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Addison, B. C., Wright, D. J., Nicholson, B. A., Cale, B., Mocnik, T., Huber, D., et al. (2021). TOI-257b (HD 19916b): a warm sub-saturn orbiting an evolved F-type star. Mon. Not. Roy. Astron. Soc., 502(3), 3704–3722.
Abstract: We report the discovery of a warm sub-Saturn, TOI-257b (HD 19916b), based on data from NASA's Transiting Exoplanet Survey Satellite (TESS). The transit signal was detected by TESS and confirmed to be of planetary origin based on radial velocity observations. An analysis of the TESS photometry, the MINERVA-Australis, FEROS, and HARPS radial velocities, and the asteroseismic data of the stellar oscillations reveals that TOI-257b has a mass of M-P = 0.138 +/- 0.023M(J) (43.9 +/- 7.3 M-circle plus), a radius of R-P = 0.639 +/- 0.013 R-J (7.16 +/- 0.15 R-circle plus), bulk density of 0.65(-0.11)(+0.12) (cgs), and period 18.38818(-0.00084)(+0.00085) days. TOI-257b orbits a bright (V = 7.612 mag) somewhat evolved late F-type star with M-* = 1.390 +/- 0.046(Msun), R-* = 1.888 +/- 0.033 R-sun, T-eff = 6075 +/- 90 K, and vsin i = 11.3 +/- 0.5 kms(-1). Additionally, we find hints for a second non-transiting sub-Saturn mass planet on a similar to 71 day orbit using the radial velocity data. This system joins the ranks of a small number of exoplanet host stars (similar to 100) that have been characterized with asteroseismology. Warm sub-Saturns are rare in the known sample of exoplanets, and thus the discovery of TOI-257b is important in the context of future work studying the formation and migration history of similar planetary systems.
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Astudillo-Defru, 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 168-9 unveiled by TESS. Astron. Astrophys., 636, 13 pp.
Abstract: We report the detection of a transiting super-Earth-sized planet (R = 1.39 +/- 0.09 R-circle plus) in a 1.4-day orbit around L 168-9 (TOI-134), 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 ground-based photometry, seeing-limited and high-resolution 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 168-9 b to be 4.60 +/- 0.56 M-circle 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.
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Bustamante, M., & Contreras, M. (2016). Multi-asset Black-Scholes model as a variable second class constrained dynamical system. Physica A, 457, 540–572.
Abstract: In this paper, we study the multi-asset Black-Scholes model from a structural point of view. For this, we interpret the multi-asset Black-Scholes equation as a multidimensional Schrodinger one particle equation. The analysis of the classical Hamiltonian and Lagrangian mechanics associated with this quantum model implies that, in this system, the canonical momentums cannot always be written in terms of the velocities. This feature is a typical characteristic of the constrained system that appears in the high-energy physics. To study this model in the proper form, one must apply Dirac's method for constrained systems. The results of the Dirac's analysis indicate that in the correlation parameters space of the multi assets model, there exists a surface (called the Kummer surface Sigma(K), where the determinant of the correlation matrix is null) on which the constraint number can vary. We study in detail the cases with N = 2 and N = 3 assets. For these cases, we calculate the propagator of the multi-asset Black-Scholes equation and show that inside the Kummer Sigma(K) surface the propagator is well defined, but outside Sigma(K) the propagator diverges and the option price is not well defined. On Sigma(K) the propagator is obtained as a constrained path integral and their form depends on which region of the Kummer surface the correlation parameters lie. Thus, the multi-asset Black-Scholes model is an example of a variable constrained dynamical system, and it is a new and beautiful property that had not been previously observed. (C) 2016 Elsevier B.V. All rights reserved.
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Canessa, E., & Chaigneau, S. (2015). Calibrating Agent-Based Models Using a Genetic Algorithm. Stud. Inform. Control, 24(1), 79–90.
Abstract: We present a Genetic Algorithm (GA)-based tool that calibrates Agent-based Models (ABMs). The GA searches through a user-defined set of input parameters of an ABM, delivering values for those parameters so that the output time series of an ABM may match the real system's time series to certain precision. Once that set of possible values has been available, then a domain expert can select among them, the ones that better make sense from a practical point of view and match the explanation of the phenomenon under study. In developing the GA, we have had three main goals in mind. First, the GA should be easily used by non-expert computer users and allow the seamless integration of the GA with different ABMs. Secondly, the GA should achieve a relatively short convergence time, so that it may be practical to apply it to many situations, even if the corresponding ABMs exhibit complex dynamics. Thirdly, the GA should use a few data points of the real system's time series and even so, achieve a sufficiently good match with the ABM's time series to attaining relational equivalence between the real system under study and the ABM that models it. That feature is important since social science longitudinal studies commonly use few data points. The results show that all of those goals have been accomplished.
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Canessa, G., Gallego, J. A., Ntaimo, L., & Pagnoncelli, B. K. (2019). An algorithm for binary linear chance-constrained problems using IIS. Comput. Optim. Appl., 72(3), 589–608.
Abstract: We propose an algorithm based on infeasible irreducible subsystems to solve binary linear chance-constrained 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 chance-constrained 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.
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Clavero-Leon, C., Ruiz, D., Cillero, J., Orlando, J., & Gonzalez, B. (2021). The multi metal-resistant bacterium Cupriavidus metallidurans CH34 affects growth and metal mobilization in Arabidopsis thaliana plants exposed to copper. PeerJ, 9, e11373.
Abstract: Copper (Cu) is important for plant growth, but high concentrations can lead to detrimental effects such as primary root length inhibition, vegetative tissue chlorosis, and even plant death. The interaction between plant-soil microbiota and roots can potentially affect metal mobility and availability, and, therefore, overall plant metal concentration. Cupriavidus metallidurans CH34 is a multi metal-resistant bacterial model that alters metal mobility and bioavailability through ion pumping, metal complexation, and reduction processes. The interactions between strain CH34 and plants may affect the growth, metal uptake, and translocation of Arabidopsis thaliana plants that are exposed to or not exposed to Cu. In this study, we looked also at the specific gene expression changes in C. metallidurans when co-cultured with Cu-exposed A. thaliana. We found that A. thaliana's rosette area, primary and secondary root growth, and dry weight were affected by strain CH34, and that beneficial or detrimental effects depended on Cu concentration. An increase in some plant growth parameters was observed at copper concentrations lower than 50 mM and significant detrimental effects were found at concentrations higher than 50 mM Cu. We also observed up to a 90% increase and 60% decrease in metal accumulation and mobilization in inoculated A. thaliana. In turn, copper-stressed A. thaliana altered C. metallidurans colonization, and cop genes that encoded copper resistance in strain CH34 were induced by the combination of A. thaliana and Cu. These results reveal the complexity of the plant-bacteria-metal triad and will contribute to our understanding of their applications in plant growth promotion, protection, and phytoremediation strategies.
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Contreras, G. M. (2014). Stochastic volatility models at rho = +/- 1 as second class constrained Hamiltonian systems. Physica A, 405, 289–302.
Abstract: The stochastic volatility models used in the financial world are characterized, in the continuous-time case, by a set of two coupled stochastic differential equations for the underlying asset price S and volatility sigma. In addition, the correlations of the two Brownian movements that drive the stochastic dynamics are measured by the correlation parameter rho (-1 <= rho <= 1). This stochastic system is equivalent to the Fokker-Planck equation for the transition probability density of the random variables S and sigma. Solutions for the transition probability density of the Heston stochastic volatility model (Heston, 1993) were explored in Dragulescu and Yakovenko (2002), where the fundamental quantities such as the transition density itself, depend on rho in such a manner that these are divergent for the extreme limit rho = +/- 1. The same divergent behavior appears in Hagan et al. (2002), where the probability density of the SABR model was analyzed. In an option pricing context, the propagator of the bi-dimensional Black-Scholes equation was obtained in Lemmens et al. (2008) in terms of the path integrals, and in this case, the propagator diverges again for the extreme values rho = +/- 1. This paper shows that these similar divergent behaviors are due to a universal property of the stochastic volatility models in the continuum: all of them are second class constrained systems for the most extreme correlated limit rho = +/- 1. In this way, the stochastic dynamics of the rho = +/- 1 cases are different of the rho (1 <= rho <= 1) case, and it cannot be obtained as a continuous limit from the rho not equal +/- 1 regimen. This conclusion is achieved by considering the Fokker-Planck equation or the bi-dimensional Black-Scholes equation as a Euclidean quantum Schrodinger equation. Then, the analysis of the underlying classical mechanics of the quantum model, implies that stochastic volatility models at rho = +/- 1 correspond to a constrained system. To study the dynamics in an appropriate form, Dirac's method for constrained systems (Dirac, 1958, 1967) must be employed, and Dirac's analysis reveals that the constraints are second class. In order to obtain the transition probability density or the option price correctly, one must evaluate the propagator as a constrained Hamiltonian path-integral (Henneaux and Teitelboim, 1992), in a similar way to the high energy gauge theory models. In fact, for all stochastic volatility models, after integrating over momentum variables, one obtains an effective Euclidean Lagrangian path integral over the volatility alone. The role of the second class constraints is determining the underlying asset price S completely in terms of volatility, so it plays no role in the path integral. In order to examine the effect of the constraints on the dynamics for both extreme limits, the probability density function is evaluated by using semi-classical arguments, in an analogous manner to that developed in Hagan et al. (2002), for the SABR model. (C) 2014 Elsevier B.V. All rights reserved.
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Contreras, M., & Hojman, S. A. (2014). Option pricing, stochastic volatility, singular dynamics and constrained path integrals. Physica A, 393, 391–403.
Abstract: Stochastic volatility models have been widely studied and used in the financial world. The Heston model (Heston, 1993) [7] is one of the best known models to deal with this issue. These stochastic volatility models are characterized by the fact that they explicitly depend on a correlation parameter p which relates the two Brownian motions that drive the stochastic dynamics associated to the volatility and the underlying asset. Solutions to the Heston model in the context of option pricing, using a path integral approach, are found in Lemmens et al. (2008) [21] while in Baaquie (2007,1997) [12,13] propagators for different stochastic volatility models are constructed. In all previous cases, the propagator is not defined for extreme cases rho = +/- 1. It is therefore necessary to obtain a solution for these extreme cases and also to understand the origin of the divergence of the propagator. In this paper we study in detail a general class of stochastic volatility models for extreme values rho = +/- 1 and show that in these two cases, the associated classical dynamics corresponds to a system with second class constraints, which must be dealt with using Dirac's method for constrained systems (Dirac, 1958,1967) [22,23] in order to properly obtain the propagator in the form of a Euclidean Hamiltonian path integral (Henneaux and Teitelboim, 1992) [25]. After integrating over momenta, one gets an Euclidean Lagrangian path integral without constraints, which in the case of the Heston model corresponds to a path integral of a repulsive radial harmonic oscillator. In all the cases studied, the price of the underlying asset is completely determined by one of the second class constraints in terms of volatility and plays no active role in the path integral. (C) 2013 Elsevier B.V. All rights reserved.
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Contreras, M., & Pena, J. P. (2019). The quantum dark side of the optimal control theory. Physica A, 515, 450–473.
Abstract: In a recent article, a generic optimal control problem was studied from a physicist's point of view (Contreras et al. 2017). Through this optic, the Pontryagin equations are equivalent to the Hamilton equations of a classical constrained system. By quantizing this constrained system, using the right ordering of the operators, the corresponding quantum dynamics given by the Schrodinger equation is equivalent to that given by the Hamilton-Jacobi-Bellman equation of Bellman's theory. The conclusion drawn there were based on certain analogies between the equations of motion of both theories. In this paper, a closer and more detailed examination of the quantization problem is carried out, by considering three possible quantization procedures: right quantization, left quantization, and Feynman's path integral approach. The Bellman theory turns out to be the classical limit h -> 0 of these three different quantum theories. Also, the exact relation of the phase S(x, t) of the wave function Psi(x, t) = e(i/hS(x,t)) of the quantum theory with Bellman's cost function J(+)(x, t) is obtained. In fact, S(x, t) satisfies a 'conjugate' form of the Hamilton-Jacobi-Bellman equation, which implies that the cost functional J(+)(x, t) must necessarily satisfy the usual Hamilton-Jacobi-Bellman equation. Thus, the Bellman theory effectively corresponds to a quantum view of the optimal control problem. (C) 2018 Elsevier B.V. All rights reserved.
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Contreras, M., Pellicer, R., & Villena, M. (2017). Dynamic optimization and its relation to classical and quantum constrained systems. Physica A, 479, 12–25.
Abstract: We study the structure of a simple dynamic optimization problem consisting of one state and one control variable, from a physicist's point of view. By using an analogy to a physical model, we study this system in the classical and quantum frameworks. Classically, the dynamic optimization problem is equivalent to a classical mechanics constrained system, so we must use the Dirac method to analyze it in a correct way. We find that there are two second-class constraints in the model: one fix the momenta associated with the control variables, and the other is a reminder of the optimal control law. The dynamic evolution of this constrained system is given by the Dirac's bracket of the canonical variables with the Hamiltonian. This dynamic results to be identical to the unconstrained one given by the Pontryagin equations, which are the correct classical equations of motion for our physical optimization problem. In the same Pontryagin scheme, by imposing a closed-loop lambda-strategy, the optimality condition for the action gives a consistency relation, which is associated to the Hamilton-Jacobi-Bellman equation of the dynamic programming method. A similar result is achieved by quantizing the classical model. By setting the wave function Psi (x, t) = e(is(x,t)) in the quantum Schrodinger equation, a non-linear partial equation is obtained for the S function. For the right-hand side quantization, this is the Hamilton-Jacobi-Bellman equation, when S(x, t) is identified with the optimal value function. Thus, the Hamilton-Jacobi-Bellman equation in Bellman's maximum principle, can be interpreted as the quantum approach of the optimization problem. (C) 2017 Elsevier B.V. All rights reserved.
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Dorval, P., Talens, G. J. J., Otten, G. P. P. L., Brahm, R., Jordan, A., Torres, P., et al. (2020). MASCARA-4 b/bRing-1 b: A retrograde hot Jupiter around a bright A-type star. Astron. Astrophys., 635, 10 pp.
Abstract: Context. The Multi-site All-Sky CAmeRA (MASCARA) and bRing are both photometric ground-based instruments with multiple stations that rely on interline charge-coupled devices with wide-field lenses to monitor bright stars in the local sky for variability. MASCARA has already discovered several planets in the northern sky, which are among the brightest known transiting hot Jupiter systems. Aims. In this paper, we aim to characterize a transiting planetary candidate in the southern skies found in the combined MASCARA and bRing data sets of HD 85628, an A7V star of V = 8.2 mag at a distance 172 pc, to establish its planetary nature. Methods. The candidate was originally detected in data obtained jointly with the MASCARA and bRing instruments using a Box Least-Square search for transit events. Further photometry was taken by the 0.7 m Chilean-Hungarian Automated Telescope (CHAT), and radial velocity measurements with the Fiber Dual Echelle Optical Spectrograph on the European Southern Observatory 1.0 m Telescope. High-resolution spectra during a transit were taken with the CTIO high-resolution spectrometer (CHIRON) on the Small and Moderate Aperture Research Telescope System 1.5 m telescope to target the Doppler shadow of the candidate. Results. We confirm the existence of a hot Jupiter transiting the bright A7V star HD 85628, which we co-designate as MASCARA-4b and bRing-1b. It is in an orbit of 2.824 days, with an estimated planet radius of 1.53(-0.04)(+0.07) R-Jup and an estimated planet mass of 3.1 +/- 0.9 M-Jup, putting it well within the planetary regime. The CHAT observations show a partial transit, reducing the probability that the transit was around a faint background star. The CHIRON observations show a clear Doppler shadow, implying that the transiting object is in a retrograde orbit with |lambda| = 244.9(-3.6)(+2.7)degrees. The planet orbits at a distance of 0.047 +/- 0.004 AU from the star and has a zero-albedo equilibrium temperature of 2100 +/- 100 K. In addition, we find that HD 85628 has a previously unreported stellar companion star in the Gaia DR2 data demonstrating common proper motion and parallax at 4.3 '' separation (projected separation similar to 740 AU), and with absolute magnitude consistent with being a K/M dwarf. Conclusions. MASCARA-4 b/bRing-1 b is the brightest transiting hot Jupiter known to date in a retrograde orbit. It further confirms that planets in near-polar and retrograde orbits are more common around early-type stars. Due to its high apparent brightness and short orbital period, the system is particularly well suited for further atmospheric characterization.
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Dumett, M. A., & Cominetti, R. (2018). On The Stability Of An Adaptive Learning Dynamics In Traffic Games. J. Dyn. Games, 5(4), 265–282.
Abstract: This paper investigates the dynamic stability of an adaptive learning procedure in a traffic game. Using the Routh-Hurwitz criterion we study the stability of the rest points of the corresponding mean field dynamics. In the special case with two routes and two players we provide a full description of the number and nature of these rest points as well as the global asymptotic behavior of the dynamics. Depending on the parameters of the model, we find that there are either one, two or three equilibria and we show that in all cases the mean field trajectories converge towards a rest point for almost all initial conditions.
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Faes, M. G. R., Valdebenito, M. A., Yuan, X. K., Wei, P. F., & Beer, M. (2021). Augmented reliability analysis for estimating imprecise first excursion probabilities in stochastic linear dynamics. Adv. Eng. Softw., 155, 102993.
Abstract: Imprecise probability allows quantifying the level of safety of a system taking into account the effect of both aleatory and epistemic uncertainty. The practical estimation of an imprecise probability is usually quite demanding from a numerical viewpoint, as it is necessary to propagate separately both types of uncertainty, leading in practical cases to a nested implementation in the so-called double loop approach. In view of this issue, this contribution presents an alternative approach that avoids the double loop by replacing the imprecise probability problem by an augmented, purely aleatory reliability analysis. Then, with the help of Bayes' theorem, it is possible to recover an expression for the failure probability as an explicit function of the imprecise parameters from the augmented reliability problem, which ultimately allows calculating the imprecise probability. The implementation of the proposed framework is investigated within the context of imprecise first excursion probability estimation of uncertain linear structures subject to imprecisely defined stochastic quantities and crisp stochastic loads. The associated augmented reliability problem is solved within the context of Directional Importance Sampling, leading to an improved accuracy at reduced numerical costs. The application of the proposed approach is investigated by means of two examples. The results obtained indicate that the proposed approach can be highly efficient and accurate.
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Ferrada, F., Babonneau, F., Homem-de-Mello, T., & Jalil-Vega, F. (2022). Energy planning policies for residential and commercial sectors under ambitious global and local emissions objectives: A Chilean case study. J. Clean. Prod., 350, 131299.
Abstract: Chile is currently engaged in an energy transition process to meet ambitious greenhouse gas reductions and improved air quality indices. In this paper, we apply a long-term energy planning model, with the objective of finding the set of technologies that meet strong reductions of CO2 emissions and of local PM2.5 concentrations. For this purpose, we use the existing ETEM-Chile (Energy-Technology-Environment-Model) model which considers a simplified version of the Chilean electricity sector that we extend to the residential and commercial sectors and to local concentration considerations. We propose an original approach to integrate in the same framework local and global emission constraints. Results show that to meet the goal of zero emissions by 2050, electrification of end-use demands increases up to 49.2% with a strong growth of the CO2 marginal cost. It should be noted that this electrification rate is much lower than government projections and those usually found in the literature, in certain geographic areas in southern Chile with a wide availability of firewood for residential heating. Regarding local PM2.5 concentrations, our analysis shows that even without a specific emission reduction target, acceptable PM2.5 concentrations are achieved by 2045, due to first the emergence of more efficient, cleaner and cost-effective end-use technologies, in particular, residential firewood heaters, and second the use of drier and therefore less contaminating firewood. Achieving acceptable air quality as early as 2030 is also possible but comes with a high marginal cost of PM2.5 concentration. Our results illustrate the need for implementing effective public policies to (i) regulate the firewood heating market to increase its production and improve its environmental quality and (ii) incentivize the installation of efficient firewood heaters in the residential sector.
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Formenti, E., Goles, E., & Martin, B. (2012). Computational Complexity of Avalanches in the Kadanoff Sandpile Model. Fundam. Inform., 115(1), 107–124.
Abstract: This paper investigates the avalanche problem AP for the Kadanoff sandpile model (KSPM). We prove that (a slight restriction of) AP is in NC1 in dimension one, leaving the general case open. Moreover, we prove that AP is P-complete in dimension two. The proof of this latter result is based on a reduction from the monotone circuit value problem by building logic gates and wires which work with an initial sand distribution in KSPM. These results are also related to the known prediction problem for sandpiles which is in NC1 for one-dimensional sandpiles and P-complete for dimension 3 or higher. The computational complexity of the prediction problem remains open for the Bak's model of two-dimensional sandpiles.
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Goles, E., Lobos, F., Ruz, G. A., & Sene, S. (2020). Attractor landscapes in Boolean networks with firing memory: a theoretical study applied to genetic networks. Nat. Comput., 19(2), 295–319.
Abstract: In this paper we study the dynamical behavior of Boolean networks with firing memory, namely Boolean networks whose vertices are updated synchronously depending on their proper Boolean local transition functions so that each vertex remains at its firing state a finite number of steps. We prove in particular that these networks have the same computational power than the classical ones, i.e. any Boolean network with firing memory composed of m vertices can be simulated by a Boolean network by adding vertices. We also prove general results on specific classes of networks. For instance, we show that the existence of at least one delay greater than 1 in disjunctive networks makes such networks have only fixed points as attractors. Moreover, for arbitrary networks composed of two vertices, we characterize the delay phase space, i.e. the delay values such that networks admits limit cycles or fixed points. Finally, we analyze two classical biological models by introducing delays: the model of the immune control of the lambda\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\lambda $$\end{document}-phage and that of the genetic control of the floral morphogenesis of the plant Arabidopsis thaliana.
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Goles, E., Montealegre, P., & Rios-Wilson, 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 (non-directed) 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 non-polynomial 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 non-homogeneous 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 PSPACE-complete.
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Gordon, M. A., Vargas, F. J., & Peters, A. A. (2021). Comparison of Simple Strategies for Vehicular Platooning With Lossy Communication. IEEE Access, 9, 103996–104010.
Abstract: This paper studies vehicle platooning with communication channels subject to random data loss. We focus on homogeneous discrete-time platoons in a predecessor-following topology with a constant time headway policy. We assume that each agent in the platoon sends its current position to the immediate follower through a lossy channel modeled as a Bernoulli process. To reduce the negative effects of data loss over the string stability and performance of the platoon, we use simple strategies that modify the measurement, error, and control signals of the feedback control loop, in each vehicle, when a dropout occurs. Such strategies are based on holding the previous value, dropping to zero, or replacing with a prediction based on a simple linear extrapolation. We performed a simulation-based comparison among a set of different strategies, and found that some strategies are favorable in terms of performance, while some others present improvements for string stabilization. These results strongly suggest that proper design of compensation schemes for the communications of interconnected multi-agent systems plays an important role in their performance and their scalability properties.
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Hobson, M. J., Brahm, R., Jordan, A.., Espinoza, N., Kossakowski, D., Henning, T., et al. (2021). A Transiting Warm Giant Planet around the Young Active Star TOI-201. Astron. J., 161(5), 235.
Abstract: We present the confirmation of the eccentric warm giant planet TOI-201 b, first identified as a candidate in Transiting Exoplanet Survey Satellite photometry (Sectors 1-8, 10-13, and 27-28) and confirmed using groundbased photometry from Next Generation Transit Survey and radial velocities from FEROS, HARPS, CORALIE, and MINERVA-Australis. TOI-201 b orbits a young (0.87(-0.49)(+0.46)) and bright (V = 9.07 mag) F-type star with a 52.9781 day period. The planet has a mass of 0.42(-0.03)(+0.05) M-J, a radius of 1.008(-0.015)(+0.012) R-J, and an orbital eccentricity of 0.28(-0.09)(+0.06); it appears to still be undergoing fairly rapid cooling, as expected given the youth of the host star. The star also shows long-term variability in both the radial velocities and several activity indicators, which we attribute to stellar activity. The discovery and characterization of warm giant planets such as TOI-201 b are important for constraining formation and evolution theories for giant planets.
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Ibarra, C., O'Ryan, R., & Silva, B. (2018). Applying knowledge governance to understand the role of science in environmental regulation: The case of arsenic in Chile. Environ. Sci. Policy, 86, 115–124.
Abstract: The relationship between scientific knowledge and decision-making surrounding environmental issues is complex and represents a flourishing area of scholarship and practice. However, a sense of frustration persists regarding efforts to increase the use of science for decision-making. Regulations of copper smelter arsenic emissions developed in Chile during the 1990s represent a successful example of science informing policy making. The case involved production and use of local science in contrast to the common practice of copying international ambient standards. In this paper, we investigate arsenic regulation in Chile in the 1990s and focus on the role of the major science intervention during the process, project FONDEF 2-24. The case is examined through the lens of knowledge governance (van Kerkhoff and Pilbeam, 2017). This theoretically-oriented approach guides our critical reflection on the relationship between knowledge and policy making, taking into consideration the formal and informal rules that shape the intervention and the underlying social and cultural patterns. The success of the science intervention's influence on policy is better understood with such a perspective. We expand the knowledge governance approach by scrutinizing the relations of coherence between levels of analysis to assess their alignment. The approach could be helpful for studying other cases, particularly at times when a new field of policy is emerging.
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