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-

Drug Repurposing for Cancers With Limited Survival: Protocol for a Retrospective Cohort Study

Only 5% of the molecules tested in oncology phase 1 trials reach the market after an average of 7.5 years of waiting and at a cost of tens of millions of dollars. To reduce the cost and shorten the time of discovery of new treatments, drug repurposing (research with molecules already approved for another indication) and the use of secondary data (not collected for the purpose of research) have been proposed. Due to advances in informatics in clinical care, secondary data can, in some cases, be of equal quality to primary data generated through prospective studies.Objective: The objective of this study is to identify drugs currently marketed for other indications that may have an effect on the prognosis of patients with cancer.Methods: We plan to monitor a cohort of patients with high-lethality cancers treated in the public health system of Catalonia between 2006 and 2012, retrospectively, for survival for 5 years after diagnosis or until death. A control cohort, comprising people without cancer, will also be retrospectively monitored for 5 years. The following study variables will be extracted from different population databases: type of cancer (patients with cancer cohort), date and cause of death, pharmacological treatment, sex, age, and place of residence. During the first stage of statistical analysis of the patients with cancer cohort, the drugs consumed by the long-term survivors (alive at 5 years) will be compared with those consumed by nonsurvivors. In the second stage, the survival associated with the consumption of each relevant drug will be analyzed. For the analyses, groups will be matched for potentially confounding variables, and multivariate analyses will be performed to adjust for residual confounding variables if necessary. The control cohort will be used to verify whether the associations found are exclusive to patients with cancer or whether they also occur in patients without cancer.Results: We anticipate discovering multiple significant associations between commonly used drugs and the survival outcomes of patients with cancer. We expect to publish the initial results in the first half of 2024.Conclusions: This retrospective study may identify several commonly used drugs as candidates for repurposing in the treatment of various cancers. All analyses are considered exploratory; therefore, the results will have to be confirmed in subsequent clinical trials. However, the results of this study may accelerate drug discovery in oncology

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