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Antico, F. C., Concha-Riedel, J., Valdivia, I., García Herrera, C., & Utrera, A. (2023). The fracture mechanical behavior of the interface between animal fibers, mortar, and earth matrices. A theoretical and experimental approach. Compos. B. Eng., 254, 110568.
Abstract: Theoretical-experimental research is presented to address the mechanics and failure mode of the interface between two matrices with brittle behavior, earth and mortar, and pig hair, an organic fiber that is a massive waste from the food industry worldwide. A comprehensive statistical analysis of the pull-out force is presented, accounting for the effect of fiber embedded length, diameter variability, and age of the matrices. Experimental results are contrasted with fracture-mechanics theories to describe its behavior in this matter. Results show that neither fiber length, variability of diameter, nor the age of the matrix influences the pull-out force of both matrices evaluated in this work. Our results show the brittle nature of these interfaces, which was also observed using a high-speed camera. The tensile load of the fibers was compared to the pull-out force, showing that these fibers always work within their elastic regime. This work contributes directly to the sustainable goals 9, 11, and 15 enacted by the United Nations in 2015, by contributing to the understanding of the fracture mechanics of a waste product used as reinforcement of construction matrices.
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Araya, H., Bahamonde, N., Fermín, L., Roa, T., & Torres, S. (2023). ON THE CONSISTENCY OF LEAST SQUARES ESTIMATOR IN MODELS SAMPLED AT RANDOM TIMES DRIVEN BY LONG MEMORY NOISE: THE JITTERED CASE. Stat. Sin., 33, 331–351.
Abstract: In numerous applications, data are observed at random times. Our main purpose is to study a model observed at random times that incorporates a long-memory noise process with a fractional Brownian Hurst exponent H. We propose a least squares estimator in a linear regression model with long-memory noise and a random sampling time called “jittered sampling”. Specifically, there is a fixed sampling rate 1/N, contaminated by an additive noise (the jitter) and governed by a probability density function supported in [0, 1/N]. The strong consistency of the estimator is established, with a convergence rate depending on N and the Hurst exponent. A Monte Carlo analysis supports the relevance of the theory and produces additional insights, with several levels of long-range dependence (varying the Hurst index) and two different jitter densities.
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Araya, H., Bahamonde, N., Fermin, L., Roa, T., & Torres, S. (2023). ON THE CONSISTENCY OF THE LEAST SQUARES ESTIMATOR IN MODELS SAMPLED AT RANDOM TIMES DRIVEN BY LONG MEMORY NOISE: THE RENEWAL CASE. Stat. Sin., 33, 1–26.
Abstract: In this study, we prove the strong consistency of the least squares estimator in a random sampled linear regression model with long-memory noise and an independent set of random times given by renewal process sampling. Additionally, we illustrate how to work with a random number of observations up to time T = 1. A simulation study is provided to illustrate the behavior of the different terms, as well as the performance of the estimator under various values of the Hurst parameter H.
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Arias-Garzón, D., Tabares-Soto, R., Bernal-Salcedo. J., & Ruz, G. A. (2023). Biases associated with database structure for COVID-19 detection in X-ray images. Sci. Rep., 13, 3477.
Abstract: Several artificial intelligence algorithms have been developed for COVID-19-related topics. One that has been common is the COVID-19 diagnosis using chest X-rays, where the eagerness to obtain early results has triggered the construction of a series of datasets where bias management has not been thorough from the point of view of patient information, capture conditions, class imbalance, and careless mixtures of multiple datasets. This paper analyses 19 datasets of COVID-19 chest X-ray images, identifying potential biases. Moreover, computational experiments were conducted using one of the most popular datasets in this domain, which obtains a 96.19% of classification accuracy on the complete dataset. Nevertheless, when evaluated with the ethical tool Aequitas, it fails on all the metrics. Ethical tools enhanced with some distribution and image quality considerations are the keys to developing or choosing a dataset with fewer bias issues. We aim to provide broad research on dataset problems, tools, and suggestions for future dataset developments and COVID-19 applications using chest X-ray images.
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Aylwin, R., & Jerez-Hanckes, C. (2023). Finite-Element Domain Approximation for Maxwell Variational Problems on Curved Domains. SIAM J. Numer. Anal., Early Access.
Abstract: We consider the problem of domain approximation in finite element methods for Maxwell equations on curved domains, i.e., when affine or polynomial meshes fail to exactly cover the domain of interest. In such cases, one is forced to approximate the domain by a sequence of polyhedral domains arising from inexact meshes. We deduce conditions on the quality of these approximations that ensure rates of error convergence between discrete solutions -- in the approximate domains -- to the continuous one in the original domain.
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Aylwin, R., Jerez-Hanckes, C., Schwab, C., & Zech, J. (2023). Multilevel Domain Uncertainty Quantification in Computational Electromagnetics. Math. Models Methods Appl. Sci., Early Access.
Abstract: We continue our study [Domain Uncertainty Quantification in Computational Electromagnetics, JUQ (2020), 8:301--341] of the numerical approximation of time-harmonic electromagnetic fields for the Maxwell lossy cavity problem for uncertain geometries. We adopt the same affine-parametric shape parametrization framework, mapping the physical domains to a nominal polygonal domain with piecewise smooth maps. The regularity of the pullback solutions on the nominal domain is characterized in piecewise Sobolev spaces. We prove error convergence rates and optimize the algorithmic steering of parameters for edge-element discretizations in the nominal domain combined with: (a) multilevel Monte Carlo sampling, and (b) multilevel, sparse-grid quadrature for computing the expectation of the solutions with respect to uncertain domain ensembles. In addition, we analyze sparse-grid interpolation to compute surrogates of the domain-to-solution mappings. All calculations are performed on the polyhedral nominal domain, which enables the use of standard simplicial finite element meshes. We provide a rigorous fully discrete error analysis and show, in all cases, that dimension-independent algebraic convergence is achieved. For the multilevel sparse-grid quadrature methods, we prove higher order convergence rates which are free from the so-called curse of dimensionality, i.e. independent of the number of parameters used to parametrize the admissible shapes. Numerical experiments confirm our theoretical results and verify the superiority of the sparse-grid methods.
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Balocchi, F., Galleguillos, M., Rivera, D., Stehr, A., Arumi, J. L., Pizarro, R., et al. (2023). Forest hydrology in Chile: Past, present, and future. J. Hydrol., 616, 128681.
Abstract: This paper reviews the current knowledge of hydrological processes in Chilean temperate forests which extend along western South America from latitude 29 degrees S to 56 degrees S. This geographic region includes a diverse range of natural and planted forests and a broad sweep of vegetation, edaphic, topographic, geologic, and climatic set-tings which create a unique natural laboratory. Many local communities, endangered freshwater ecosystems, and downstream economic activities in Chile rely on water flows from forested catchments. This review aims to (i) provide a comprehensive overview of Chilean forest hydrology, to (ii) review prior research in forest hydrology in Chile, and to (iii) identify knowledge gaps and provide a vision for future research on forest hydrology in Chile. We reviewed the relation between native forests, commercial plantations, and other land uses on water yield and water quality from the plot to the catchment scale. Much of the global understanding of forests and their relationship with the water cycle is in line with the findings of the studies reviewed here. Streamflow from forested catchments increases after timber harvesting, native forests appear to use less water than plantations, and streams draining native forest yield less sediment than streams draining plantations or grassland/shrublands. We identified 20 key knowledge gaps such as forest groundwater systems, soil-plant-atmosphere interactions, native forest hydrology, and the effect of forest management and restoration on hydrology. Also, we found a paucity of research in the northern geographic areas and forest types (35-36 degrees S); most forest hydrology studies in Chile (56%) have been conducted in the southern area (Los Rios Region around 39-40 degrees S). There is limited knowledge of the geology and soils in many forested areas and how surface and groundwater are affected by changes in land cover. There is an opportunity to advance our understanding using process-based investigations linking field studies and modeling. Through the establishment of a forest hydrology science “society” to coor-dinate efforts, regional and national-scale land use planning might be supported. Our review ends with a vision to advance a cross-scale collaborative effort to use new nation-wide catchment-scale networks Long-term Ecosystem Research (LTER) sites, to promote common and
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Balocchi, F., Galleguillos, M., Rivera, D., Stehr, A., Arumi, J. L., Pizarro, R., et al. (2023). Forest Hydrology in Chile; paste, present, and future" (vol 616, 128681, 2023). J. Hydrol., 617(B), 129025.
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Bhat, S. M., Ahmed, S., Bahar, A. N., Wahid, K. A., Otsuki, A., & Singh, P. (2023). Design of Cost-Efficient SRAM Cell in Quantum Dot Cellular Automata Technology. Electronics, 12(2), 367.
Abstract: SRAM or Static Random-Access Memory is the most vital memory technology. SRAM is fast and robust but faces design challenges in nanoscale CMOS such as high leakage, power consumption, and reliability. Quantum-dot Cellular Automata (QCA) is the alternative technology that can be used to address the challenges of conventional SRAM. In this paper, a cost-efficient single layer SRAM cell has been proposed in QCA. The design has 39 cells with a latency of 1.5 clock cycles and achieves an overall improvement in cell count, area, latency, and QCA cost compared to the reported designs. It can therefore be used to design nanoscale memory structures of higher order.
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Caceres-Vasquez, J., Jara, D. H., Costamagna, J., Martinez-Gomez, F., Silva, C. P., Lemus, L., et al. (2023). Effect of non-covalent self-dimerization on the spectroscopic and electrochemical properties of mixed Cu(i) complexes. RSC Advances, 13(2), 825–838.
Abstract: A series of six new Cu(i) complexes with ([Cu(N-{4-R}pyridine-2-yl-methanimine)(PPh3)Br]) formulation, where R corresponds to a donor or acceptor p-substituent, have been synthesized and were used to study self-association effects on their structural and electrochemical properties. X-ray diffraction results showed that in all complexes the packing is organized from a dimer generated by supramolecular pi stacking and hydrogen bonding. H-1-NMR experiments at several concentrations showed that all complexes undergo a fast-self-association monomer-dimer equilibrium in solution, while changes in resonance frequency towards the high or low field in specific protons of the imine ligand allow establishing that dimers have similar structures to those found in the crystal. The thermodynamic parameters for this self-association process were calculated from dimerization constants determined by VT-H-1-NMR experiments for several concentrations at different temperatures. The values for K-D (4.0 to 70.0 M-1 range), Delta H (-1.4 to -2.6 kcal mol(-1) range), Delta S (-0.2 to 2.1 cal mol(-1) K-1 range), and Delta G(298) (-0.8 to -2.0 kcal mol(-1) range) are of the same order and indicate that the self-dimerization process is enthalpically driven for all complexes. The electrochemical profile of the complexes shows two redox Cu(ii)/Cu(i) processes whose relative intensities are sensitive to concentration changes, indicating that both species are in chemical equilibrium, with the monomer and the dimer having different electrochemical characteristics. We associate this behaviour with the structural lability of the Cu(i) centre that allows the monomeric molecules to reorder conformationally to achieve a more adequate assembly in the non-covalent dimer. As expected, structural properties in the solid and in solution, as well as their electrochemical properties, are not correlated with the electronic parameters usually used to evaluate R substituent effects. This confirms that the properties of the Cu(i) complexes are usually more influenced by steric effects than by the inductive effects of substituents of the ligands. In fact, the results obtained showed the importance of non-covalent inte
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Concha, M., & Ruz, G. A. (2023). Evaluation of Atmospheric Environmental Regulations: The Case of Thermoelectric Power Plants. Atmosphere, 14(2), 358.
Abstract: In Chile, the concept of sacrifice zones corresponds to those land surfaces in which industrial development was prioritized over the environmental impact that it caused. A high number of industries that emit pollutants into the environment are concentrated in these zones. This paper studies the atmospheric component of the Environmental Impact Declaration and Assessment’s (EID and EIA, respectively) environmental assessment instruments of the thermoelectric power plants in northern Chile, based on their consistency with current environmental quality regulations. We specify concepts on air quality, atmospheric emission regulations, and the critical parameters and factors to be considered when carrying out an environmental impact assessment. Finally, we end by presenting possible alternatives to replace the current methodologies and criteria for atmospheric regulation in areas identified as saturated or of environmental sacrifice, with an emphasis on both population health and an environmental approach.
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de la Cruz, R., Fuentes, C., & Padilla, O. (2023). A Bayesian Mixture Cure Rate Model for Estimating Short-Term and Long-Term Recidivism. Entropy, 25(1), 56.
Abstract: Mixture cure rate models have been developed to analyze failure time data where a proportion never fails. For such data, standard survival models are usually not appropriate because they do not account for the possibility of non-failure. In this context, mixture cure rate models assume that the studied population is a mixture of susceptible subjects who may experience the event of interest and non-susceptible subjects that will never experience it. More specifically, mixture cure rate models are a class of survival time models in which the probability of an eventual failure is less than one and both the probability of eventual failure and the timing of failure depend (separately) on certain individual characteristics. In this paper, we propose a Bayesian approach to estimate parametric mixture cure rate models with covariates. The probability of eventual failure is estimated using a binary regression model, and the timing of failure is determined using a Weibull distribution. Inference for these models is attained using Markov Chain Monte Carlo methods under the proposed Bayesian framework. Finally, we illustrate the method using data on the return-to-prison time for a sample of prison releases of men convicted of sexual crimes against women in England and Wales and we use mixture cure rate models to investigate the risk factors for long-term and short-term survival of recidivism.
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Dewitte, B., Concha, E., Saavedra, D., Pizarro, O., Martinez-Villalobos, C., Gushchina, D., et al. (2023). The ENSO-induced South Pacific Meridional Mode. Front. clim., 4, 18 pp.
Abstract: Previous studies have investigated the role of the Pacific meridional mode (PMM), a climate mode of the mid-latitudes in the Northern and Southern Hemisphere, in favoring the development of the El Niño Southern Oscillation (ENSO). However little is known on how ENSO can influence the development of the PMM. Here we investigate the relationship between ENSO and the South Pacific Meridional Mode (SPMM) focusing on strong SPMM events that follows strong El Niño events. This type of events represents more than 60% of such events in the observational record and the historical simulations of the CESM Large ensemble (CESM-LE). It is first shown that such a relationship is rather stationary in both observations and the CESM-LE. Our analyses further reveal that strong SPMM events are associated with a coastal warming o northern central Chile peaking in Austral winter resulting from the propagation of waves forced at the equator during the development of El Niño events. The time delay between the ENSO peak (Boreal winter) and this coastal warming (Austral winter) can be understood in terms of the diferential contribution of the equatorially-forced propagating baroclinic waves to the warming along
the coast. In particular, the diference in phase speeds of the waves (the
high-order mode the wave the slower) implies that they do not overlap along their propagation south of 20◦S. This contributes to the persistence of warm coastal SST anomalies o Central Chile until the Austral summer following the concurrent El Niño event. This coastal warming is favorable to the development of strong SPMM events as the South Pacific Oscillation become active during that season. The analysis of the simulations of the Coupled Intercomparison Project phases 5 and 6 (CMIP5/6) indicates that very few models realistically simulate this ENSO/SPMM relationship and associated oceanic teleconnection.
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Ding, C., Dang, C., Valdebenito, M. A., Faes, M. G. R., Broggi, M., & Beer, M. (2023). First-passage probability estimation of high-dimensional nonlinear stochastic dynamic systems by a fractional moments-based mixture distribution approach. Mech. Syst. Sig. Process., 185, 109775.
Abstract: First-passage probability estimation of high-dimensional nonlinear stochastic dynamic systems is a significant task to be solved in many science and engineering fields, but remains still an open challenge. The present paper develops a novel approach, termed 'fractional moments-based mixture distribution', to address such challenge. This approach is implemented by capturing the extreme value distribution (EVD) of the system response with the concepts of fractional moment and mixture distribution. In our context, the fractional moment itself is by definition a high-dimensional integral with a complicated integrand. To efficiently compute the fractional moments, a parallel adaptive sampling scheme that allows for sample size extension is developed using the refined Latinized stratified sampling (RLSS). In this manner, both variance reduction and parallel computing are possible for evaluating the fractional moments. From the knowledge of low-order fractional moments, the EVD of interest is then expected to be reconstructed. Based on introducing an extended inverse Gaussian distribution and a log extended skew-normal distribution, one flexible mixture distribution model is proposed, where its fractional moments are derived in analytic form. By fitting a set of fractional moments, the EVD can be recovered via the proposed mixture model. Accordingly, the first-passage probabilities under different thresholds can be obtained from the recovered EVD straightforwardly. The performance of the proposed method is verified by three examples consisting of two test examples and one engineering problem.
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Feuilloley, L., Fraigniaud, P., Montealegre, P., Rapaport, I., Remila, E., & Todinca, I. (2023). Local certification of graphs with bounded genus. Discret Appl. Math., 325, 9–36.
Abstract: Naor, Parter, and Yogev [SODA 2020] recently designed a compiler for automatically translating standard centralized interactive protocols to distributed interactive protocols, as introduced by Kol, Oshman, and Saxena [PODC 2018]. In particular, by using this compiler, every linear-time algorithm for deciding the membership to some fixed graph class can be translated into a dMAM(O(log n)) protocol for this class, that is, a distributed interactive protocol with O(log n)-bit proof size in n-node graphs, and three interactions between the (centralized) computationally-unbounded but non-trustable prover Merlin, and the (decentralized) randomized computationally-limited verifier Arthur. As a corol-lary, there is a dMAM(O(log n)) protocol for recognizing the class of planar graphs, as well as for recognizing the class of graphs with bounded genus.We show that there exists a distributed interactive protocol for recognizing the class of graphs with bounded genus performing just a single interaction, from the prover to the verifier, yet preserving proof size of O(log n) bits. This result also holds for the class of graphs with bounded non-orientable genus, that is, graphs that can be embedded on a non-orientable surface of bounded genus. The interactive protocols described in this paper are actually proof-labeling schemes, i.e., a subclass of interactive protocols, previously introduced by Korman, Kutten, and Peleg [PODC 2005]. In particular, these schn be computed a priori, at low cost, by the nodes themselves. Our results thus extend the recent proof-labeling scheme for planar graphs by Feuilloley et al. [PODC 2020], to graphs of bounded genus, and to graphs of bounded non-orientable genus.
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Fina, M., Lauff, C., Faes, M. G. R., Valdebenito, M. A., Wagner, W., & Freitag, S. (2023). Bounding imprecise failure probabilities in structural mechanics based on maximum standard deviation. Struct. Saf., 101, 102293.
Abstract: This paper proposes a framework to calculate the bounds on failure probability of linear structural systems whose performance is affected by both random variables and interval variables. This kind of problems is known to be very challenging, as it demands coping with aleatoric and epistemic uncertainty explicitly. Inspired by the framework of the operator norm theorem, it is proposed to consider the maximum standard deviation of the structural response as a proxy for detecting the crisp values of the interval parameters, which yield the bounds of the failure probability. The scope of application of the proposed approach comprises linear structural systems, whose properties may be affected by both aleatoric and epistemic uncertainty and that are subjected to (possibly imprecise) Gaussian loading. Numerical examples indicate that the application of such proxy leads to substantial numerical advantages when compared to a traditional double-loop approach for coping with imprecise failure probabilities. In fact, the proposed framework allows to decouple the propagation of aleatoric and epistemic uncertainty.
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Goles, E., Leal, L., Montealegre, P., Rapaport, I., & Rios-Wilson, M. (2023). Distributed maximal independent set computation driven by finite-state dynamics. Int. J. Parallel Emergent Distrib. Syst., Early Access.
Abstract: A Maximal Independent Set (MIS) is an inclusion maximal set of pairwise non-adjacent vertices. The computation of an MIS is one of the core problems in distributed computing. In this article, we introduce and analyze a finite-state distributed randomized algorithm for computing a Maximal Independent Set (MIS) on arbitrary undirected graphs. Our algorithm is self-stabilizing (reaches a correct output on any initial configuration) and can be implemented on systems with very scarce conditions. We analyze the convergence time of the proposed algorithm, showing that in many cases the algorithm converges in logarithmic time with high probability.
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Herrera, M. N. (2023). The contribution of the Chilean mining industry to the achievement of the 17 sustainable development goals. Geosystem Eng., Early Access.
Abstract: Chile is a world leader in copper production and is expected to reach production of around 6,237,000 tons of fine copper by 2022. On the other hand, in 2021 the production of copper by the hydrometallurgical route reached 1,509,000 tons and that of the smelting and refining route was 4,606,000 tons. Considering this production scenario, this article describes in a general way the contributions that the Chilean mining industry has made to the fulfillment of the 17 sustainable development goals, SDGs. The main advances are highlighted, besides discussing the main pending tasks to comply with the commitments made by Chile towards the international community.
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Jerez-Hanckes, C., Martínez, I. A., Pettersson, I., & Rybalko, V. (2023). Derivation of a bidomain model for bundles of myelinated axons. Nonlinear Anal.-Real World Appl., 70, 103789.
Abstract: The work concerns the multiscale modeling of a nerve fascicle of myelinated axons. We present a rigorous derivation of a macroscopic bidomain model describing the behavior of the electric potential in the fascicle based on the FitzHugh-Nagumo membrane dynamics. The approach is based on the two-scale convergence machinery combined with the method of monotone operators.
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Morales-Navarrete, D., Bevilacqua, M., Caamano-Carrillo, C., & Castro, L. M. (2023). Modeling Point Referenced Spatial Count Data: A Poisson Process Approach. J. Am. Stat. Assoc., Early Access.
Abstract: Random fields are useful mathematical tools for representing natural phenomena with complex dependence structures in space and/or time. In particular, the Gaussian random field is commonly used due to its attractive properties and mathematical tractability. However, this assumption seems to be restrictive when dealing with counting data. To deal with this situation, we propose a random field with a Poisson marginal distribution considering a sequence of independent copies of a random field with an exponential marginal distribution as “inter-arrival times ” in the counting renewal processes framework. Our proposal can be viewed as a spatial generalization of the Poisson counting process. Unlike the classical hierarchical Poisson Log-Gaussian model, our proposal generates a (non)-stationary random field that is mean square continuous and with Poisson marginal distributions. For the proposed Poisson spatial random field, analytic expressions for the covariance function and the bivariate distribution are provided. In an extensive simulation study, we investigate the weighted pairwise likelihood as a method for estimating the Poisson random field parameters. Finally, the effectiveness of our methodology is illustrated by an analysis of reindeer pellet-group survey data, where a zero-inflated version of the proposed model is compared with zero-inflated Poisson Log-Gaussian and Poisson Gaussian copula models. for this article, including technical proofs and R code for reproducing the work, are available as an online supplement.
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