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Arango Hoyos, B. E., Franco Osorio, H., Valencia Gomez, E. K., Guerrero Sanchez, J., Del Canto Palominos, A. P., Larrain, F. A., et al. (2023). Exploring the capture and desorption of CO2 on graphene oxide foams supported by computational calculations. Sci. Rep., 13(1), 14476.
Abstract: In the last decade, the highest levels of greenhouse gases (GHG) in the atmosphere have been recorded, with carbon dioxide (CO2) being one of the GHGs that most concerns mankind due to the rate at which it is generated on the planet. Given its long time of permanence in the atmosphere (between 100 to 150 years); this has deployed research in the scientific field focused on the absorption and desorption of CO2 in the atmosphere. This work presents the study of CO2 adsorption employing
materials based on graphene oxide (GO), such as GO foams with different oxidation percentages (3.00%, 5.25%, and 9.00%) in their structure, obtained via an environmentally friendly method. The characterization of CO2 adsorption was carried out in a closed system, within which were placed the GO foams and other CO2 adsorbent materials (zeolite and silica gel). Through a controlled chemical reaction, production of CO2 was conducted to obtain CO2 concentration curves inside the system and calculate from these the efficiency, obtained between 86.28 and 92.20%, yield between 60.10 and 99.50%, and effectiveness of CO2 adsorption of the materials under study. The results obtained suggest that GO foams are a promising material for carbon capture and the future development of a new clean technology, given their highest CO2 adsorption efficiency and yield.
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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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Avudaiappan, S., Moreno, P. I. C., Montoya, R. L. F., Chávez-Delgado, M., Arunachalam, K. P., Guindos, P., et al. (2023). Experimental investigation on the physical, microstructural, and mechanical properties of hemp limecrete. Sci. Rep., 13(1), 22650.
Abstract: This paper investigates the hemp limecrete mechanical and microstructural performance of a new sustainable and environmental friendly building material. Several studies have investigated the hemp limecrete focusing on the non-structural applications. The newly developed hemp limecrete consists of high mechanical and microstructural properties. The specimens were prepared with varying lengths and proportions of hemp fibers with lime and tested for compressive strength, flexural strength, thermal conductivity and microstructural analysis like SEM and EDS. The study found that the optimal fiber content for making mortars was between 2 and 4%. This conclusion was reached after analyzing the influence of fiber length and ratio on the properties of the mortars. The dry unit weight decreased when the fiber content was higher than 4%. In terms of strength, the study found that the flexural strength of the hemp limecrete improved with an increase in fiber ratio, but the compressive strength decreased. However, with 2% hemp fiber, compressive strengths of 3.48 MPa and above were obtained. The study also highlighted the good thermal insulation properties and dimensional stability of hemp limecrete. These findings have important implications for the use of hemp limecrete as a sustainable building material. The results suggest that hemp limecrete has the potential to be a viable alternative to conventional concrete in specific applications, particularly in areas where environmental sustainability is a priority.
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Cabrera, M., Cordova-Lepe, F., Gutierrez-Jara, J. P. -, & Vogt-Geisse, K. (2021). An SIR-type epidemiological model that integrates social distancing as a dynamic law based on point prevalence and socio-behavioral factors. Sci. Rep., 11(1), 10170.
Abstract: Modeling human behavior within mathematical models of infectious diseases is a key component to understand and control disease spread. We present a mathematical compartmental model of Susceptible-Infectious-Removed to compare the infected curves given by four different functional forms describing the transmission rate. These depend on the distance that individuals keep on average to others in their daily lives. We assume that this distance varies according to the balance between two opposite thrives: the self-protecting reaction of individuals upon the presence of disease to increase social distancing and their necessity to return to a culturally dependent natural social distance that occurs in the absence of disease. We present simulations to compare results for different society types on point prevalence, the peak size of a first epidemic outbreak and the time of occurrence of that peak, for four different transmission rate functional forms and parameters of interest related to distancing behavior, such as: the reaction velocity of a society to change social distance during an epidemic. We observe the vulnerability to disease spread of close contact societies, and also show that certain social distancing behavior may provoke a small peak of a first epidemic outbreak, but at the expense of it occurring early after the epidemic onset, observing differences in this regard between society types. We also discuss the appearance of temporal oscillations of the four different transmission rates, their differences, and how this oscillatory behavior is impacted through social distancing; breaking the unimodality of the actives-curve produced by the classical SIR-model.
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Escapil-Inchauspe, P., & Ruz, G. A. (2023). h-Analysis and data-parallel physics-informed neural networks. Sci. Rep., 13(1), 17562.
Abstract: We explore the data-parallel acceleration of physics-informed machine learning (PIML) schemes, with a focus on physics-informed neural networks (PINNs) for multiple graphics processing units (GPUs) architectures. In order to develop scale-robust and high-throughput PIML models for sophisticated applications which may require a large number of training points (e.g., involving complex and high-dimensional domains, non-linear operators or multi-physics), we detail a novel protocol based on h-analysis and data-parallel acceleration through the Horovod training framework. The protocol is backed by new convergence bounds for the generalization error and the train-test gap. We show that the acceleration is straightforward to implement, does not compromise training, and proves to be highly efficient and controllable, paving the way towards generic scale-robust PIML. Extensive numerical experiments with increasing complexity illustrate its robustness and consistency, offering a wide range of possibilities for real-world simulations.
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Gazitua, M. C., Morgante, V., Poupin, M. J., Ledger, T., Rodriguez-Valdecantos, G., Herrera, C., et al. (2021). The microbial community from the early-plant colonizer (Baccharis linearis) is required for plant establishment on copper mine tailings. Sci. Rep., 11(1), 10448.
Abstract: Plants must deal with harsh environmental conditions when colonizing abandoned copper mine tailings. We hypothesized that the presence of a native microbial community can improve the colonization of the pioneer plant, Baccharis linearis, in soils from copper mining tailings. Plant growth and microbial community compositions and dynamics were determined in cultivation pots containing material from two abandoned copper mining tailings (Huana and Tambillos) and compared with pots containing fresh tailings or surrounding agricultural soil. Controls without plants or using irradiated microbe-free substrates, were also performed. Results indicated that bacteria (Actinobacteria, Gammaproteobacteria, and Firmicutes groups) and fungi (Glomus genus) are associated with B. linearis and may support plant acclimation, since growth parameters decreased in both irradiated (transiently without microbial community) and fresh tailing substrates (with a significantly different microbial community). Consistently, the composition of the bacterial community from abandoned copper mining tailings was more impacted by plant establishment than by differences in the physicochemical properties of the substrates. Bacteria located at B. linearis rhizoplane were clearly the most distinct bacterial community compared with those of fresh tailings, surrounding soil and non-rhizosphere abandoned tailings substrates. Beta diversity analyses showed that the rhizoplane bacterial community changed mainly through species replacement (turnover) than species loss (nestedness). In contrast, location/geographical conditions were more relevant than interaction with the plants, to explain fungal community differences.
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Goles, E., Mascareno, A., Medina, P., & Rica, S. (2020). Migration-induced transition in social structures: a view through the Sakoda model of social interactions. Sci. Rep., 10(1), 18338.
Abstract: We study the dynamics of three populations evolving in a two-dimensional discrete grid according to rules of attraction, rejection, or indifference following the framework of the seminal model by Sakoda and we apply it to migration phenomena. An interesting feature of the Sakoda model is the existence of a Potts-like energy which, as a common principle, decreases as time passes by. Here we consider the evolution of two populations until stabilization, then, we perturb this attractor by the inclusion of a third arrival: the immigrants. We show the conditions under which this irruption does not alter significantly the previous attractor (a sociological morphostatic behaviour) or it is dramatically changed (morphogenetic behaviour). We observe empirically that for a morphostatic behaviour the energy decreases while for morphogenesis this energy increases, revealing an escalation of social tension.
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Goles, E., Medina, P., & Santivanez, J. (2023). Majority networks and local consensus algorithm. Sci. Rep., 13(1), 1858.
Abstract: In this paper, we study consensus behavior based on the local application of the majority consensus algorithm (a generalization of the majority rule) over four-connected bi-dimensional networks. In this context, we characterize theoretically every four-vicinity network in its capacity to reach consensus (every individual at the same opinion) for any initial configuration of binary opinions. Theoretically, we determine all regular grids with four neighbors in which consensus is reached and in which ones not. In addition, in those instances in which consensus is not reached, we characterize statistically the proportion of configurations that reach spurious fixed points from an ensemble of random initial configurations. Using numerical simulations, we also analyze two observables of the system to characterize the algorithm: (1) the quality of the achieved consensus, that is if it respects the initial majority of the network; and (2) the consensus time, measured as the average amount of steps to reach convergence.
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Gutierrez-Jara, J. P., Vogt-Geisse, K., Cabrera, M., Cordova-Lepe, F., & Munoz-Quezada, M. T. (2022). Effects of human mobility and behavior on disease transmission in a COVID-19 mathematical model. Sci. Rep., 12(1), 10840.
Abstract: Human interactions and perceptions about health risk are essential to understand the evolution over the course of a pandemic. We present a Susceptible-Exposed-Asymptomatic-Infectious-Recovered-Susceptible mathematical model with quarantine and social-distance-dependent transmission rates, to study COVID-19 dynamics. Human activities are split across different location settings: home, work, school, and elsewhere. Individuals move from home to the other locations at rates dependent on their epidemiological conditions and maintain a social distancing behavior, which varies with their location. We perform simulations and analyze how distinct social behaviors and restrictive measures affect the dynamic of the disease within a population. The model proposed in this study revealed that the main focus on the transmission of COVID-19 is attributed to the “home” location setting, which is understood as family gatherings including relatives and close friends. Limiting encounters at work, school and other locations will only be effective if COVID-19 restrictions occur simultaneously at all those locations and/or contact tracing or social distancing measures are effectively and strictly implemented, especially at the home setting.
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Han, Z. Y., Chen, H., He, C. L., Dodbiba, G., Otsuki, A., Wei, Y. Z., et al. (2023). Nanobubble size distribution measurement by interactive force apparatus under an electric field. Sci. Rep., 13(1), 3663.
Abstract: Nanobubbles have been applied in many fields, such as environmental cleaning, material production, agriculture, and medicine. However, the measured nanobubble sizes differed among the measurement methods, such as dynamic light scattering, particle trajectory, and resonance mass methods. Additionally, the measurement methods were limited with respect to the bubble concentration, refractive index of liquid, and liquid color. Here, a novel interactive force measurement method for bulk nanobubble size measurement was developed by measuring the force between two electrodes filled with bulk nanobubble-containing liquid under an electric field when the electrode distance was changed in the nm scale with piezoelectric equipment. The nanobubble size was measured with a bubble gas diameter and also an effective water thin film layer covered with a gas bubble that was estimated to be approximately 10 nm based on the difference between the median diameter of the particle trajectory method and this method. This method could also be applied to the solid particle size distribution measurement in a solution.
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Lagos, N. A., Benitez, S., Grenier, C., Rodriguez-Navarro, A. B., Garcia-Herrera, C., Abarca-Ortega, A., et al. (2021). Plasticity in organic composition maintains biomechanical performance in shells of juvenile scallops exposed to altered temperature and pH conditions. Sci. Rep., 11(1), 24201.
Abstract: The exposure to environmental variations in pH and temperature has proven impacts on benthic ectotherms calcifiers, as evidenced by tradeoffs between physiological processes. However, how these stressors affect structure and functionality of mollusk shells has received less attention. Episodic events of upwelling of deep cold and low pH waters are well documented in eastern boundary systems and may be stressful to mollusks, impairing both physiological and biomechanical performance. These events are projected to become more intense, and extensive in time with ongoing global warming. In this study, we evaluate the independent and interactive effects of temperature and pH on the biomineral and biomechanical properties of Argopecten purpuratus scallop shells. Total organic matter in the shell mineral increased under reduced pH (similar to 7.7) and control conditions (pH similar to 8.0). The periostracum layer coating the outer shell surface showed increased protein content under low pH conditions but decreasing sulfate and polysaccharides content. Reduced pH negatively impacts shell density and increases the disorder in the orientation of calcite crystals. At elevated temperatures (18 degrees C), shell microhardness increased. Other biomechanical properties were not affected by pH/temperature treatments. Thus, under a reduction of 0.3 pH units and low temperature, the response of A. purpuratus was a tradeoff among organic compounds (biopolymer plasticity), density, and crystal organization (mineral plasticity) to maintain shell biomechanical performance, while increased temperature ameliorated the impacts on shell hardness. Biopolymer plasticity was associated with ecophysiological performance, indicating that, under the influence of natural fluctuations in pH and temperature, energetic constraints might be critical in modulating the long-term sustainability of this compensatory mechanism.
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Martinez-Villalobos, C., & Neelin, J. D. (2023). Regionally high risk increase for precipitation extreme events under global warming. Sci. Rep., 13, 5579.
Abstract: Daily precipitation extremes are projected to intensify with increasing moisture under global warming following the Clausius-Clapeyron (CC) relationship at about 7%/∘C
. However, this increase is not spatially homogeneous. Projections in individual models exhibit regions with substantially larger increases than expected from the CC scaling. Here, we leverage theory and observations of the form of the precipitation probability distribution to substantially improve intermodel agreement in the medium to high precipitation intensity regime, and to interpret projected changes in frequency in the Coupled Model Intercomparison Project Phase 6. Besides particular regions where models consistently display super-CC behavior, we find substantial occurrence of super-CC behavior within a given latitude band when the multi-model average does not require that the models agree point-wise on location within that band. About 13% of the globe and almost 25% of the tropics (30% for tropical land) display increases exceeding 2CC. Over 40% of tropical land points exceed 1.5CC. Risk-ratio analysis shows that even small increases above CC scaling can have disproportionately large effects in the frequency of the most extreme events. Risk due to regional enhancement of precipitation scale increase by dynamical effects must thus be included in vulnerability assessment even if locations are imprecise.
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Mellado, P. (2022). Intrinsic topological magnons in arrays of magnetic dipoles. Sci. Rep., 12(1), 1420.
Abstract: We study a simple magnetic system composed of periodically modulated magnetic dipoles with an easy axis. Upon adjusting the geometric modulation amplitude alone, chains and two-dimensional stacked chains exhibit a rich magnon spectrum where frequency gaps and magnon speeds are easily manipulable. The blend of anisotropy due to dipolar interactions between magnets and geometrical modulation induces a magnetic phase with fractional Zak number in infinite chains and end states in open one-dimensional systems. In two dimensions it gives rise to topological modes at the edges of stripes. Tuning the amplitude in two-dimensional lattices causes a band touching, which triggers the exchange of the Chern numbers of the volume bands and switches the sign of the thermal conductivity.
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Mellado, P., Concha, A., Hofhuis, K., & Tapia, I. (2023). Intrinsic chiral field as vector potential of the magnetic current in the zig-zag lattice of magnetic dipoles. Sci. Rep., 13(1), 1245.
Abstract: Chiral magnetic insulators manifest novel phases of matter where the sense of rotation of the magnetization is associated with exotic transport phenomena. Effective control of such phases and their dynamical evolution points to the search and study of chiral fields like the Dzyaloshinskii-Moriya interaction. Here we combine experiments, numerics, and theory to study a zig-zag dipolar lattice as a model of an interface between magnetic in-plane layers with a perpendicular magnetization. The zig-zag lattice comprises two parallel sublattices of dipoles with perpendicular easy plane of rotation. The dipolar energy of the system is exactly separable into a sum of symmetric and antisymmetric long-range exchange interactions between dipoles, where the antisymmetric coupling generates a nonlocal Dzyaloshinskii-Moriya field which stabilizes winding textures with the form of chiral solitons. The Dzyaloshinskii-Moriya interaction acts as a vector potential or gauge field of the magnetic current and gives rise to emergent magnetic and electric fields that allow the manifestation of the magnetoelectric effect in the system.
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