OPTIMIZATION BASED CONTROL OF A DIRECT ROTARY DRYER

Indexación: Web of Science; ScieloRESUMEN: Este trabajo presenta el control de un secador rotatorio directo basado en optimización no lineal. Esta metodología permite auto-sintonizar dinámicamente un controlador PI o PID, mejorando claramente el control del proceso respecto de la sintonización clásica. El control del proceso se realiza a través de simulación computacional vía Matlab y su verificación a través de un proceso piloto, lo que permite apreciar la potencialidad de la sintonía dinámica que se propone. Los resultados, tiempo de respuesta y dinámica de control posibilitan que investigación futura pueda escalar esta propuesta desde el laboratorio a procesos industriales.ABSTRACT: This paper presents the control of a direct rotary dryer based on nonlinear optimization. This methodology allows the dynamic self-tuning of PI or PID controller, clearly improving process control over the classic tuning approach. Process control is done through Matlab via computer simulation and verification through a pilot process, which allows us to appreciate the potential of the proposed dynamic tuning. The results, response time and dynamic control allow us to scale future research from the laboratory (pilot scale) to industrial processes.http://ref.scielo.org/swb3h

Real-time gun detection in CCTV: An open problem

Object detectors have improved in recent years, obtaining better results and faster inference time. However, small object detection is still a problem that has not yet a definitive solution. The autonomous weapons detection on Closed-circuit television (CCTV) has been studied recently, being extremely useful in the field of security, counter-terrorism, and risk mitigation. This article presents a new dataset obtained from a real CCTV installed in a university and the generation of synthetic images, to which Faster R-CNN was applied using Feature Pyramid Network with ResNet-50 resulting in a weapon detection model able to be used in quasi real-time CCTV (90 ms of inference time with an NVIDIA GeForce GTX-1080Ti card) improving the state of the art on weapon detection in a two stages training. In this work, an exhaustive experimental study of the detector with these datasets was performed, showing the impact of synthetic datasets on the training of weapons detection systems, as well as the main limitations that these systems present nowadays. The generated synthetic dataset and the real CCTV dataset are available to the whole research community.Ministerio de Economía y Competitividad TIN2017-82113-C2-1-

In vivo antimicrobial activity of silver nanoparticles produced via a green chemistry synthesis using Acacia rigidula as a reducing and capping agent

Introduction: One of the main issues in the medical field and clinical practice is the development of novel and effective treatments against infections caused by antibiotic-resistant bacteria. One avenue that has been approached to develop effective antimicrobials is the use of silver nanoparticles (Ag-NPs), since they have been found to exhibit an efficient and wide spectrum of antimicrobial properties. Among the main drawbacks of using Ag-NPs are their potential cytotoxicity against eukaryotic cells and the latent environmental toxicity of their synthesis methods. Therefore, diverse green synthesis methods, which involve the use of environmentally friendly plant extracts as reductive and capping agents, have become attractive to synthesize Ag-NPs that exhibit antimicrobial effects against resistant bacteria at concentrations below toxicity thresholds for eukaryotic cells. Purpose: In this study, we report a green one-pot synthesis method that uses Acacia rigidula extract as a reducing and capping agent, to produce Ag-NPs with applications as therapeutic agents to treat infections in vivo. Materials and methods: The Ag-NPs were characterized using transmission electron microscopy (TEM), high-resolution TEM, selected area electron diffraction, energy-dispersive spectroscopy, ultraviolet–visible, and Fourier transform infrared. Results: We show that Ag-NPs are spherical with a narrow size distribution. The Ag-NPs show antimicrobial activities in vitro against Gram-negative (Escherichia coli, Pseudomonas aeruginosa, and a clinical multidrug-resistant strain of P. aeruginosa) and Gram-positive (Bacillus subtilis) bacteria. Moreover, antimicrobial effects of the Ag-NPs, against a resistant P. aeruginosa clinical strain, were tested in a murine skin infection model. The results demonstrate that the Ag-NPs reported in this work are capable of eradicating pathogenic resistant bacteria in an infection in vivo. In addition, skin, liver, and kidney damage profiles were monitored in the murine infection model, and the results demonstrate that Ag-NPs can be used safely as therapeutic agents in animal models. Conclusion: Together, these results suggest the potential use of Ag-NPs, synthesized by green chemistry methods, as therapeutic agents against infections caused by resistant and nonresistant strains. Keywords: silver nanoparticles, green synthesis, in vitro antibacterial activity, in vivo antibacterial activity, skin infection, toxicological stud

Inappropriate antibiotic use in the COVID-19 era: Factors associated with inappropriate prescribing and secondary complications. Analysis of the registry SEMI-COVID

Background: Most patients with COVID-19 receive antibiotics despite the fact that bacterial co-infections are rare. This can lead to increased complications, including antibacterial resistance. We aim to analyze risk factors for inappropriate antibiotic prescription in these patients and describe possible complications arising from their use. Methods: The SEMI-COVID-19 Registry is a multicenter, retrospective patient cohort. Patients with antibiotic were divided into two groups according to appropriate or inappropriate prescription, depending on whether the patient fulfill any criteria for its use. Comparison was made by means of multilevel logistic regression analysis. Possible complications of antibiotic use were also identified. Results: Out of 13,932 patients, 3047 (21.6%) were prescribed no antibiotics, 6116 (43.9%) were appropriately prescribed antibiotics, and 4769 (34.2%) were inappropriately prescribed antibiotics. The following were independent factors of inappropriate prescription: February-March 2020 admission (OR 1.54, 95%CI 1.18-2.00), age (OR 0.98, 95%CI 0.97-0.99), absence of comorbidity (OR 1.43, 95%CI 1.05-1.94), dry cough (OR 2.51, 95%CI 1.94-3.26), fever (OR 1.33, 95%CI 1.13-1.56), dyspnea (OR 1.31, 95%CI 1.04-1.69), flu-like symptoms (OR 2.70, 95%CI 1.75-4.17), and elevated C-reactive protein levels (OR 1.01 for each mg/L increase, 95% CI 1.00-1.01). Adverse drug reactions were more frequent in patients who received ANTIBIOTIC (4.9% vs 2.7%, p < .001). Conclusion: The inappropriate use of antibiotics was very frequent in COVID-19 patients and entailed an increased risk of adverse reactions. It is crucial to define criteria for their use in these patients. Knowledge of the factors associated with inappropriate prescribing can be helpful

Energy Estimation of Cosmic Rays with the Engineering Radio Array of the Pierre Auger Observatory

The Auger Engineering Radio Array (AERA) is part of the Pierre Auger Observatory and is used to detect the radio emission of cosmic-ray air showers. These observations are compared to the data of the surface detector stations of the Observatory, which provide well-calibrated information on the cosmic-ray energies and arrival directions. The response of the radio stations in the 30 to 80 MHz regime has been thoroughly calibrated to enable the reconstruction of the incoming electric field. For the latter, the energy deposit per area is determined from the radio pulses at each observer position and is interpolated using a two-dimensional function that takes into account signal asymmetries due to interference between the geomagnetic and charge-excess emission components. The spatial integral over the signal distribution gives a direct measurement of the energy transferred from the primary cosmic ray into radio emission in the AERA frequency range. We measure 15.8 MeV of radiation energy for a 1 EeV air shower arriving perpendicularly to the geomagnetic field. This radiation energy -- corrected for geometrical effects -- is used as a cosmic-ray energy estimator. Performing an absolute energy calibration against the surface-detector information, we observe that this radio-energy estimator scales quadratically with the cosmic-ray energy as expected for coherent emission. We find an energy resolution of the radio reconstruction of 22% for the data set and 17% for a high-quality subset containing only events with at least five radio stations with signal.Comment: Replaced with published version. Added journal reference and DO

Measurement of the Radiation Energy in the Radio Signal of Extensive Air Showers as a Universal Estimator of Cosmic-Ray Energy

We measure the energy emitted by extensive air showers in the form of radio emission in the frequency range from 30 to 80 MHz. Exploiting the accurate energy scale of the Pierre Auger Observatory, we obtain a radiation energy of 15.8 \pm 0.7 (stat) \pm 6.7 (sys) MeV for cosmic rays with an energy of 1 EeV arriving perpendicularly to a geomagnetic field of 0.24 G, scaling quadratically with the cosmic-ray energy. A comparison with predictions from state-of-the-art first-principle calculations shows agreement with our measurement. The radiation energy provides direct access to the calorimetric energy in the electromagnetic cascade of extensive air showers. Comparison with our result thus allows the direct calibration of any cosmic-ray radio detector against the well-established energy scale of the Pierre Auger Observatory.Comment: Replaced with published version. Added journal reference and DOI. Supplemental material in the ancillary file

Measurement of the cosmic ray spectrum above 4×10184{\times}10^{18} eV using inclined events detected with the Pierre Auger Observatory

A measurement of the cosmic-ray spectrum for energies exceeding $4{\times}10^{18}$ eV is presented, which is based on the analysis of showers with zenith angles greater than $60^{\circ}$ detected with the Pierre Auger Observatory between 1 January 2004 and 31 December 2013. The measured spectrum confirms a flux suppression at the highest energies. Above $5.3{\times}10^{18}$ eV, the "ankle", the flux can be described by a power law $E^{-\gamma}$ with index $\gamma=2.70 \pm 0.02 \,\text{(stat)} \pm 0.1\,\text{(sys)}$ followed by a smooth suppression region. For the energy ($E_\text{s}$) at which the spectral flux has fallen to one-half of its extrapolated value in the absence of suppression, we find $E_\text{s}=(5.12\pm0.25\,\text{(stat)}^{+1.0}_{-1.2}\,\text{(sys)}){\times}10^{19}$ eV.Comment: Replaced with published version. Added journal reference and DO

Informe de Política Monetaria - Octubre 2020

Recent data suggest that the technical staff’s appraisals of the condition and development of economic activity, inflation and the labor market have been in line with current trends, marked by a decline in demand and the persistence of ample excess productive capacity. A significant projected fall in output materialized in the second quarter, contributing to a decline in inflation below the 3% target and reflected in a significant deterioration of the labor market. A slow recovery in output and employment is expected to continue for the remainder of 2020 and into next year, alongside growing inflation that should remain below the target. The Colombian economy is likely to undergo a significant recession in 2020 (GDP contraction of 7.6%), though this may be less severe than projected in the previous report (-8.5%). Output is expected to have begun a slow recovery in the second half of this year, though it is not projected to return to pre-pandemic levels in 2021 amid significant global uncertainty. The output decline in the first half of 2020 was less severe than anticipated, thanks to an upward revision in first-quarter GDP and a smaller contraction in the second quarter (-15.5%) than had been projected (-16.5%). Available economic indicators suggest an annual decline in GDP in the third quarter of around 9%. No significant acceleration of COVID-19 cases that would imply a tightening of social distancing measures is presumed for the remainder of this year or in 2021. In that context, a gradual opening of the economy would be expected to continue, with supply in sectors that have been most affected by the pandemic recovering slowly as restrictions on economic activity continue to be relaxed. On the spending side, an improvement in consumer confidence, suppressed demand for goods and services, low interest rates, and higher expected levels of foreign demand should contribute to a recovery in output. A low base of comparison would also help explain the expected increase in GDP in 2021. Based on the conditions laid out above, economic growth in 2020 is expected to be between -9% and -6.5%, with a central value of -7.6%. Growth in 2021 is projected to be between 3% and 7%, with a central value of 4.6% (Graph 1.1). Upward revisions compared to the July report take into account a lower-than-expected fall in first-semester growth and a somewhat faster recovery in the third quarter in some sectors. The forecast intervals for 2020 and 2021 growth tightened somewhat but continue to reflect a high degree of uncertainty over theevolution of the pandemic, the easures required to deal with it, and their effects on global and domestic economic activity.Box 1. Evaluation of the Predictive Capacity of Expected Inflation Measures. Authors: César Anzola-Bravo, Anderson Grajales-Olarte, Alexander Guarín-López, Julián Camilo Mateus-Gamboa, Jonathan Alexander Muñoz-Martínez, Carlos Andrés Quicazán-Moreno, Juan Sebastián Rojas-Moreno, Cristhian Hernando Ruiz-CardozoBox 2. Literature Review: Weighing the Drivers of Portfolio Flows to Emerging Market Economies. Authors: Andrés Sánchez-Jabb