
EscapilInchauspe, P., & JerezHanckes, C. (2020). Helmholtz Scattering by Random Domains: FirstOrder Sparse Boundary Elements Approximation. SIAM J. Sci. Comput., to appear.



Fernandez, M., Munoz, F. D., & Moreno, R. (2020). Analysis of imperfect competition in natural gas supply contracts for electric power generation: A closedloop approach. Energy Econ., 87, 15 pp.
Abstract: The supply of natural gas is generally based on contracts that are signed prior to the use of this fuel for power generation. Scarcity of natural gas in systems where a share of electricity demand is supplied with gas turbines does not necessarily imply demand rationing, because most gas turbines can still operate with diesel when natural gas is not available. However, scarcity conditions can lead to electricity price spikes, with welfare effects for consumers and generation firms. We develop a closedloop equilibrium model to evaluate if generation firms have incentives to contract or import the sociallyoptimal volumes of natural gas to generate electricity. We consider a perfectlycompetitive electricity market, where all firms act as pricetakers in the short term, but assume that only a small number of firms own gas turbines and procure natural gas from, for instance, foreign suppliers in liquefied form. We illustrate an application of our model using a network reduction of the electric power system in Chile, considering two strategic firms that make annual decisions about natural gas imports in discrete quantities. We also assume that strategic firms compete in the electricity market with a set of competitive firms do not make strategic decisions about natural gas imports (i.e., a competitive fringe). Our results indicate that strategic firms could have incentives to sign natural gas contracts for volumes that are much lower than the sociallyoptimal ones, which leads to supernormal profits for these firms in the electricity market. Yet, this effect is rather sensitive to the price of natural gas. A high price of natural gas eliminates the incentives of generation firms to exercise market power through natural gas contracts. (C) 2020 Elsevier B.V. All rights reserved.



Gill, S., Wheatley, P. J., Cooke, B. F., Jordan, A., Nielsen, L. D., Bayliss, D., et al. (2020). NGTS11 b (TOI1847 b): A Transiting Warm Saturn Recovered from a TESS Singletransit Event. Astrophys. J. Lett., 898(1), 6 pp.
Abstract: We report the discovery of NGTS11 b (=TOI1847b), a transiting Saturn in a 35.46 day orbit around a mid Ktype star (Teff = 5050 +/ 80 K). We initially identified the system from a singletransit event in a TESS fullframe image light curve. Following 79 nights of photometric monitoring with an NGTS telescope, we observed a second full transit of NGTS11 b approximately one year after the TESS singletransit event. The NGTS transit confirmed the parameters of the transit signal and restricted the orbital period to a set of 13 discrete periods. We combined our transit detections with precise radialvelocity measurements to determine the true orbital period and measure the mass of the planet. We find NGTS11 b has a radius of 0.817 +/(0.028)(0.032) RJup, a mass of 0.344 +/(0.092)(0.073) MJup, and an equilibrium temperature of just 435 +/(34)(32) K, making it one of the coolest known transiting gas giants. NGTS11 b is the first exoplanet to be discovered after being initially identified as a TESS singletransit event, and its discovery highlights the power of intense photometric monitoring in recovering longerperiod transiting exoplanets from singletransit events.



Goles, E., Montealegre, P., & RiosWilson, M. (2020). On The Effects Of Firing Memory In The Dynamics Of Conjunctive Networks. Discret. Contin. Dyn. Syst., 40(10), 5765–5793.
Abstract: A boolean network is a map F : {0, 1}(n) > {0, 1}(n) that defines a discrete dynamical system by the subsequent iterations of F. Nevertheless, it is thought that this definition is not always reliable in the context of applications, especially in biology. Concerning this issue, models based in the concept of adding asynchronicity to the dynamics were propose. Particularly, we are interested in a approach based in the concept of delay. We focus in a specific type of delay called firing memory and it effects in the dynamics of symmetric (nondirected) conjunctive networks. We find, in the caseis in which the implementation of the delay is not uniform, that all the complexity of the dynamics is somehow encapsulated in the component in which the delay has effect. Thus, we show, in the homogeneous case, that it is possible to exhibit attractors of nonpolynomial period. In addition, we study the prediction problem consisting in, given an initial condition, determinate if a fixed coordinate will eventually change its state. We find again that in the nonhomogeneous case all the complexity is determined by the component that is affected by the delay and we conclude in the homogeneous case that this problem is PSPACEcomplete.



Goles, E., Tsompanas, M. A., Adamatzky, A., Tegelaar, M., Wosten, H. A. B., & Martinez, G. J. (2020). Computational universality of fungal sandpile automata. Phys. Lett. A, 384(22), 8 pp.
Abstract: Hyphae within the mycelia of the ascomycetous fungi are compartmentalised by septa. Each septum has a pore that allows for intercompartmental and interhyphal streaming of cytosol and even organelles. The compartments, however, have special organelles, Woronin bodies, that can plug the pores. When the pores are blocked, no flow of cytoplasm takes place. Inspired by the controllable compartmentalisation within the mycelium of the ascomycetous fungi we designed twodimensional fungal automata. A fungal automaton is a cellular automaton where communication between neighbouring cells can be blocked on demand. We demonstrate computational universality of the fungal automata by implementing sandpile cellular automata circuits there. We reduce the Monotone Circuit Value Problem to the Fungal Automaton Prediction Problem. We construct families of wires, crossovers and gates to prove that the fungal automata are Pcomplete. (C) 2020 Elsevier B.V. All rights reserved.



Golovach, P. A., Heggernes, P., Lima, P. T., & Montealegre, P. (2020). Finding connected secluded subgraphs. J. Comput. Syst. Sci., 113, 101–124.
Abstract: Problems related to finding induced subgraphs satisfying given properties form one of the most studied areas within graph algorithms. However, for many applications, it is desirable that the found subgraph has as few connections to the rest of the graph as possible, which gives rise to the SECLUDED PiSUBGRAPH problem. Here, input k is the size of the desired subgraph, and input t is a limit on the number of neighbors this subgraph has in the rest of the graph. This problem has been studied from a parameterized perspective, and unfortunately it turns out to be W[1]hard for many graph properties Pi, even when parameterized by k + t. We show that the situation changes when we are looking for a connected induced subgraph satisfying Pi. In particular, we show that the CONNECTED SECLUDED PiSUBGRAPH problem is FPT when parameterized by just t for many important graph properties Pi. (C) 2020 Elsevier Inc. All rights reserved.



Gonzalez, E., & Villena, M. J. (2020). On the spatial dynamics of vaccination: A spatial SIRSV model. Comput. Math. Appl., 80(5), 733–743.
Abstract: In this paper, we analyze the effects of vaccination from a spatial perspective. We propose a spatial deterministic SIRSV model, which considers a nonlinear system of partial differential equations with explicit attrition and diffusion terms for the vaccination process. The model allows us to simulate numerically the spatial and temporal dynamics of an epidemic, considering different spatial strategies for the vaccination policy. In particular, in our first example we analyze the classical SIRSV evolution with the addition of movements due to diffusion, while in the second one we focus on modeling one ring vaccination policy. We expect this model can improve spatial predictions of SIR vaccination models by taking into account the spatial dimension of the problem. (C) 2020 Elsevier Ltd. All rights reserved.



Guevara, E., Babonneau, F., HomemdeMello, T., & Moret, S. (2020). A machine learning and distributionally robust optimization framework for strategic energy planning under uncertainty. Appl. Energy, 271, 18 pp.
Abstract: This paper investigates how the choice of stochastic approaches and distribution assumptions impacts strategic investment decisions in energy planning problems. We formulate a twostage stochastic programming model assuming different distributions for the input parameters and show that there is significant discrepancy among the associated stochastic solutions and other robust solutions published in the literature. To remedy this sensitivity issue, we propose a combined machine learning and distributionally robust optimization (DRO) approach which produces more robust and stable strategic investment decisions with respect to uncertainty assumptions. DRO is applied to deal with ambiguous probability distributions and Machine Learning is used to restrict the DRO model to a subset of important uncertain parameters ensuring computational tractability. Finally, we perform an outofsample simulation process to evaluate solutions performances. The Swiss energy system is used as a case study all along the paper to validate the approach.



Hojman, S. A., & Asenjo, F. A. (2020). Classical and Quantum Dispersion Relations. Phys. Scr., 95(8), 7 pp.
Abstract: It is showed that, in general, classical and quantum dispersion relations are different due to the presence of the Bohm potential. There are exact particular solutions of the quantum (wave) theory which obey the classical dispersion relation, but they differ in the general case. The dispersion relations may also coincide when additional assumptions are made, such as WKB or eikonal approximations, for instance. This general result also holds for nonquantum wave equations derived from classical counterparts, such as in ray and wave optics, for instance. Explicit examples are given for covariant scalar, vectorial and tensorial fields in flat and curved spacetimes.



Josserand, C., Pomeau, Y., & Rica, S. (2020). Finitetime localized singularities as a mechanism for turbulent dissipation. Phys. Rev. Fluids, 5(5), 15 pp.
Abstract: The nature of the fluctuations of the dissipation rate in fluid turbulence is still under debate. One reason may be that the observed fluctuations are strong events of dissipation, which reveal the trace of spatiotemporal singularities of the Euler equations, which are the zero viscosity limit of ordinary incompressible fluids. Viscosity regularizes these hypothetical singularities, resulting in a chaotic fluctuating state in which the strong events appear randomly in space and time, making the energy dissipation highly fluctuating. Yet, to date, it is not known if smooth initial conditions of the Euler equations with finite energy do or do not blow up in finite time. We overcome this central difficulty by providing a scenario for singularitymediated turbulence based on the selffocusing nonlinear Schrodinger equation. It avoids the intrinsic difficulty of Euler equations since it is well known that solutions of this NLS equation with smooth initial conditions do blow up in finite time. When adding viscosity, the model shows (i) that dissipation takes place near the singularities only, (ii) that such intense events are random in space and time, (iii) that the mean dissipation rate is almost constant as the viscosity varies, and (iv) the observation of an ObukhovKolmogorov spectrum with a powerlaw dependence together with an intermittent behavior using structure function correlations, in close correspondence with the one measured in fluid turbulence.



Kamal, C., Gravelle, S., & Botto, L. (2020). Hydrodynamic slip can align thin nanoplatelets in shear flow. Nat. Commun., 11(1), 10 pp.
Abstract: The largescale processing of nanomaterials such as graphene and MoS2 relies on understanding the flow behaviour of nanometricallythin platelets suspended in liquids. Here we show, by combining nonequilibrium molecular dynamics and continuum simulations, that rigid nanoplatelets can attain a stable orientation for sufficiently strong flows. Such a stable orientation is in contradiction with the rotational motion predicted by classical colloidal hydrodynamics. This surprising effect is due to hydrodynamic slip at the liquidsolid interface and occurs when the slip length is larger than the platelet thickness; a slip length of a few nanometers may be sufficient to observe alignment. The predictions we developed by examining pure and surfacemodified graphene is applicable to different solvent/2D material combinations. The emergence of a fixed orientation in a direction nearly parallel to the flow implies a slipdependent change in several macroscopic transport properties, with potential impact on applications ranging from functional inks to nanocomposites. Current theories predict that a platelike particle rotates continuously in a shear flow. Kamal et al. instead show that even nanometric hydrodynamic slip may induce a thin platelike particle to adopt a stable orientation, and discuss implications of this effect for flow processing of 2D nanomaterials.



Lagos, F., Schreiber, M. R., Parsons, S. G., Zurlo, A., Mesa, D., Gansicke, B. T., et al. (2020). The White Dwarf Binary Pathways Survey III. Contamination from hierarchical triples containing a white dwarf. Mon. Not. Roy. Astron. Soc., 494(1), 915–922.
Abstract: The White Dwarf Binary Pathways Survey aims at increasing the number of known detached A, F, G, and K mainsequence stars in close orbits with white dwarf companions (WD+AFGK binaries) to refine our understanding about compact binary evolution and the nature of Supernova Ia progenitors. These close WD+AFGK binary stars are expected to form through common envelope evolution, in which tidal forces tend to circularize the orbit. However, some of the identified WD+AFGK binary candidates show eccentric orbits, indicating that these systems are either formed through a different mechanism or perhaps they are not close WD+AFGK binaries. We observed one of these eccentric WD+AFGK binaries with SPHERE and find that the system TYC 72189341 is in fact a triple system where the WD is a distant companion. The inner binary likely consists of the Gtype star plus an unseen lowmass companion in an eccentric orbit. Based on this finding, we estimate the fraction of triple systems that could contaminate the WD+AFGK sample. We find that less than 15 per cent of our targets with orbital periods shorter than 100 d might be hierarchical triples.



Montealegre, R., PerezSalazar, S., Rapaport, I., & Todinca, I. (2020). Graph reconstruction in the congested clique. J. Comput. Syst. Sci., 113, 1–17.
Abstract: In this paper we study the reconstruction problem in the congested clique model. Given a class of graphs g, the problem is defined as follows: if G is not an element of g, then every node must reject; if G is an element of g, then every node must end up knowing all the edges of G. The cost of an algorithm is the total number of bits received by any node through one link. It is not difficult to see that the cost of any algorithm that solves this problem is Omega(log vertical bar g(n)vertical bar/n), where g(n) is the subclass of all nnode labeled graphs in g. We prove that the lower bound is tight and that it is possible to achieve it with only 2 rounds. (C) 2020 Elsevier Inc. All rights reserved.



Munoz, M., RoblesNavarro, A., Fuentealba, P., & Cardenas, C. (2020). Predicting Deprotonation Sites Using Alchemical Derivatives. J. Phys. Chem. A, 124(19), 3754–3760.
Abstract: An alchemical transformation is any process, physical or fictitious, that connects two points in the chemical space. A particularly important transformation is the vanishing of a proton, whose energy can be linked to the proton dissociation enthalpy of acids. In this work we assess the reliability of alchemical derivatives in predicting the proton dissociation enthalpy of a diverse series of mono and polyprotic molecules. Alchemical derivatives perform remarkably well in ranking the proton affinity of all molecules. Additionally, alchemical derivatives could be use also as a predictive tool because their predictions correlate quite well with calculations based on energy differences and experimental values. Although secondorder alchemical derivatives underestimate the dissociation enthalpy, the deviation seems to be almost constant. This makes alchemical derivatives extremely accurate to evaluate the difference in proton affinity between two acid sites of polyprotic molecule. Finally, we show that the reason for the underestimation of the dissociation enthalpy is most likely the contribution of higherorder derivatives.



Nielsen, L. D., Brahm, R., Bouchy, F., Espinoza, N., Turner, O., Rappaport, S., et al. (2020). Three shortperiod Jupiters from TESS: HIP 65Ab, TOI157b, and TOI169b. Astron. Astrophys., 639, 17 pp.
Abstract: We report the confirmation and mass determination of three hot Jupiters discovered by the Transiting Exoplanet Survey Satellite (TESS) mission: HIP 65Ab (TOI129, TIC201248411) is an ultrashortperiod Jupiter orbiting a bright (V = 11.1 mag) K4dwarf every 0.98 days. It is a massive 3.213 +/ 0.078 MJ planet in a grazing transit configuration with an impact parameter of b = 1.17(0.08)(+0.10) b=1.170.08+0.10 . As a result the radius is poorly constrained, 2.03(0.49)(+0.61)R(J) 2.030.49+0.61 RJ . The planet's distance to its host star is less than twice the separation at which it would be destroyed by Roche lobe overflow. It is expected to spiral into HIP 65A on a timescale ranging from 80 Myr to a few gigayears, assuming a reduced tidal dissipation quality factor of Q(s)(') = 10(7) – 10(9) Qs ' =107109 . We performed a full phasecurve analysis of the TESS data and detected both illumination and ellipsoidal variations as well as Doppler boosting. HIP 65A is part of a binary stellar system, with HIP 65B separated by 269 AU (3.95 arcsec on sky). TOI157b (TIC 140691463) is a typical hot Jupiter with a mass of 1.18 +/ 0.13 MJ and a radius of 1.29 +/ 0.02 RJ. It has a period of 2.08 days, which corresponds to a separation of just 0.03 AU. This makes TOI157 an interesting system, as the host star is an evolved G9 subgiant star (V = 12.7). TOI169b (TIC 183120439) is a bloated Jupiter orbiting a V = 12.4 Gtype star. It has a mass of 0.79 +/ 0.06 MJ and a radius of 1.09(0.05)(+0.08)R(J) 1.090.05+0.08<mml:msub>RJ . Despite having the longest orbital period (P = 2.26 days) of the three planets, TOI169b receives the most irradiation and is situated on the edge of the Neptune desert. All three host stars are metal rich with [Fe / H] ranging from 0.18 to0.24.



PabonPereira, C. P., Hamelers, H. V. M., Matilla, I., & van Lier, J. B. (2020). New Insights on the Estimation of the Anaerobic Biodegradability of Plant Material: Identifying Valuable Plants for Sustainable Energy Production. Processes, 8(7), 23 pp.
Abstract: Based on fifteen European plant species, a statistical model for the estimation of the anaerobic biodegradability of plant material was developed. We show that this new approach represents an accurate and costeffective method to identify valuable energy plants for sustainable energy production. In particular, anaerobic biodegradability (Bo) of lignocellulosic material was empirically found to be related to the amount of cellulose plus lignin, as analytically assessed by the van Soest method, i.e., the acid detergent fiber (ADF) value. Apart from being theoretically meaningful, the ADFbased empirical model requires the least effort compared to the other four proposed conceptual models proposed, as individual fractions of cellulose, hemicellulose, and lignin do not need to be assessed, which also enhances the predictive accuracy of the model's estimation. The model's results showed great predictability power, allowing us to identify interesting crops for sustainable crop rotations. Finally, the model was used to predictB(o)of 114 European plant samples that had been previously characterized by means of the van Soest method.



Reus, L., & Fabozzi, F. J. Robust Solutions to the LifeCycle Consumption Problem. Comput. Econ., , 19 pp.
Abstract: This paper demonstrates how the wellknown discrete lifecycle consumption problem (LCP) can be solved using the Robust Counterpart (RC) formulation technique, as defined in BenTal and Nemirovski (Math Oper Res 23(4):769805, 1998). To do this, we propose a methodology that involves applying a change of variables over the original consumption before deriving the RC. These transformations allow deriving a closed solution to the inner problem, and thus to solve the LCP without facing the curse of dimensionality and without needing to specify the prior distribution for the investment opportunity set. We generalize the methodology and illustrate how it can be used to solve other type of problems. The results show that our methodology enables solving longterm instances of the LCP (30 years). We also show it provides an alternative consumption pattern as to the one provided by a benchmark that uses a dynamic programming approach. Rather than finding a consumption that maximizes the expected lifetime utility, our solution delivers higher utilities for worstcase scenarios of future returns.



Reus, L., Carrasco, J. A., & Pincheira, P. (2020). Do it with a smile: Forecasting volatility with currency options. Financ. Res. Lett., 34, 10 pp.
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.



Ritt, M., & Pereira, J. (2020). Heuristic and exact algorithms for minimumweight nonspanning arborescences. Eur. J. Oper. Res., 287(1), 61–75.
Abstract: We address the problem of finding an arborescence of minimum total edge weight rooted at a given vertex in a directed, edgeweighted graph. If the arborescence must span all vertices the problem is solvable in polynomial time, but the nonspanning version is NPhard. We propose reduction rules which determine vertices that are required or can be excluded from optimal solutions, a modification of Edmonds algorithm to construct arborescences that span a given set of selected vertices, and embed this procedure into an iterated local search for good vertex selections. Moreover, we propose a cutsetbased integer linear programming formulation, provide different linear relaxations to reduce the number of variables in the model and solve the reduced model using a branchandcut approach. We give extensive computational results showing that both the heuristic and the exact methods are effective and obtain better solutions on instances from the literature than existing approaches, often in much less time. (C) 2020 Elsevier B.V. All rights reserved.



Sanchez, R., & Villena, M. (2020). Comparative evaluation of wearable devices for measuring elevation gain in mountain physical activities. Proc. Inst. Mech. Eng. Part PJ. Sport. Eng. Technol., to appear, 8 pp.
Abstract: The aim of this article is to examine the validity of elevation gain measures in mountain activities, such as hiking and mountain running, using different wearable devices and postprocessing procedures. In particular, a total of 202 efforts were recorded and evaluated using three standard devices: GPS watch, GPS watch with barometric altimeter, and smartphone. A benchmark was based on orthorectified aerial photogrammetric survey conducted by the Chilean Air Force. All devices presented considerable elevation gain measuring errors, where the barometric device consistently overestimated elevation gain, while the GPS devices consistently underestimated elevation gain. The incorporation of secondary information in the postprocessing can substantially improve the elevation gain measuring accuracy independently of the device and altitude measuring technology, reducing the error from 5% to 1%. These results could help coaches and athletes correct elevation gain estimations using the proposed technique, which would serve as better estimates of physical workload in mountain physical activities.

