel'skiiMann iterations in Banach spaces. Math. Program., 175(12), 241–262.
Abstract: We study the convergence of an inexact version of the classical Krasnosel'skiiMann iteration for computing fixed points of nonexpansive maps. Our main result establishes a new metric bound for the fixedpoint residuals, from which we derive their rate of convergence as well as the convergence of the iterates towards a fixed point. The results are applied to three variants of the basic iteration: infeasible iterations with approximate projections, the Ishikawa iteration, and diagonal Krasnosels'kiiMann schemes. The results are also extended to continuous time in order to study the asymptotics of nonautonomous evolution equations governed by nonexpansive operators.



Canessa, G., Gallego, J. A., Ntaimo, L., & Pagnoncelli, B. K. (2019). An algorithm for binary linear chanceconstrained problems using IIS. Comput. Optim. Appl., 72(3), 589–608.
Abstract: We propose an algorithm based on infeasible irreducible subsystems to solve binary linear chanceconstrained problems with random technology matrix. By leveraging on the problem structure we are able to generate good quality upper bounds to the optimal value early in the algorithm, and the discrete domain is used to guide us efficiently in the search of solutions. We apply our methodology to individual and joint binary linear chanceconstrained problems, demonstrating the ability of our approach to solve those problems. Extensive numerical experiments show that, in some cases, the number of nodes explored by our algorithm is drastically reduced when compared to a commercial solver.



Agostini, C. A., Guzman, A. M., Nasirov, S., & Silva, C. (2019). A surplus based framework for crossborder electricity trade in South America. Energy Policy, 128, 673–684.
Abstract: The South American region has experienced a steady increase in its demand for electricity and faces several challenges in the development of the electricity sector. Among them, high fluctuations in hydro generation, high and volatile prices of fossil fuels, and environmental and social impacts associated to energy activities. Strengthening cooperation for crossborder electricity trade is considered a sustainable alternative for addressing these challenges. For the expansion of electricity trade among countries within the region, both infrastructure and a regulation that defines the conditions of the electric power exchanges between countries are required. A good regulatory framework would allow all market players to have access to the commercialization of energy with other countries in the region, guarantee that the treatment of exchanges is nondiscriminatory, and maintain the efficiency, cost effectiveness and security characteristics operation of all electricity systems. In this context, this paper proposes a framework with the basic setting conditions for the import and export of energy from the “surplus” available for exchange. The empirical analysis of the regulatory proposal, based on simulations, shows that the exchange of energy from Chile with its neighboring countries is feasible in a clear and transparent manner, reducing the marginal costs of energy and the total cost of operation, keeping the average cost of generation relatively constant.



ArayaLetelier, G., Parra, P. F., LopezGarcia, D., GarciaValdes, A., Candia, G., & Lagos, R. (2019). Collapse risk assessment of a Chilean dual wallframe reinforced concrete office building. Eng. Struct., 183, 770–779.
Abstract: Several codeconforming reinforced concrete buildings were severely damaged during the 2010 moment magnitude (Mw) 8.8 Chile earthquake, raising concerns about their real collapse margin. Although critical updates were introduced into the Chilean design codes after 2010, guidelines for collapse risk assessment of Chilean buildings remain insufficient. This study evaluates the collapse potential of a typical dual system (shear walls and moment frames) office building in Santiago. Collapse fragility functions were obtained through incremental dynamic analyses using a stateoftheart finite element model of the building. Sitespecific seismic hazard curves were developed, which explicitly incorporated epistemic uncertainty, and combined with the collapse fragility functions to estimate the mean annual frequency of collapse (lambda(c)) values and probabilities of collapse in 50years (Pc(50)). Computed values of lambda(c) and Pc(50) were on the order of 10(5)10(4), and 0.10.7%, respectively, consistent with similar studies developed for buildings in the US. The results also showed that the deaggregation of lambda(c) was controlled by small to medium earthquake intensities and that different models of the collapse fragility functions and hazard curves had a nonnegligible effect on lambda(c) and Pc(50), and thus, propagation of uncertainty in risk assessment problems must be adequately taken into account.



Asenjo, F. A., & Comisso, L. (2019). Gravitational electromotive force in magnetic reconnection around Schwarzschild black holes. Phys. Rev. D, 99(6), 7 pp.
Abstract: We analytically explore the effects of the gravitational electromotive force on magnetic reconnection around Schwarzschild black holes through a generalized generalrelativistic magnetohydrodynamic model that retains twofluid effects. It is shown that the gravitational electromotive force can couple to collisionless twofluid effects and drive magnetic reconnection. This is allowed by the departure from quasineutrality in curved spacetime, which is explicitly manifested as the emergence of an effective resistivity in Ohm's law. The departure from quasineutrality is owed to different gravitational pulls experienced by separate parts of the current layer. This produces an enhancement of the reconnecion rate due to purely gravitational effects.



Simon, F., Ordonez, J., Girard, A., & Parrado, C. (2019). Modelling energy use in residential buildings: How design decisions influence final energy performance in various Chilean climates. Indoor Built Environ., 28(4), 533–551.
Abstract: To reduce the energy consumption in buildings, there is a demand for tools that identify significant parameters of energy performance. The work presents the development and validation of a simulation model, called MEEDI, and graphical figures for the parametric sensitivity investigation of energy performance in different climates in Chile. The MEEDI is based on the ISO 13790 monthly calculation method of building energy use with two improved procedures for the calculation of the heat transfer through the floor and the solar heat gains. The graphical figures illustrate the effects of climate conditions, envelope components and window size and orientation on the energy consumption. The MEEDI program can contribute to find the best solution to increase energy efficiency in residential buildings. It can be adapted for various parameters, making it useful for future projects. The economic viability of specific measures for building envelope materials was analysed. Payback periods range from 5 to 27 years depending on the location and energy scenario. The study illustrates how building design decisions can have a significant impact on final energy performance. With simple envelope components modification, valuable energy gains and carbon emission reductions can be achieved in a costeffective manner in Chile.



Rojas, E. R., & Dumais, J. (2019). A Mechanical Cusp Catastrophe Imposes a Universal Developmental Constraint on the Shapes of TipGrowing Cells. In Biophysical Journal (Vol. 116, p. 121A). Cell Press.



Liedloff, M., Montealegre, P., & Todinca, I. (2019). Beyond Classes of Graphs with “Few” Minimal Separators: FPT Results Through Potential Maximal Cliques. Algorithmica, 81(3), 986–1005.
Abstract: Let P(G,X) be a property associating a boolean value to each pair (G,X) where G is a graph and X is a vertex subset. Assume that P is expressible in counting monadic second order logic (CMSO) and let t be an integer constant. We consider the following optimization problem: given an input graph G=(V,E), find subsets XFV such that the treewidth of G[F] is at most t, property P(G[F],X) is true and X is of maximum size under these conditions. The problem generalizes many classical algorithmic questions, e.g., Longest Induced Path, Maximum Induced Forest, IndependentHPacking, etc. Fomin et al. (SIAM J Comput 44(1):5487, 2015) proved that the problem is polynomial on the class of graph Gpoly, i.e. the graphs having at most poly(n) minimal separators for some polynomial poly. Here we consider the class Gpoly+kv, formed by graphs of Gpoly to which we add a set of at most k vertices with arbitrary adjacencies, called modulator. We prove that the generic optimization problem is fixed parameter tractable on Gpoly+kv, with parameter k, if the modulator is also part of the input.



RamirezSagner, G., & Munoz, F. D. (2019). The effect of headsensitive hydropower approximations on investments and operations in planning models for policy analysis. Renew. Sust. Energ. Rev., 105, 38–47.
Abstract: Planning for new generation infrastructure in hydrothermal power systems requires consideration of a series of nonlinearities that are often ignored in planning models for policy analysis. In this article, three different capacity planning models are used, one nonlinear and two linear ones, with different degrees of complexity, to quantify the impact of simplifying the head dependency of hydropower generation on investments in both conventional and renewable generators and system operations. It was found that simplified investment models can bias the optimal generation portfolios by, for example, understating the need for coal and combinedcycle gas units and overstating investments in wind capacity with respect to a more accurate nonlinear formulation, which could affect policy recommendations. It was also found that the economic cost of employing a simplified model can be below 10% of total system cost for most of the scenarios and system configurations analyzed, but as high as nearly 70% of total system cost for specific applications. Although these results are not general, they suggest that for certain system configurations both linear models can provide reasonable approximations to more complex nonlinear formulations. Uncertain water inflows were also considered using stochastic variants of all three planning models. Interestingly, if due to time or computational limitations only one of these two features could be accounted for, these results indicate that explicit modeling of the nonlinearhead effect in a deterministic model could yield better results (up to 0.6% of economic regret) than a stochastic linear model (up to 9.6% of economic regret) that considers the uncertainty of water inflows.



Cominetti, R., Roshchina, V., & Williamson, A. (2019). A counterexample to De Pierro's conjecture on the convergence of underrelaxed cyclic projections. Optimization, 68(1), 3–12.
Abstract: The convex feasibility problem consists in finding a point in the intersection of a finite family of closed convex sets. When the intersection is empty, a best compromise is to search for a point that minimizes the sum of the squared distances to the sets. In 2001, de Pierro conjectured that the limit cycles generated by the underrelaxed cyclic projection method converge when towards a least squares solution. While the conjecture has been confirmed under fairly general conditions, we show that it is false in general by constructing a system of three compact convex sets in for which the underrelaxed cycles do not converge.



Cabrera, F., Torres, A., Campos, J. L., & Jeison, D. (2019). Effect of Operational Conditions on the Behaviour and Associated Costs of Mixed Microbial Cultures for PHA Production. Polymers, 11(2), 14 pp.
Abstract: Massive production and disposal of petrochemical derived plastics represent relevant environmental problems. Polyhydroxyalkanoates (PHA) are a renewable alternative that can even be produced from wastes. The production of PHA from acetate using mixed microbial cultures was studied. The effect of two key operational conditions was evaluated, i.e., substrate concentration and cycle length. The effects of these factors on several responses were studied using a surface response methodology. Several reactors were operated under selected conditions for at least 10 solids retention times to ensure stable operation. Results show that conditions providing higher PHA content involve lower biomass productivities. This has a great impact on biomass production costs. Results suggest then that PHA content alone may not be a reasonable criterion for determining optimal conditions for PHB production. If production costs need to be reduced, conditions that provide a lower PHA content in the selection reactor, but a higher biomass productivity may be of interest.



RamirezFlandes, S., Gonzalez, B., & Ulloa, O. (2019). Redox traits characterize the organization of global microbial communities. Proc. Natl. Acad. Sci. U. S. A., 116(9), 3630–3635.
Abstract: The structure of biological communities is conventionally described as profiles of taxonomic units, whose ecological functions are assumed to be known or, at least, predictable. In environmental microbiology, however, the functions of a majority of microorganisms are unknown and expected to be highly dynamic and collectively redundant, obscuring the link between taxonomic structure and ecosystem functioning. Although genetic traitbased approaches at the community level might overcome this problem, no obvious choice of gene categories can be identified as appropriate descriptive units in a general ecological context. We used 247 microbial metagenomes from 18 biomes to determine which set of genes better characterizes the differences among biomes on the global scale. We show that profiles of oxidoreductase genes support the highest biome differentiation compared with profiles of other categories of enzymes, general proteincoding genes, transporter genes, and taxonomic gene markers. Based on oxidoreductases' description of microbial communities, the role of energetics in differentiation and particular ecosystem function of different biomes become readily apparent. We also show that taxonomic diversity is decoupled from functional diversity, e. g., grasslands and rhizospheres were the most diverse biomes in oxidoreductases but not in taxonomy. Considering that microbes underpin biogeochemical processes and nutrient recycling through oxidoreductases, this functional diversity should be relevant for a better understanding of the stability and conservation of biomes. Consequently, this approach might help to quantify the impact of environmental stressors on microbial ecosystems in the context of the globalscale biome crisis that our planet currently faces.



Henriquez, P. A., & Ruz, G. A. (2019). Noise reduction for nearinfrared spectroscopy data using extreme learning machines. Eng. Appl. Artif. Intell., 79, 13–22.
Abstract: The near infrared (NIR) spectra technique is an effective approach to predict chemical properties and it is typically applied in petrochemical, agricultural, medical, and environmental sectors. NIR spectra are usually of very high dimensions and contain huge amounts of information. Most of the information is irrelevant to the target problem and some is simply noise. Thus, it is not an easy task to discover the relationship between NIR spectra and the predictive variable. However, this kind of regression analysis is one of the main topics of machine learning. Thus machine learning techniques play a key role in NIR based analytical approaches. Preprocessing of NIR spectral data has become an integral part of chemometrics modeling. The objective of the preprocessing is to remove physical phenomena (noise) in the spectra in order to improve the regression or classification model. In this work, we propose to reduce the noise using extreme learning machines which have shown good predictive performances in regression applications as well as in large dataset classification tasks. For this, we use a novel algorithm called CPLELM, which has an architecture in parallel based on a nonlinear layer in parallel with another nonlinear layer. Using the soft margin loss function concept, we incorporate two Lagrange multipliers with the objective of including the noise of spectral data. Six reallife dataset were analyzed to illustrate the performance of the developed models. The results for regression and classification problems confirm the advantages of using the proposed method in terms of root mean square error and accuracy.



MacLean, S., MontalvaMedel, M., & Goles, E. (2019). Block invariance and reversibility of one dimensional linear cellular automata. Adv. Appl. Math., 105, 83–101.
Abstract: Consider a onedimensional, binary cellular automaton f (the CA rule), where its n nodes are updated according to a deterministic block update (blocks that group all the nodes and such that its order is given by the order of the blocks from left to right and nodes inside a block are updated synchronously). A CA rule is block invariant over a family F of block updates if its set of periodic points does not change, whatever the block update of F is considered. In this work, we study the block invariance of linear CA rules by means of the property of reversibility of the automaton because such a property implies that every configuration has a unique predecessor, so, it is periodic. Specifically, we extend the study of reversibility done for the Wolfram elementary CA rules 90 and 150 as well as, we analyze the reversibility of linear rules with neighbourhood radius 2 by using matrix algebra techniques. (C) 2019 Elsevier Inc. All rights reserved.



Alejo, L., Atkinson, J., Arriagada, C., GuzmanFierro, V., & Roeckel, M. (2019). Effluent composition prediction of a twostage anaerobic digestion process: machine learning and stoichiometry techniques (vol 25, pg 21149, 2018) (Vol. 26). Springer Heidelberg.
Abstract: The original publication of this paper contains a mistake. Unfortunately, an author was inadvertently missed out, Constanza Arriagada had participated in the operation of the anaerobic digesters cited in the work and now as a PhD student, she is involved in the production of other publication.

