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Araya-Letelier, G., Parra, P. F., Lopez-Garcia, D., Garcia-Valdes, A., Candia, G., & Lagos, R. (2019). Collapse risk assessment of a Chilean dual wall-frame reinforced concrete office building. Eng. Struct., 183, 770–779.
Abstract: Several code-conforming reinforced concrete buildings were severely damaged during the 2010 moment magnitude (M-w) 8.8 Chile earthquake, raising concerns about their real collapse margin. Although critical updates were introduced into the Chilean design codes after 2010, guidelines for collapse risk assessment of Chilean buildings remain insufficient. This study evaluates the collapse potential of a typical dual system (shear walls and moment frames) office building in Santiago. Collapse fragility functions were obtained through incremental dynamic analyses using a state-of-the-art finite element model of the building. Site-specific seismic hazard curves were developed, which explicitly incorporated epistemic uncertainty, and combined with the collapse fragility functions to estimate the mean annual frequency of collapse (lambda(c)) values and probabilities of collapse in 50-years (P-c(50)). Computed values of lambda(c) and P-c(50) were on the order of 10(-5)-10(-4), and 0.1-0.7%, respectively, consistent with similar studies developed for buildings in the US. The results also showed that the deaggregation of lambda(c) was controlled by small to medium earthquake intensities and that different models of the collapse fragility functions and hazard curves had a non-negligible effect on lambda(c) and P-c(50), and thus, propagation of uncertainty in risk assessment problems must be adequately taken into account.
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Benitez-Llambay, P., Krapp, L., Ramos, X. S., & Kratter, K. M. (2023). RAM: Rapid Advection Algorithm on Arbitrary Meshes. Astron. J., 952(2), 106.
Abstract: The study of many astrophysical flows requires computational algorithms that can capture high Mach number flows, while resolving a large dynamic range in spatial and density scales. In this paper we present a novel method, RAM: Rapid Advection Algorithm on Arbitrary Meshes. RAM is a time-explicit method to solve the advection equation in problems with large bulk velocity on arbitrary computational grids. In comparison with standard upwind algorithms, RAM enables advection with larger time steps and lower truncation errors. Our method is based on the operator splitting technique and conservative interpolation. Depending on the bulk velocity and resolution, RAM can decrease the numerical cost of hydrodynamics by more than one order of magnitude. To quantify the truncation errors and speed-up with RAM, we perform one- and two-dimensional hydrodynamics tests. We find that the order of our method is given by the order of the conservative interpolation and that the effective speed-up is in agreement with the relative increment in time step. RAM will be especially useful for numerical studies of disk-satellite interaction, characterized by high bulk orbital velocities and nontrivial geometries. Our method dramatically lowers the computational cost of simulations that simultaneously resolve the global disk and potential well inside the Hill radius of the secondary companion.
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Cataldo-Born, M., Araya-Letelier, G., & Pabon, C. (2016). Obstacles and motivations for earthbag social housing in Chile: energy, environment, economic and codes implications. Rev. Constr., 15(3), 17–26.
Abstract: Chile presents a social housing deficit that needs to be addressed with solutions that increase habitability and environmental benefits. This paper addresses the benefits of implementing earthbag buildings as an option to mitigate the existing social housing deficit in Chile. A literature review presents details on the use of earthbag buildings around the world, and motivations and obstacles for implementing earthbag buildings in Chile. In particular, a case study was simulated to compare an earthbag social house to a reinforced brick masonry social house in terms of environmental and economic performances such as CO2 emissions, energy and costs. It is concluded that both alternatives generate similar CO2 emissions, but the earthbag social house can save up to 20% of energy during its life cycle. In economic terms, the earthbag social house generates savings of 50% and 38% for initial investment and life cycle cost, respectively, compared to the reinforced brick masonry social house. The implementation of earthbag social housing projects would be encouraged by the development of a Chilean building code for earthbag design that provides guidance on the safe use of this technique in a seismic country.
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Ferran, S., Beghelli, A., Huerta-Canepa, G., & Jensen, F. (2018). Correctness assessment of a crowdcoding project in a computer programming introductory course. Comput. Appl. Eng. Educ., 26(1), 162–170.
Abstract: Crowdcoding is a programming model that outsources a software project implementation to the crowd. As educators, we think that crowdcoding could be leveraged as part of the learning path of engineering students from a computer programming introductory course to solve local community problems. The benefits are twofold: on the one hand the students practice the concepts learned in class and, on the other hand, they participate in real-life problems. Nevertheless, several challenges arise when developing a crowdcoding platform, the first one being how to check the correctness of student's code without giving an extra burden to the professors in the course. To overcome this issue, we propose a novel system that does not resort to expert review; neither requires knowing the right answers beforehand. The proposed scheme automatically clusters the student's codes based solely on the output they produce. Our initial results show that the largest cluster contains the same codes selected as correct by the automated and human testing, as long as some conditions apply.
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Hobson, M. J., Trifonov, T., Henning, T., Jordan, A., Rojas, F., Espinoza, N., et al. (2023). Alert Results TOI-199 b: A Well-characterized 100 day Transiting Warm Giant Planet with TTVs Seen from Antarctica 41 of 41 TOI-199 b: A Well-characterized 100 day Transiting Warm Giant Planet with TTVs Seen from Antarctica. Astron. J., 166(5), 201.
Abstract: We present the spectroscopic confirmation and precise mass measurement of the warm giant planet TOI-199 b. This planet was first identified in TESS photometry and confirmed using ground-based photometry from ASTEP in Antarctica including a full 6.5 hr long transit, PEST, Hazelwood, and LCO; space photometry from NEOSSat; and radial velocities (RVs) from FEROS, HARPS, CORALIE, and CHIRON. Orbiting a late G-type star, TOI-199 b has a 104.854-0.002+0.001day period, a mass of 0.17 +/- 0.02 M J, and a radius of 0.810 +/- 0.005 R J. It is the first warm exo-Saturn with a precisely determined mass and radius. The TESS and ASTEP transits show strong transit timing variations (TTVs), pointing to the existence of a second planet in the system. The joint analysis of the RVs and TTVs provides a unique solution for the nontransiting companion TOI-199 c, which has a period of 273.69-0.22+0.26days and an estimated mass of 0.28-0.01+0.02MJ . This period places it within the conservative habitable zone.
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Holguin-Garcia, S. A., Guevara-Navarro, E., Daza-Chica, A. E., Patiño-Claro, M. A., Arteaga-Arteaga, H. B., Ruz, G. A., et al. (2024). A comparative study of CNN-capsule-net, CNN-transformer encoder, and Traditional machine learning algorithms to classify epileptic seizure. BMC Med. Inform. Decis. Mak., 24(1), 60.
Abstract: IntroductionEpilepsy is a disease characterized by an excessive discharge in neurons generally provoked without any external stimulus, known as convulsions. About 2 million people are diagnosed each year in the world. This process is carried out by a neurological doctor using an electroencephalogram (EEG), which is lengthy.MethodTo optimize these processes and make them more efficient, we have resorted to innovative artificial intelligence methods essential in classifying EEG signals. For this, comparing traditional models, such as machine learning or deep learning, with cutting-edge models, in this case, using Capsule-Net architectures and Transformer Encoder, has a crucial role in finding the most accurate model and helping the doctor to have a faster diagnosis.ResultIn this paper, a comparison was made between different models for binary and multiclass classification of the epileptic seizure detection database, achieving a binary accuracy of 99.92% with the Capsule-Net model and a multiclass accuracy with the Transformer Encoder model of 87.30%.Conclusion Artificial intelligence is essential in diagnosing pathology. The comparison between models is helpful as it helps to discard those that are not efficient. State-of-the-art models overshadow conventional models, but data processing also plays an essential role in evaluating the higher accuracy of the models.
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Ruffino, B., Campo, G., Crutchik, D., Reyes, A., & Zanetti, M. (2022). Drinking Water Supply in the Region of Antofagasta (Chile): A Challenge between Past, Present and Future. Int. J. Environ. Res. Public Health, 19(21), 14406.
Abstract: Since the mid-nineteen century, when the first mining companies were established in the region of Antofagasta to extract saltpeter, mining managers and civil authorities have always had to face a number of problems to secure a water supply sufficient for the development of industrial activities and society. The unique features of the region, namely the scarcity of rainfall, the high concentration of arsenic in freshwaters and the increasing pressure of the mining sector, have made the supply of drinking water for local communities a challenge. In the 1950s, the town of Antofagasta experienced a serious drinking water crisis. The 300 km long aqueduct starting from the Toconce catchment, opened in 1958, temporarily ended this shortage of drinking water but created an even more dramatic problem. The concentration of arsenic in the water consumed by the population had grown by approx. ten times, reaching the value of 0.860 mg/L and seriously affecting people's health. The water treatment plants (WTPs) which were installed starting from the 1970s in the region (namely the Old and New Salar del Carmen in Antofagasta and Cerro Topater in Calama, plus the two recent desalination plants in Antofagasta and Tocopilla), have ensured, since 2014, that the drinking water coverage in the urban areas was practically universal (>99.9%). However, the rural areas have continued to experience significant shortcomings regarding their capacity to ensure the quality and continuity of the water supply service in the long run. Presently, approx. 42% of the rural population of the region of Antofagasta does not have a formal supply of drinking water. The recent amendments to the Chilean Water Code (March 2022) and the interventions carried out in the framework of the Agua Potable Rural (APR) program were intended to reduce the socio-ecological inequalities due to the lack of drinking water in the semi-concentrated and isolated rural population.
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