
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.



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.



Becker, F., Montealecre, P., Rapaport, I., & Todinca, I. (2020). The Impact Of Locality In The Broadcast Congested Clique Model. SIAM Discret. Math., 34(1), 682–700.
Abstract: The broadcast congested clique model (BCLIQUE) is a messagepassing model of distributed computation where n nodes communicate with each other in synchronous rounds. First, in this paper we prove that there is a oneround, deterministic algorithm that reconstructs the input graph G if the graph is ddegenerate, and rejects otherwise, using bandwidth b = O(d . log n). Then, we introduce a new parameter to the model. We study the situation where the nodes, initially, instead of knowing their immediate neighbors, know their neighborhood up to a fixed radius r. In this new framework, denoted BCLIQuE[r], we study the problem of detecting, in G, an induced cycle of length at most k (CYCLE <= k) and the problem of detecting an induced cycle of length at least k +1 (CYCLE>k). We give upper and lower bounds. We show that if each node is allowed to see up to distance r = left perpendicular k/2 right perpendicular + 1, then a polylogarithmic bandwidth is sufficient for solving CYCLE>k with only two rounds. Nevertheless, if nodes were allowed to see up to distance r = left perpendicular k/3 right perpendicular, then any oneround algorithm that solves CYCLE>k needs the bandwidth b to be at least Omega(n/ log n). We also show the existence of a oneround, deterministic BCLIQUE algorithm that solves CYCLE <= k with bandwitdh b = O(n(1/left perpendicular k/2 right perpendicular). log n). On the negative side, we prove that, if epsilon <= 1/3 and 0 < r <= k/4, then any epsilonerror, Rround, bbandwidth algorithm in the BCLIQUE[r] model that solves problem CYCLE(<= k )satisfies R . b = Omega(n(1/left perpendicular k/2 right perpendicular)).



Cando, M. A., Hube, M. A., Parra, P. F., & Arteta, C. A. (2020). Effect of stiffness on the seismic performance of code conforming reinforced concrete shear wall buildings. Eng. Struct., 219, 14 pp.
Abstract: This study assesses the effect of the stiffness on the seismic performance of residential shear wall buildings designed according to current Chilean regulations, including DS60 and DS61. Specifically, the paper focuses on the effect of stiffness on the building overstrength, displacement ductility, fragility for Life Safety (LS) and collapse limit states, as well as the probability of achieving these two limits states in 50 years. The seismic performance is assessed for a group of four 20 story residential shear wall buildings archetypes located in Santiago. Walls were modeled using the multiple vertical line element model (MVLEM) with inelastic hysteretic materials for the vertical elements, and a linear elastic shear behavior. Pushover analyses were considered to estimate the buildings overstrength and displacement ductility, while incremental dynamic analyses were per formed to estimate fragility curves. A probabilistic seismic hazard analysis, which considered the seismicity of Chile central zone, was performed to estimate the probability of achieving the two limits states in 50 years. The results show that an increase in the stiffness reduces the chance of exceeding the LS and collapse limit states for the same intensity level. Additionally, the probabilistic seismic hazard analysis shows that, when the stiffness increases, the probability of reaching the LS limit state in 50 years also decreases. Counterintuitively, the probability of collapse in 50 years increases as the stiffness increases, due to the considered seismic hazard and the design requirements. Since society is moving towards resilient structural designs that minimize damage, disruption and economic losses, it is concluded that the performance of reinforced concrete shear wall buildings is improved by increasing the stiffness.



Canessa, E., Chaigneau, S. E., Moreno, S., & Lagos, R. (2020). Informational content of cosine and other similarities calculated from highdimensional Conceptual Property Norm data. Cogn. Process., to appear, 14 pp.
Abstract: To study concepts that are coded in language, researchers often collect lists of conceptual properties produced by human subjects. From these data, different measures can be computed. In particular, interconcept similarity is an important variable used in experimental studies. Among possible similarity measures, the cosine of conceptual property frequency vectors seems to be a de facto standard. However, there is a lack of comparative studies that test the merit of different similarity measures when computed from property frequency data. The current work compares four different similarity measures (cosine, correlation, Euclidean and Chebyshev) and five different types of data structures. To that end, we compared the informational content (i.e., entropy) delivered by each of those 4 x 5 = 20 combinations, and used a clustering procedure as a concrete example of how informational content affects statistical analyses. Our results lead us to conclude that similarity measures computed from lowerdimensional data fare better than those calculated from higherdimensional data, and suggest that researchers should be more aware of data sparseness and dimensionality, and their consequences for statistical analyses.



Carmichael, T. W., Quinn, S. N., Mustill, A. J., Huang, C., Zhou, G., Persson, C. M., et al. (2020). Two Intermediatemass Transiting Brown Dwarfs from the TESS Mission. Astron. J., 160(1), 15 pp.
Abstract: We report the discovery of two intermediatemass transiting brown dwarfs (BDs), TOI569b and TOI1406b, from NASA's Transiting Exoplanet Survey Satellite mission. TOI569b has an orbital period of P = 6.55604 0.00016 days, a mass of Mb = 64.1 1.9 , and a radius of Rb = 0.75 0.02 . Its host star, TOI569, has a mass of Mstar = 1.21 0.05, a radius of Rstar = 1.47 0.03 dex, and an effective temperature of Teff = 5768 110 K. TOI1406b has an orbital period of P = 10.57415 0.00063 days, a mass of Mb = 46.0 2.7 , and a radius of Rb = 0.86 0.03 . The host star for this BD has a mass of Mstar = 1.18 0.09 a radius of Rstar = 1.35 0.03 dex, and an effective temperature of Teff = 6290 100 K. Both BDs are in circular orbits around their host stars and are older than 3 Gyr based on stellar isochrone models of the stars. TOI569 is one of two slightly evolved stars known to host a transiting BD (the other being KOI415). TOI1406b is one of three known transiting BDs to occupy the mass range of 4050 and one of two to have a circular orbit at a period near 10 days (with the first being KOI205b). Both BDs have reliable ages from stellar isochrones, in addition to their wellconstrained masses and radii, making them particularly valuable as tests for substellar isochrones in the BD massradius diagram.



Verdugo, I., Cruz, J. J., Alvarez, E., Reszka, P., da Silva, L. F. F., & Fuentes, A. (2020). Candle flame soot sizing by planar timeresolved laserinduced incandescence. Sci Rep, 10(1), 12 pp.
Abstract: Soot emissions from flaming combustion are relevant as a significant source of atmospheric pollution and as a source of nanomaterials. Candles are interesting targets for soot characterization studies since they burn complex fuels with a large number of carbon atoms, and yield stable and repeatable flames. We characterized the soot particle size distributions in a candle flame using the planar twocolor timeresolved laser induced incandescence (2D2C TiReLII) technique, which has been successfully applied to different combustion applications, but never before on a candle flame. Soot particles are heated with a planar laser sheet to temperatures above the normal flame temperatures. The incandescent soot particles emit thermal radiation, which decays over time when the particles cool down to the flame temperature. By analyzing the temporal decay of the incandescence signal, soot particle size distributions within the flame are obtained. Our results are consistent with previous works, and show that the outer edges of the flame are characterized by larger particles (approximate to 60 nm), whereas smaller particles (approximate to 25 nm) are found in the central regions. We also show that our effective temperature estimates have a maximum error of 100 K at early times, which decreases as the particles cool.



Cardenas, C., Guzman, F., Carmona, M., Munoz, C., Nilo, L., Labra, A., et al. (2020). Synthetic Peptides as a Promising Alternative to Control Viral Infections in Atlantic Salmon. Pathogens, 9(8), 600.
Abstract: Viral infections in salmonids represent an ongoing challenge for the aquaculture industry. Two RNA viruses, the infectious pancreatic necrosis virus (IPNV) and the infectious salmon anemia virus (ISAV), have become a latent risk without healing therapies available for either. In this context, antiviral peptides emerge as effective and relatively safe therapeutic molecules. Based on in silico analysis of VP2 protein from IPNV and the RNAdependent RNA polymerase from ISAV, a set of peptides was designed and were chemically synthesized to block selected key events in their corresponding infectivity processes. The peptides were tested in fish cell lines in vitro, and four were selected for decreasing the viral load: peptide GIM182 for IPNV, and peptides GIM535, GIM538 and GIM539 for ISAV. In vivo tests with the IPNV GIM 182 peptide were carried out using Salmo salar fish, showing a significant decrease of viral load, and proving the safety of the peptide for fish. The results indicate that the use of peptides as antiviral agents in disease control might be a viable alternative to explore in aquaculture.`



Canessa, G., Moreno, E., & Pagnoncelli, B. K. (2020). The riskaverse ultimate pit problem. Optim. Eng., to appear.
Abstract: In this work, we consider a riskaverse ultimate pit problem where the grade of the mineral is uncertain. We derive conditions under which we can generate a set of nested pits by varying the risk level instead of using revenue factors. We propose two properties that we believe are desirable for the problem: risk nestedness, which means the pits generated for different risk aversion levels should be contained in one another, and additive consistency, which states that preferences in terms of order of extraction should not change if independent sectors of the mine are added as precedences. We show that only an entropic risk measure satisfies these properties and propose a twostage stochastic programming formulation of the problem, including an efficient approximation scheme to solve it. We illustrate our approach in a small selfconstructed example, and apply our approximation scheme to a realworld section of the Andina mine, in Chile.



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, to appear.
Abstract: Based on fifteen European plants a statistical model for the estimation of theanaerobic biodegradability of plant material was developed. We show that this new formulation represents an accurate and costeffective method to identifying 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 ADF value. Apart from being theoretically meaningful, the ADFbased empirical model requires the least effort compared to other four conceptual models proposed, as individual fractions of cellulose, hemicellulose and lignin do not need to be assessed, which also enhances the accuracy of the model�s estimation. The model�s results showed greatpredictability power, allowing to identify interesting crops for sustainable crop rotations. Finally, the model was used to predict Bo of 114 European plant
samples that had been previously characterized by means of the van Soest method.



Barrera, J., & Lagos, G. (2020). Limit distributions of the upper order statistics for the Levyfrailty MarshallOlkin distribution. Extremes, to appear.



Caroca, P., Cartes, C., Davies, T. B., Olivari, J., Rica, S., & VogtGeisse, K. (2020). The anatomy of the 2019 Chilean social unrest. Chaos, to appear.
Abstract: We analyze the 2019 Chilean social unrest episode, consisting of a sequence of events, through the lens of an epidemiclike model that considers global contagious dynamics. We adjust the parameters to the Chilean social unrest aggregated public data available from the Undersecretary of Human Rights, and observe that the number of violent events follows a welldefined pattern already observed in various public disorder episodes in other countries since the sixties. Although the epidemiclike models display a single event that reaches a peak followed by an exponential decay, we add standard perturbation schemes that may produce a rich temporal behavior as observed in the 2019 Chilean social turmoil. Although we only have access to aggregated data, we are still able to fit it to our model quite well, providing interesting insights on social unrest dynamics.



Wiener, M., Moreno, S., Jafvert, C., & Nies, L. (2020). Time Series Analysis of Water Use and Indirect Reuse within a HUC4 Basin (Wabash) over a Nine Year Period. Science of the Total Environment, to appear.



Castaneda, P., & Reus, L. (2019). Suboptimal investment behavior and welfare costs: A simulation based approach. Financ. Res. Lett., 30, 170–180.
Abstract: We propose a representation of suboptimal investment behavior based on the stochastic discount factor (SDF) paradigm. Suboptimal investment behavior is rationalized as being the investor's optimal decision under a wrong SDF, while wealth trajectories and budget constraints are based on the true SDF. We develop a novel Monte Carlo simulation approach to compute the welfare costs for this suboptimal behavior. We study the suboptimal portfolio choice under CRRA preferences using two financial market models. The Monte Carlo simulation delivers comparable welfare losses to those computed in the original studies, which are based on partial differential equations (PDE) and – finitedifference schemes.



Weaver, I. C., LopezMorales, M., Espinoza, N., Rackham, B. V., Osip, D. J., Apai, D., et al. (2020). ACCESS: A Visual to Nearinfrared Spectrum of the Hot Jupiter WASP43b with Evidence of H2O, but No Evidence of Na or K. Astron. J., 159(1), 21 pp.
Abstract: We present a new groundbased visual transmission spectrum of the hot Jupiter WASP43b, obtained as part of the ACCESS Survey. The spectrum was derived from four transits observed between 2015 and 2018, with combined wavelength coverage between 5300 and 9000 A and an average photometric precision of 708 ppm in 230 A bins. We perform an atmospheric retrieval of our transmission spectrum combined with literature Hubble Space Telescope/WFC3 observations to search for the presence of clouds/hazes as well as Na, K, H alpha, and H2O planetary absorption and stellar spot contamination over a combined spectral range of 531816420 A. We do not detect a statistically significant presence of Na i or K i alkali lines, or H alpha in the atmosphere of WASP43b. We find that the observed transmission spectrum can be best explained by a combination of heterogeneities on the photosphere of the host star and a clear planetary atmosphere with H2O. This model yields a log evidence of 8.26 0.42 higher than a flat (featureless) spectrum. In particular, the observations marginally favor the presence of large, lowcontrast spots over the four ACCESS transit epochs with an average covering fraction T = 132 K 132 K. Within the planet's atmosphere, we recover a log H2O volume mixing ratio of 2.78(1.47)(+1.38), which is consistent with previous H2O abundance determinations for this planet.



Travisany, D., Goles, E., Latorre, M., Cort?s, M. P., & Maass, A. (2020). Generation and robustness of Boolean networks to model Clostridium difficile infection. Nat. Comput., 19(1), 111–134.
Abstract: One of the more common healthcare associated infection is Chronic diarrhea. This disease is caused by the bacterium Clostridium difficile which alters the normal composition of the human gut flora. The most successful therapy against this infection is the fecal microbial transplant (FMT). They displace C. difficile and contribute to gut microbiome resilience, stability and prevent further episodes of diarrhea. The microorganisms in the FMT their interactions and inner dynamics reshape the gut microbiome to a healthy state. Even though microbial interactions play a key role in the development of the disease, currently, little is known about their dynamics and properties. In this context, a Boolean network model for C. difficile infection (CDI) describing one set of possible interactions was recently presented. To further explore the space of possible microbial interactions, we propose the construction of a neutral space conformed by a set of models that differ in their interactions, but share the final community states of the gut microbiome under antibiotic perturbation and CDI. To begin with the analysis, we use the previously described Boolean network model and we demonstrate that this model is in fact a threshold Boolean network (TBN). Once the TBN model is set, we generate and use an evolutionary algorithm to explore to identify alternative TBNs. We organize the resulting TBNs into clusters that share similar dynamic behaviors. For each cluster, the associated neutral graph is constructed and the most relevant interactions are identified. Finally, we discuss how these interactions can either affect or prevent CDI.



Aybar, M., PerezCalleja, P., Li, M., Pavissich, J. P., & Nerenberg, R. (2019). Predation creates unique void layer in membraneaerated biofilms. Water Res., 149, 232–242.
Abstract: The membraneaerated biofilm reactor (MABR) is a novel wastewater treatment technology based on oxygensupplying membranes. The counter diffusion of oxygen and electron donors in MABRs leads to unique behavior, and we hypothesized it also could impact predation. We used optical coherence tomography (OCT), microsensor analyses, and mathematical modeling to investigate predation in membraneaerated biofilms (MABs). When protozoa were excluded from the inoculum, the MAB's OCTobservable void fraction was around 5%. When protozoa were included, the void fraction grew to nearly 50%, with large, continuous voids at the base of the biofilm. Realtime OCT imaging showed highly motile protozoa in the voids. MABs with protozoa and a high bulk COD (270 mg/L) only had 4% void fraction. DNA sequencing revealed a high relative abundance of amoeba in both high and lowCOD MABs. Flagellates were only abundant in the lowCOD MAB. Modeling also suggested a relationship between substrate concentrations, diffusion mode (co or counterdiffusion), and bioflim void fraction. Results suggest that amoeba proliferate in the bioflim interior, especially in the aerobic zones. Voids form once COD limitation at the base of MABs allows predation rates to exceed microbial growth rates. Once formed, the voids provide a niche for motile protozoa, which expand the voids into a large, continuous gap. This increases the potential for biofilm sloughing, and may have detrimental effects on slowgrowing, aerobic microorganisms such as nitrifying bacteria. (C)2018 Elsevier Ltd. All rights reserved.



Reus, L., Pagnoncelli, B., & Armstrong, M. (2019). Better management of production incidents in mining using multistage stochastic optimization. Resour. Policy, 63, 13 pp.
Abstract: Among the many sources of uncertainty in mining are production incidents: these can be strikes, environmental issues, accidents, or any kind of event that disrupts production. In this work, we present a strategic mine planning model that takes into account these types of incidents, as well as random prices. When confronted by production difficulties, mines which have contracts to supply customers have a range of flexibility options including buying on the spot market, or taking material from a stockpile if they have one. Earlier work on this subject was limited in that the optimization could only be carried out for a few stages (up to 5 years) and in that it only analyzed the riskneutral case. By using decomposition schemes, we are now able to solve largescale versions of the model efficiently, with a horizon of up to 15 years. We consider decision trees with up to 615 scenarios and implement risk aversion using Conditional ValueatRisk, thereby detecting its effect on the optimal policy. The results provide a “roadmap” for mine management as to optimal decisions, taking future possibilities into account. We present extensive numerical results using the new sddp.jl library, written in the Julia language, and discuss policy implications of our findings.



O' Ryan, R., Benavides, C., Diaz, M., San Martin, J. P., & Mallea, J. (2019). Using probabilistic analysis to improve greenhouse gas baseline forecasts in developing country contexts: the case of Chile. Clim. Policy, 19(3), 299–314.
Abstract: In this paper, initial steps are presented toward characterizing, quantifying, incorporating and communicating uncertainty applying a probabilistic analysis to countrywide emission baseline forecasts, using Chile as a case study. Most GHG emission forecasts used by regulators are based on bottomup deterministic approaches. Uncertainty is usually incorporated through sensitivity analysis and/or use of different scenarios. However, much of the available information on uncertainty is not systematically included. The deterministic approach also gives a wide range of variation in values without a clear sense of probability of the expected emissions, making it difficult to establish both the mitigation contributions and the subsequent policy prescriptions for the future. To improve on this practice, we have systematically included uncertainty into a bottomup approach, incorporating it in key variables that affect expected GHG emissions, using readily available information, and establishing expected baseline emissions trajectories rather than scenarios. The resulting emission trajectories make explicit the probability percentiles, reflecting uncertainties as well as possible using readily available information in a manner that is relevant to the decision making process. Additionally, for the case of Chile, contradictory deterministic results are eliminated, and it is shown that, whereas under a deterministic approach Chile's mitigation ambition does not seem high, the probabilistic approach suggests this is not necessarily the case. It is concluded that using a probabilistic approach allows a better characterization of uncertainty using existing data and modelling capacities that are usually weak in developing country contexts. Key policy insights Probabilistic analysis allows incorporating uncertainty systematically into key variables for baseline greenhouse gas emission scenario projections. By using probabilistic analysis, the policymaker can be better informed as to future emission trajectories. Probabilistic analysis can be done with readily available data and expertise, using the usual models preferred by policymakers, even in developing country contexts.



Jarur, M. C., Dumais, J., & Rica, S. (2019). Limiting speed for jumping. C. R. Mec., 347(4), 305–317.
Abstract: General mechanical considerations provide an upper bound for the takeoff velocity of any jumper, animate or inanimate, rigid or soft body, animal or vegetal. The takeoff velocity is driven by the ratio of released energy to body mass. Further, the mean reaction force on a rigid platform during pushoff is inversely proportional to the characteristic size of the jumper. These general considerations are illustrated in the context of Alexander's jumper model, which can be solved exactly and which shows an excellent agreement with the mechanical results. (C) 2019 Academie des sciences. Published by Elsevier Masson SAS. All rights reserved.

