This paper studies the correlation between different macroscopic features of image regions and object properties with the Sauter diameter (D32) of bubble size in flotation. Bubbles were sampled from the collection zone of a two-dimensional flotation cell using a McGill Bubble Size Analyzer, and photographed bubbles were processed using image analysis. The Sauter mean diameters were obtained under different experimental conditions using a semiautomated methodology, in which non-identifiable bubbles were manually characterized to estimate the bubble size distribution. For the same processed images, different image properties from their binary representation were studied in terms of their correlation with D32. The median and variability of the shadow percentage, aspect ratio, power spectral density, perimeter, equivalent diameters, solidity, and circularity, among other image or object properties, were studied. These properties were then related to the measured D32 values, from which four predictors were chosen to obtain a multivariable model that adequately described the Sauter diameter. After removing abnormal gas dispersion conditions, the multivariable linear model was able to represent D32 values (99 datasets) for superficial gas rates in the range of 0.4–2.5 cm/s, for four types of frothers and surfactant concentrations ranging from 0 to 32 ppm. The model was tested with 72 independent datasets, showing the generalizability of the results. Thus, the approach proved to be applicable at the laboratory scale for D32 = 1.3–6.7 mm.

Women’s insertion or consolidation in science has been thoroughly researched. Such discussion could be particularly relevant concerning sustainable development goal five (SDG 5) on Gender Equality advancement. However, the debate is focused on women percentages inserted into scientific labor, leaving the issue of symbolic experience for women in research unaddressed and with little empirical support. The data come from a survey developed under a FONDECYT project, which studied knowledge production in Chile. Researchers obtained contacts through invitations on social networks such as Twitter, Facebook, and LinkedIn and databases containing scientists’ emails working in Chile. The non-probabilistic sample collected 583 cases, with participants residing in 15 of the 16 country regions. As a result, this document presents the findings of a study on symbolic experience using an instrument to determine whether there are any homophily patterns. It aims to determine if scientists tend to cite others as referents only when they encounter a situation like their own. The findings reveal a clear way scientists estimate the effect of others in terms of their gender homophily. This intervening factor could be crucial in reproducing the disparities and asymmetries that characterize Chile’s scientific field.

Risk factors associated with tooth loss have been studied; however, the current status of the epidemiological profiles and the impact of the pandemic on the oral health of the elderly is still unknown. This study aims to determine the experience of caries and tooth loss among elderly Chilean citizens in five regions and to identify the risk factors associated with tooth loss. The sample includes 135 participants over 60 years old assessed during COVID-19 lockdown. Sociodemographic variables such as education and RSH (Social Registry of Households) were obtained through a teledentistry platform called TEGO. The history of chronic diseases such as diabetes, obesity, depression and dental caries reported by DMFT index scores were incorporated. The statistical analysis included Adjusted Odds Ratios (ORs) to assess risk factors associated with the lack of functional dentition. Multivariate hypothesis testing was used to compare the mean equality of DMFT and its components between regions (p-value < 0.05). Individuals with RSH ≤ 40% were at higher risk of having no functional dentition with OR 4.56 (95% CI: 1.71, 12.17). The only mean difference between regions was the filled tooth component. Tooth loss was associated with multidimensional lower income, where the elderly belonging to the 40% most vulnerable population had a higher prevalence of non-functional dentition. This study highlights the importance of implementing a National Oral Health Policy that focuses on oral health promotion and minimally invasive dentistry for the most vulnerable population.

Information disorders on social media can have a significant impact on citizens’ participation in democratic processes. To better understand the spread of false and inaccurate information online, this research analyzed data from Twitter, Facebook, and Instagram. The data were collected and verified by professional fact-checkers in Chile between October 2019 and October 2021, a period marked by political and health crises. The study found that false information spreads faster and reaches more users than true information on Twitter and Facebook. Instagram, on the other hand, seemed to be less affected by this phenomenon. False information was also more likely to be shared by users with lower reading comprehension skills. True information, on the other hand, tended to be less verbose and generate less interest among audiences. This research provides valuable insights into the characteristics of misinformation and how it spreads online. By recognizing the patterns of how false information diffuses and how users interact with it, we can identify the circumstances in which false and inaccurate messages are prone to becoming widespread. This knowledge can help us to develop strategies to counter the spread of misinformation and protect the integrity of democratic processes.

This paper provides a theoretical and numerical comparison of classical first-order splitting methods for solving smooth convex optimization problems and cocoercive equations. From a theoretical point of view, we compare convergence rates of gradient descent, forward-backward, Peaceman-Rachford, and Douglas-Rachford algorithms for minimizing the sum of two smooth convex functions when one of them is strongly convex. A similar comparison is given in the more general cocoercive setting under the presence of strong monotonicity and we observe that the convergence rates in optimization are strictly better than the corresponding rates for cocoercive equations for some algorithms. We obtain improved rates with respect to the literature in several instances by exploiting the structure of our problems. Moreover, we indicate which algorithm has the smallest convergence rate depending on strong convexity and cocoercive parameters. From a numerical point of view, we verify our theoretical results by implementing and comparing previous algorithms in well established signal and image inverse problems involving sparsity. We replace the widely used ℓ1 norm with the Huber loss and we observe that fully proximal-based strategies have numerical and theoretical advantages with respect to methods using gradient steps.

Las arquitecturas dirigidas por eventos (EDA) comenzaron a desarrollarse a principios de este siglo y tomaron fuerza este último tiempo. En la búsqueda de una nueva propuesta en el ámbito de procesamiento de eventos complejos (CEP), este documento presenta una prueba de escalabilidad entre una arquitectura orientada a eventos y una tradicional utilizando datos sintéticos. Finalmente, se diseñó e implementó un prototipo orientado a eventos utilizando datos reales bajo una simulación trace-driven con el fin de procesar eventos en tiempo real y reconocer patrones complejos generando alarmas ante anomalías detectadas. Del presente estudio, se obtuvo que EDA se comporta de mejor forma que una arquitectura tradicional para sistemas basados en sensores. Además, el prototipo implementado para CEP fue capaz de procesar eventos y detectar anomalías en tiempo real sin acceder a una base de datos históricos.

In an effort to mitigate the 2019 novel coronavirus disease pandemic, mask wearing and social distancing have become standard practices. While effective in fighting the spread of the virus, these protective measures have been shown to deteriorate speech perception and sound intensity, which necessitates speaking louder to compensate. The goal of this paper is to investigate via numerical simulations how compensating for mask wearing and social distancing affects measures associated with vocal health. A three-mass body-cover model of the vocal folds (VFs) coupled with the sub- and supraglottal acoustic tracts is modified to incorporate mask and distance dependent acoustic pressure models. The results indicate that sustaining target levels of intelligibility and/or sound intensity while using these protective measures may necessitate increased subglottal pressure, leading to higher VF collision and, thus, potentially inducing a state of vocal hyperfunction, a progenitor to voice pathologies.