
Affolter, C., Kedzierska, J., Vielma, T., Weisse, B., & Aiyangar, A. (2020). Estimating lumbar passive stiffness behaviour from subjectspecific finite element models and in vivo 6DOF kinematics. J. Biomech., 102, 11 pp.
Abstract: Passive rotational stiffness of the osseoligamentous spine is an important input parameter for estimating invivo spinal loading using musculoskeletal models. These data are typically acquired from cadaveric testing. Increasingly, they are also estimated from subjectspecific imagingbased finite element (FE) models, which are typically built from CT/MR data obtained in supine position and employ pure rotation kinematics. We explored the sensitivity of FEbased lumbar passive rotational stiffness to two aspects of functional invivo kinematics: (a) passive strain changes from supine to upright standing position, and (b) invivo coupled translationrotation kinematics. We developed subjectspecific FE models of four subjects' L4L5 segments from supine CT images. Sagittally symmetric flexion was simulated in two ways: (i) pure flexion up to 12 degrees under a 500 N follower load directly from the supine pose. (ii) First, a displacementbased approach was implemented to attain the upright pose, as measured using Dynamic Stereo Xray (DSX) imaging. We then simulated invivo flexion using DSX imagingderived kinematics. Datasets from weightbearing motion with three different external weights [(4.5 kg), (9.1 kg), (13.6 kg)] were used. Accounting for supineupright motion generated compressive preloads approximate to 468 N (+/ 188 N) and a “pretorque” approximate to 2.5 Nm (+/ 2.2 Nm), corresponding to 25% of the reaction moment at 10 degrees flexion (case (i)). Rotational stiffness estimates from DSXbased coupled translationrotation kinematics were substantially higher compared to pure flexion. Reaction Moments were almost 90% and 60% higher at 5 degrees and 10 degrees of L4L5 flexion, respectively. Withinsubject differences in rotational stiffness based on external weight were small, although betweensubject variations were large. (C) 2020 Elsevier Ltd. All rights reserved.



Akian, M., Gaubert, S., & Hochart, A. (2020). A Game Theory Approach To The Existence And Uniqueness Of Nonlinear PerronFrobenius Eigenvectors. Discret. Contin. Dyn. Syst., 40(1), 207–231.
Abstract: We establish a generalized PerronFrobenius theorem, based on a combinatorial criterion which entails the existence of an eigenvector for any nonlinear orderpreserving and positively homogeneous map f acting on the open orthant R>0(n). This criterion involves dominions, i.e., sets of states that can be made invariant by one player in a twoperson game that only depends on the behavior of f “at infinity”. In this way, we characterize the situation in which for all alpha, beta > 0, the “slice space” Salpha(beta) :={x is an element of R>0(n) vertical bar alpha x <= f(x) <= beta x} is bounded in Hilbert's projective metric, or, equivalently, for all uniform perturbations g of f, all the orbits of g are bounded in Hilbert's projective metric. This solves a problem raised by Gaubert and Gunawardena (Trans. AMS, 2004). We also show that the uniqueness of an eigenvector is characterized by a dominion condition, involving a different game depending now on the local behavior of f near an eigenvector. We show that the dominion conditions can be verified by directed hypergraph methods. We finally illustrate these results by considering specific classes of nonlinear maps, including Shapley operators, generalized means and nonnegative tensors.



Alcaino, P., SantaMaria, H., MagnaVerdugo, C., & Lopez, L. (2020). Experimental fastassessment of postfire residual strength of reinforced concrete frame buildings based on nondestructive tests. Constr. Build. Mater., 234, 10 pp.
Abstract: Assessment of the residual strength of reinforced concrete buildings subjected to fire is a problem that requires fast and sufficiently reliable resolution, necessary for the action of firefighters, forensic fire investigation, and structural assessment of postfire condition of the building to take place. In all cases safety and integrity of firefighters and researchers can be at risk, and it is necessary to have rapidly and sufficiently reliable information in order to choose whether to enter freely, to enter with caution, or simply do not enter to the burned structure. This required prompt assessment gives no time or background to develop mathematical models of the structure and damage propagation. This work presents an experimental methodology for a fast assessment of postfire residual strength of reinforced concrete frame buildings based on the high correlation between the loss of strength and nondestructive test results of frame concrete elements subjected to fire action. (C) 2019 Elsevier Ltd. All rights reserved.



Alejo, L., Atkinson, J., & Lackner, S. (2020). Looking deeper – exploring hidden patterns in reactor data of Nremoval systems through clustering analysis. Water Sci. Technol., to appear.
Abstract: In this work, clustering analysis of two partial nitritationanammox (PNA) moving bed biofilm reactors (MBBR) containing different types of carrier material was explored for the identification of patterns and operational conditions that may benefit process performance. The systems ran for two years under fluctuations of temperature and organic matter. Ex situ batch activity tests were performed every other week during the operation of these reactors. These datasets and the parameters, which were monitored online and in the laboratory, were combined and analyzed applying clustering analysis to identify nonobvious information regarding the performance of the systems. The initial results were consistent with the literature and from an operational perspective, which allowed the parameters to be explored further. The new information revealed that the oxidation reduction potential (ORP) and the anaerobic ammonium oxidizing bacteria (AnAOB) activity correlated well. ORP also dropped when the reactors were exposed to real wastewater (presence of organic matter). Moreover, operating conditions during nitrite accumulation were identified through clustering, and also revealed inhibition of anammox bacteria already at low nitrite concentrations.



Arbelaez, H., Bravo, V., Hernandez, R., Sierra, W., & Venegas, O. (2020). A new approach for the univalence of certain integral of harmonic mappings. Indag. Math.New Ser., 31(4), 525–535.
Abstract: The principal goal of this paper is to extend the classical problem of finding the values of alpha is an element of C for which either (f) over cap (alpha) (z) = integral(z)(0) (f (zeta)/zeta)(alpha) d zeta or f(alpha) (z) = integral(z)(0)(f' (zeta))(alpha)d zeta are univalent, whenever f belongs to some subclasses of univalent mappings in D, to the case of harmonic mappings, by considering the shear construction introduced by Clunie and SheilSmall in [4]. (C) 2020 Royal Dutch Mathematical Society (KWG). Published by Elsevier B.V. All rights reserved.



ArevaloRamirez, T., Villacres, J., Fuentes, A., Reszka, P., & Cheein, F. A. A. (2020). Moisture content estimation of Pinus radiata and Eucalyptus globulus from reconstructed leaf reflectance in the SWIR region. Biosyst. Eng., 193, 187–205.
Abstract: Valparaiso, a centralsouthern region in Chile, has one of the highest rates of wildfire occurrence in the country. The constant threat of fires is mainly due to its highly flammable forest plantation, composed of 97.5% Pinus radiata and Eucalyptus globulus. Fuel moisture content is one of the most relevant parameters for studying fire spreading and risk, and can be estimated from the reflectance of leaves in the short wave infrared (SWIR) range, not easily available in most visionbased sensors. Therefore, this work addresses the problem of estimating the water content of leaves from the two previously mentioned species, without any knowledge of their spectrum in the SWIR band. To this end, and for validation purposes, the reflectance of 90 leaves per species, at five dehydration stages, were taken between 350 nm and 2500 nm (full spectrum). Then, two machinelearning regressors were trained with 70% of the data set to determine the unknown reflectance, in the range 1000 nm2500 nm. Results were validated with the remaining 30% of the data, achieving a root mean square error less than 9% in the spectrum estimation, and an error of 10% in spectral indices related to water content estimation. (C) 2020 IAgrE. Published by Elsevier Ltd. All rights reserved.



Argiz, L., Reyes, C., Belmonte, M., Franchi, O., Campo, R., FraVazquez, A., et al. (2020). Assessment of a fast method to predict the biochemical methane potential based on biodegradable COD obtained by fractionation respirometric tests. J. Environ. Manage., 269, 9 pp.
Abstract: The biochemical methane potential test (BMP) is the most common analytical technique to predict the performance of anaerobic digesters. However, this assay is timeconsuming (from 20 to over than 100 days) and consequently impractical when it is necessary to obtain a quick result. Several methods are available for faster BMP prediction but, unfortunately, there is still a lack of a clear alternative. Current aerobic tests underestimate the BMP of substrates since they only detect the easily biodegradable COD. In this context, the potential of COD fractionation respirometric assays, which allow the determination of the particulate slowly biodegradable fraction, was evaluated here as an alternative to early predict the BMP of substrates. Seven different origin waste streams were tested and the anaerobically biodegraded organic matter (CODmet) was compared with the different COD fractions. When considering adapted microorganisms, the appropriate operational conditions and the required biodegradation time, the differences between the CODmet, determined through BMP tests, and the biodegradable COD (CODb) obtained by respirometry, were not significant (CODmet (57.8026 +/ 21.2875) and CODb (55.6491 +/ 21.3417), t (5) = 0.189, p = 0.853). Therefore, results suggest that the BMP of a substrate might be early predicted from its CODb in only few hours. This methodology was validated by the performance of an interlaboratory studyconsidering four additional substrates.



Asenjo, F. A., & Mahajan, S. M. (2020). Resonant interaction between dispersive gravitational waves and scalar massive particles. Phys. Rev. D, 101(6), 4 pp.
Abstract: The KleinGordon equation is solved in the curved background spacetime created by a dispersive gravitational wave. Unlike solutions of perturbed Einstein equations in vacuum, dispersive gravitational waves do not travel exactly at the speed of light. As a consequence, the gravitational wave can resonantly exchange energy with scalar massive particles. Some details of the resonant interaction are displayed in a calculation demonstrating how relativistic particles (modeled by the KleinGordon equation), feeding on such gravitational waves, may be driven to extreme energies.



AstudilloDefru, N., Cloutier, R., Wang, S. X., Teske, J., Brahm, R., Hellier, C., et al. (2020). A hot terrestrial planet orbiting the bright M dwarf L 1689 unveiled by TESS. Astron. Astrophys., 636, 13 pp.
Abstract: We report the detection of a transiting superEarthsized planet (R = 1.39 +/ 0.09 Rcircle plus) in a 1.4day orbit around L 1689 (TOI134), a bright M1V dwarf (V = 11, K = 7.1) located at 25.15 +/ 0.02 pc. The host star was observed in the first sector of the Transiting Exoplanet Survey Satellite (TESS) mission. For confirmation and planet mass measurement purposes, this was followed up with groundbased photometry, seeinglimited and highresolution imaging, and precise radial velocity (PRV) observations using the HARPS and Magellan/PFS spectrographs. By combining the TESS data and PRV observations, we find the mass of L 1689 b to be 4.60 +/ 0.56 Mcircle plus and thus the bulk density to be 1.74(0.33)(+0.44) times higher than that of the Earth. The orbital eccentricity is smaller than 0.21 (95% confidence). This planet is a level one candidate for the TESS mission's scientific objective of measuring the masses of 50 small planets, and it is one of the most observationally accessible terrestrial planets for future atmospheric characterization.



Aylwin, R., JerezHanckes, C., & Pinto, J. (2020). On the Properties of Quasiperiodic Boundary Integral Operators for the Helmholtz Equation. Integr. Equ. Oper. Theory, 92(2), 41 pp.
Abstract: We study the mapping properties of boundary integral operators arising when solving twodimensional, timeharmonic waves scattered by periodic domains. For domains assumed to be at least Lipschitz regular, we propose a novel explicit representation of Sobolev spaces for quasiperiodic functions that allows for an analysis analogous to that of Helmholtz scattering by bounded objects. Except for RayleighWood frequencies, continuity and coercivity results are derived to prove wellposedness of the associated first kind boundary integral equations.



Aylwin, R., JerezHanckes, C., Schwab, C., & Zech, J. (2020). Domain Uncertainty Quantification in Computational Electromagnetics. SIAMASA J. Uncertain. Quantif., 8(1), 301–341.
Abstract: We study the numerical approximation of timeharmonic, electromagnetic fields inside a lossy cavity of uncertain geometry. Key assumptions are a possibly highdimensional parametrization of the uncertain geometry along with a suitable transformation to a fixed, nominal domain. This uncertainty parametrization results in families of countably parametric, Maxwelllike cavity problems that are posed in a single domain, with inhomogeneous coefficients that possess finite, possibly low spatial regularity, but exhibit holomorphic parametric dependence in the differential operator. Our computational scheme is composed of a sparse grid interpolation in the highdimensional parameter domain and an Hcurl conforming edge element discretization of the parametric problem in the nominal domain. As a steppingstone in the analysis, we derive a novel Strangtype lemma for Maxwelllike problems in the nominal domain, which is of independent interest. Moreover, we accommodate arbitrary small Sobolev regularity of the electric field and also cover uncertain isotropic constitutive or material laws. The shape holomorphy and edgeelement consistency error analysis for the nominal problem are shown to imply convergence rates for multilevel Monte Carlo and for quasiMonte Carlo integration, as well as sparse grid approximations, in uncertainty quantification for computational electromagnetics. They also imply expression rate estimates for deep ReLU networks of shapetosolution maps in this setting. Finally, our computational experiments confirm the presented theoretical results.



Aylwin, R., SilvaOelker, G., JerezHanckes, C., & Fay, P. (2020). Optimization methods for achieving high diffraction efficiency with perfect electric conducting gratings. J. Opt. Soc. Am. AOpt. Image Sci. Vis., 37(8), 1316–1326.
Abstract: This work presents the implementation, numerical examples, and experimental convergence study of first and secondorder optimization methods applied to onedimensional periodic gratings. Through boundary integral equations and shape derivatives, the profile of a grating is optimized such that it maximizes the diffraction efficiency for given diffraction modes for transverse electric polarization. We provide a thorough comparison of three different optimization methods: a firstorder method (gradient descent); a secondorder approach based on a Newton iteration, where the usual Newton step is replaced by taking the absolute value of the eigenvalues given by the spectral decomposition of the Hessian matrix to deal with nonconvexity; and the BroydenFletcherGoldfarbShanno (BFGS) algorithm, a quasiNewton method. Numerical examples are provided to validate our claims. Moreover, two grating profiles are designed for high efficiency in the Littrow configuration and then compared to a high efficiency commercial grating. Conclusions and recommendations, derived from the numerical experiments, are provided as well as future research avenues. (C) 2020 Optical Society of America



Azeem, M., Guérin, A., Dumais, T., Caminos, L., Goldstein, R. E., Pesci, A. I., et al. (2020). Optimal Design of Multilayer Fog Collectors. ACS Applied Materials & Interfaces, 12(6), 7736–7743.
Abstract: The growing concerns over desertification have spurred research into technologies aimed at acquiring water from nontraditional sources such as dew, fog, and water vapor. Some of the most promising developments have focused on improving designs to collect water from fog. However, the absence of a shared framework to predict, measure, and compare the water collection efficiencies of new prototypes is becoming a major obstacle to progress in the field. We address this problem by providing a general theory to design efficient fog collectors as well as a concrete experimental protocol to furnish our theory with all the necessary parameters to quantify the effective water collection efficiency. We show in particular that multilayer collectors are required for high fog collection efficiency and that all efficient designs are found within a narrow range of mesh porosity. We support our conclusions with measurements on simple multilayer harp collectors.



Barrera, J., & Lagos, G. (2020). Limit distributions of the upper order statistics for the Levyfrailty MarshallOlkin distribution. Extremes, to appear, 26 pp.
Abstract: The MarshallOlkin (MO) distribution is considered a key model in reliability theory and in risk analysis, where it is used to model the lifetimes of dependent components or entities of a system and dependency is induced by “shocks” that hit one or more components at a time. Of particular interest is the Levyfrailty subfamily of the MarshallOlkin (LFMO) distribution, since it has few parameters and because the nontrivial dependency structure is driven by an underlying Levy subordinator process. The main contribution of this work is that we derive the precise asymptotic behavior of the upper order statistics of the LFMO distribution. More specifically, we consider a sequence ofnunivariate random variables jointly distributed as a multivariate LFMO distribution and analyze the order statistics of the sequence asngrows. Our main result states that if the underlying Levy subordinator is in the normal domain of attraction of a stable distribution with index of stability alpha then, after certain logarithmic centering and scaling, the upper order statistics converge in distribution to a stable distribution if alpha> 1 or a simple transformation of it if alpha <= 1. Our result can also give easily computable confidence intervals for the last failure times, provided that a proper convergence analysis is carried out first.



Barrera, J., Carrasco, R. A., Mondschein, S., Canessa, G., & RojasZalazar, D. (2020). Operating room scheduling under waiting time constraints: the Chilean GES plan. Ann. Oper. Res., 286(12), 501–527.
Abstract: In 2000, Chile introduced profound health reforms to achieve a more equitable and fairer system (GES plan). The reforms established a maximum waiting time between diagnosis and treatment for a set of diseases, described as an opportunity guarantee within the reform. If the maximum waiting time is exceeded, the patient is referred to another (private) facility and receives a voucher to cover the additional expenses. This voucher is paid by the health provider that had to do the procedure, which generally is a public hospital. In general, this reform has improved the service for patients with GES pathologies at the expense of patients with nonGES pathologies. These new conditions create a complicated planning scenario for hospitals, in which the hospital's OR Manager must balance the fulfillment of these opportunity guarantees and the timely service of patients not covered by the guarantee. With the collaboration of the Instituto de Neurocirugia, in Santiago, Chile, we developed a mathematical model based on stochastic dynamic programming to schedule surgeries in order to minimize the cost of referrals to the private sector. Given the large size of the state space, we developed an heuristic to compute good solutions in reasonable time and analyzed its performance. Our experimental results, with both simulated and real data, show that our algorithm performs close to optimum and improves upon the current practice. When we compared the results of our heuristic against those obtained by the hospital's OR manager in a simulation setting with real data, we reduced the overtime from occurring 21% of the time to zero, and the nonGES average waiting list's length from 71 to 58 patients, without worsening the average throughput.



Barrera, J., Carrasco, R. A., & Moreno, E. (2020). Realtime fleet management decision support system with security constraints. TOP, to appear, 21 pp.
Abstract: Intelligent transportation, and in particular, fleet management, has been a forefront concern for a plethora of industries. This statement is especially true for the production of commodities, where transportation represents a central element for operational continuity. Additionally, in many industries, and in particular those with hazardous environments, fleet control must satisfy a wide range of security restrictions to ensure that risks are kept at bay and accidents are minimum. Furthermore, in these environments, any decision support tool must cope with noisy and incomplete data and give recommendations every few minutes. In this work, a fast and efficient decision support tool is presented to help fleet managers oversee and control ore trucks, in a mining setting. The main objective of this system is to help managers avoid interactions between ore trucks and personnel buses, one of the most critical security constraints in our case study, keeping a minimum security distance between the two at all times. Furthermore, additional algorithms are developed and implemented, so that this approach can work with reallife noisy GPS data. Through the use of historical data, the performance of this decision support system is studied, validating that it works under the reallife conditions presented by the company. The experimental results show that the proposed approach improved truck and road utilization significantly while allowing the fleet manager to control the security distance required by their procedures.



Barrera, J., Moreno, E., & Varas, S. (2020). A decomposition algorithm for computing income taxes with passthrough entities and its application to the Chilean case. Ann. Oper. Res., 286(12), 545–557.
Abstract: Income tax systems with “passthrough” entities transfer a firm's income to shareholders, which are taxed individually. In 2014, a Chilean tax reform introduced this type of entity and changed to an accrual basis that distributes incomes (but not losses) to shareholders. A crucial step for the Chilean taxation authority is to compute the final income of each individual given the complex network of corporations and companies, usually including cycles between them. In this paper, we show the mathematical conceptualization and the solution to the problem, proving that there is only one way to distribute income to taxpayers. Using the theory of absorbing Markov chains, we define a mathematical model for computing the taxable income of each taxpayer, and we propose a decomposition algorithm for this problem. This approach allows us to compute the solution accurately and to efficiently use computational resources. Finally, we present some characteristics of Chilean taxpayers' network and the computational results of the algorithm using this network.



Baselli, G., Contreras, F., Lillo, M., Marin, M., & Carrasco, R. A. (2020). Optimal decisions for salvage logging after wildfires. OmegaInt. J. Manage. Sci., 96, 9 pp.
Abstract: Strategic, tactical, and operational harvesting plans for the forestry and logging industry have been widely studied for more than 60 years. Many different settings and specific constraints due to legal, environmental, and operational requirements have been modeled, improving the performance of the harvesting process significantly. During the summer of 2017, Chile suffered from the most massive wildfires in its history, affecting almost half a million hectares, of which nearly half were forests owned by medium and small forestry companies. Some of the stands were burned by intense crown fires, which always spread fast, that burned the foliage and outer layer of the bark but left standing dead trees that could be salvage harvested before insect and decay processes rendered them unusable for commercial purposes. Unlike the typical operational programming models studied in the past, in this setting, companies can make insurance claims on part or all of the burnt forest, whereas the rest of the forest needs to be harvested before it loses its value. This problem is known as the salvage logging problem. The issue also has an important social component when considering medium and small forestry and logging companies: most of their personnel come from local communities, which have already been affected by the fires. Harvesting part of the remaining forest can allow them to keep their jobs longer and, hopefully, leave the company in a better financial situation if the harvesting areas are correctly selected. In this work, we present a novel mixedinteger optimizationbased approach to support salvage logging decisions, which helps in the configuration of an operationallevel harvesting and workforce assignment plan. Our model takes into account the payment from an insurance claim as well as future income from harvesting the remaining trees. The model also computes an optimal assignment of personnel to the different activities required. The objective is to improve the cash position of the company by the end of the harvest and ensure that the company is paying all its liabilities and maintaining personnel. We show how our model performs compared to the current decisions made by medium and smallsized forestry companies, and we study the specific case of a small forestry company located in Cauquenes, Chile, which used our model to decide its course of action. (C) 2019 Elsevier Ltd. All rights reserved.



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)).



Bottcher, L., Montealegre, P., Goles, E., & Gersbach, H. (2020). Competing activistsPolitical polarization. Physica A, 545, 13 pp.
Abstract: Recent empirical findings suggest that societies have become more polarized in various countries. That is, the median voter of today represents a smaller fraction of society compared to two decades ago and yet, the mechanisms underlying this phenomenon are not fully understood. Since interactions between influential actors ("activists'') and voters play a major role in opinion formation, e.g. through social media, we develop a macroscopic opinion model in which competing activists spread their political ideas in specific groups of society. These ideas spread further to other groups in declining strength. While unilateral spreading shifts the opinion distribution, competition of activists leads to additional phenomena: Small heterogeneities among competing activists cause them to target different groups in society, which amplifies polarization. For moderate heterogeneities, we obtain target cycles and further amplification of polarization. In such cycles, the stronger activist differentiates himself from the weaker one, while the latter aims to imitate the stronger activist. (C) 2019 Elsevier B.V. All rights reserved.

