Inspección de subestaciones eléctricas: YOLOv5 en la identificación de puntos calientes mediante imágenes térmicas

Substations are key facilities within an electrical system, untimely failures tend to cause low quality and negative effects on the electrical supply. An early indicator of potential electrical equipment failure is the appearance of hot spots; therefore, its detection and subsequent programmed correction avoids incurring in major failures and unnecessary operation stops. In this research, 64 experiments of the YOLOv5 algorithm were carried out, with the purpose of proposing an automated computer vision mechanism for the detection of hot spots in thermal images of electrical substations. The best results show a mAP value of 81.99%, which were obtained with the YOLOv5m algorithm and the transfer learning application. These results leave a basis to deepen and improve the performance of the algorithm by varying other hyperparameters to those considered in this study.Las subestaciones son instalaciones clave dentro de un sistema eléctrico; las fallas intempestivas tienden a causar baja calidad y efectos negativos del suministro eléctrico. Un indicador temprano de posibles fallas en los equipos eléctricos es la aparición de puntos calientes; por lo que su detección y posterior corrección programada evita incurrir en fallas mayores y paradas de operación innecesarias. En esta investigación se realizaron 64 experimentos del algoritmo YOLOv5, con la finalidad de proponer un mecanismo automatizado de visión por computadora para la detección de puntos calientes en imágenes térmicas de subestaciones eléctricas. Los mejores resultados muestran un valor mAP de 81,99 %, los cuales se obtuvieron con el algoritmo YOLOv5m y la aplicación de transfer learning. Estos resultados dejan una base para profundizar y mejorar el desempeño del algoritmo, variando otros hiperparámetros a los considerados en el presente estudio

Inspección de subestaciones eléctricas: YOLOv5 en la identificación de puntos calientes mediante imágenes térmicas

Las subestaciones son instalaciones clave dentro de un sistema eléctrico; las fallas intempestivas tienden a causar baja calidad y efectos negativos del suministro eléctrico. Un indicador temprano de posibles fallas en los equipos eléctricos es la aparición de puntos calientes; por lo que su detección y posterior corrección programada evita incurrir en fallas mayores y paradas de operación innecesarias. En esta investigación se realizaron 64 experimentos del algoritmo YOLOv5, con la finalidad de proponer un mecanismo automatizado de visión por computadora para la detección de puntos calientes en imágenes térmicas de subestaciones eléctricas. Los mejores resultados muestran un valor mAP de 81,99 %, los cuales se obtuvieron con el algoritmo YOLOv5m y la aplicación de transfer learning. Estos resultados dejan una base para profundizar y mejorar el desempeño del algoritmo, variando otros hiperparámetros a los considerados en el presente estudio

Detection of Bovine Mastitis in Raw Milk, Using a Low-Cost NIR Spectrometer and k-NN Algorithm

[Abstract] Among the bovine diseases, mastitis causes high economic losses in the dairy production system. Nowadays, detection under field conditions is mainly performed by the California Mastitis Test, which is considered the de facto standard. However, this method presents with problems of slowness and the expensiveness of the chemical-reactive process, which is deeply dependent on an expert’s trained eye and, consequently, is highly imprecise. The aim of this work is to propose a new method for bovine mastitis detection under field conditions. The proposed method uses a low-cost, smartphone-connected NIR spectrometer which solves the aforementioned problems of slowness, expert dependency and disposability of the chemical methods. This method uses spectra in combination with two k-Nearest Neighbors models. The first model is used to detect the presence of mastitis while the second model classifies the positive cases into weak and strong. The resulting method was validated by using a leave-one-out technique where the ground truth was obtained by the California Mastitis Test. The detection model achieved an accuracy of 92.4%, while the one classifying the severity showed an accuracy of 95%.This work is part of DINTA-UTMACH and RNASA-UDC research groups. This work is partially supported by Instituto de Salud Carlos III, grant number PI17/01826. It was also partially supported by different grants and projects from the Xunta de Galicia [ED431D 2017/23; ED431D 2017/16; ED431G/01; ED431C 2018/49; IN845D-2020/03]. Another source of support was the CYTED network (PCI2018\_093284) funded by the Spanish Ministry of Innovation and ScienceXunta de Galicia; ED431D 2017/23Xunta de Galicia; ED431D 2017/16Xunta de Galicia; ED431G/01Xunta de Galicia; ED431C 2018/49Xunta de Galicia; IN845D-2020/0

Effect of the Ozonization Degree of Emu Oil over Healing: An Emerging Oxidation Treatment

This chapter deals with the ozonization process of the emu oil, the objective of this study was to quantitatively determine the peroxide value (PV) to measure the degree of ozonation, the peroxide value measures the number of peroxide groups in the ozonized oil. The ozone oxidizes the unsaturated chemical functions present in the oil giving a high cure rate for epidermal wounds. The healing process is not completely understood and there are different approaches, therefore, it was determined qualitatively if it has healing and inflammation properties, but the results of our studies have shown that the length and width of the wounds were healing quickly thanks to the peroxidation rate of the oils. In addition, both tests were correlated to obtain a greater appreciation of their functions, the mechanism involves a decrease in the inflammation of the wounds and stimulates the process of scar formation

Composition and Antidiarrheal Activity of Bidens odorata

The antidiarrheal effects of chloroform, methanol, and aqueous extracts of Bidens odorata Cav. were investigated at doses of 200 mg/kg on castor-oil-induced diarrhea. The chloroform extract of B. odorata (CBO) reduced diarrhea by 72.72%. The effect of CBO was evaluated on mice with diarrhea induced by castor oil, MgSO4, arachidonic acid, or prostaglandin E2. CBO inhibited the contraction induced by carbachol chloride on ileum (100 µg/mL) and intestinal transit (200 mg/kg) in Wistar rats. The active fraction of CBO (F4) at doses of 100 mg/kg inhibited the diarrhea induced by castor oil (90.1%) or arachidonic acid (72.9%) but did not inhibit the diarrhea induced by PGE2. The active fraction of F4 (FR5) only was tested on diarrhea induced with castor oil and inhibited this diarrhea by 92.1%. The compositions of F4 and FR5 were determined by GC-MS, and oleic, palmitic, linoleic, and stearic acids were found. F4 and a mixture of the four fatty acids inhibited diarrhea at doses of 100 mg/kg (90.1% and 70.6%, resp.). The results of this study show that B. odorata has antidiarrheal effects, as is claimed by folk medicine, and could possibly be used for the production of a phytomedicine

Differential body composition effects of protease inhibitors recommended for initial treatment of HIV infection: A randomized clinical trial

This article has been accepted for publication in Clinical Infectious Diseases ©2014 The Authors .Published by Oxford University Press on Clinical Infectious Disease 60.5. DOI: 10.1093/cid/ciu898Background. It is unclear whether metabolic or body composition effects may differ between protease inhibitor-based regimens recommended for initial treatment of HIV infection. Methods. ATADAR is a phase IV, open-label, multicenter randomized clinical trial. Stable antiretroviral-naive HIV-infected adults were randomly assigned to atazanavir/ritonavir 300/100 mg or darunavir/ritonavir 800/100 mg in combination with tenofovir/emtricitabine daily. Pre-defined end-points were treatment or virological failure, drug discontinuation due to adverse effects, and laboratory and body composition changes at 96 weeks. Results. At 96 weeks, 56 (62%) atazanavir/ritonavir and 62 (71%) darunavir/ritonavir patients remained free of treatment failure (estimated difference 8.2%; 95%CI -0.6 to 21.6); and 71 (79%) atazanavir/ritonavir and 75 (85%) darunavir/ritonavir patients remained free of virological failure (estimated difference 6.3%; 95%CI -0.5 to 17.6). Seven vs. five patients discontinued atazanavir/ritonavir or darunavir/ritonavir due to adverse effects. Total and HDL cholesterol similarly increased in both arms, but triglycerides increased more in atazanavir/ritonavir arm. At 96 weeks, body fat (estimated difference 2862.2 gr; 95%CI 726.7 to 4997.7; P=0.0090), limb fat (estimated difference 1403.3 gr; 95%CI 388.4 to 2418.2; P=0.0071), and subcutaneous abdominal adipose tissue (estimated difference 28.4 cm2; 95%CI 1.9 to 55.0; P=0.0362) increased more in atazanavir/ritonavir than in darunavir/ritonavir arm. Body fat changes in atazanavir/ritonavir arm were associated with higher insulin resistance. Conclusions. We found no major differences between atazanavir/ritonavir and darunavir/ritonavir in efficacy, clinically-relevant side effects, or plasma cholesterol fractions. However, atazanavir/ritonavir led to higher triglycerides and total and subcutaneous fat than darunavir/ritonavir and fat gains with atazanavir/ritonavir were associated with insulin resistanceThis is an Investigator Sponsored Research study. It was supported in part by research grants from Bristol‐Myers Squibb and Janssen‐Cilag; Instituto de Salud Carlos III (PI12/01217) and Red Temática Cooperativa de Investigación en SIDA G03/173 (RIS‐EST11), Ministerio de Ciencia e Innovación, Spain. (Registration number: NCT01274780; registry name: ATADAR; EUDRACT; 2010‐021002‐38)

Respiratory viruses detected in Mexican children younger than 5 years old with community-acquired pneumonia: a national multicenter study

Background: Acute respiratory infections are the leading cause of mortality in children worldwide, especially in developing countries. Pneumonia accounts for 16% of all deaths of children under 5 years of age and was the cause of death of 935 000 children in 2015. Despite its frequency and severity, information regarding its etiology is limited. The aim of this study was to identify respiratory viruses associated with community-acquired pneumonia (CAP) in children younger than 5 years old. Methods: One thousand four hundred and four children younger than 5 years of age with a clinical and/or radiological diagnosis of CAP in 11 hospitals in Mexico were included. Nasal washes were collected, placed in viral medium, and frozen at �70 C until processing. The first 832 samples were processed using the multiplex Bio-Plex/Luminex system and the remaining 572 samples using the Anyplex multiplex RT-PCR. Clinical data regarding diagnosis, clinical signs and symptoms, radiographic pattern, and risk factors were obtained and recorded. Results: Of the samples tested, 81.6% were positive for viruses. Respiratory syncytial virus (types A and B) was found in 23.7%, human enterovirus/rhinovirus in 16.6%, metapneumovirus in 5.7%, parainfluenza virus (types 1–4) in 5.5%, influenza virus (types A and B) in 3.6%, adenovirus in 2.2%, coronavirus (NL63, OC43, 229E, and HKU1) in 2.2%, and bocavirus in 0.4%. Co-infection with two or more viruses was present in 22.1%; 18.4% of the samples were negative. Using biomass for cooking, daycare attendance, absence of breastfeeding, and co-infections were found to be statistically significant risk factors for the presence of severe pneumonia. Conclusions: Respiratory syncytial virus (types A and B), human enterovirus/rhinovirus, and metapneumovirus were the respiratory viruses identified most frequently in children younger than 5 years old with CAP. Co-infection was present in an important proportion of the children

Exercise Increases Serum Fibroblast Growth Factor 21 (FGF21) Levels

Fibroblast growth factor 21 (FGF21) increases glucose uptake. It is unknown if FGF21 serum levels are affected by exercise.This was a comparative longitudinal study. Anthropometric and biochemical evaluation were carried out before and after a bout of exercise and repeated after two weeks of daily supervised exercise. The study sample was composed of 60 sedentary young healthy women. The mean age was 24±3.7 years old, and the mean BMI was 21.4±7.0 kg/m². The anthropometric characteristics did not change after two weeks of exercise. FGF21 levels significantly increased after two weeks of exercise (276.8 ng/l (142.8-568.6) vs. (460.8 (298.2-742.1), p<0.0001)). The delta (final-basal) log of serum FGF21, adjusted for BMI, showed a significant positive correlation with basal glucose (r = 0.23, p = 0.04), mean maximal heart rate (MHR) (r = 0.54, p<0.0001), mean METs (r = 0.40, p = 0.002), delta plasma epinephrine (r = 0.53, p<0.0001) and delta plasma FFAs (r = 0.35, p = 0.006). A stepwise linear regression model showed that glucose, MHR, METs, FFAs, and epinephrine, were factors independently associated with the increment in FGF21 after the exercise program (F = 4.32; r² = 0.64, p<0.0001).Serum FGF21 levels significantly increased after two weeks of physical activity. This increment correlated positively with clinical parameters related to the adrenergic and lipolytic response to exercise.ClinicalTrials.gov NCT01512368

The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the extended Baryon Oscillation Spectroscopic Survey and from the second phase of the Apache Point Observatory Galactic Evolution Experiment

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since July 2014. This paper describes the second data release from this phase, and the fourteenth from SDSS overall (making this, Data Release Fourteen or DR14). This release makes public data taken by SDSS-IV in its first two years of operation (July 2014-2016). Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey (eBOSS); the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data driven machine learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS website (www.sdss.org) has been updated for this release, and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020, and will be followed by SDSS-V.Comment: SDSS-IV collaboration alphabetical author data release paper. DR14 happened on 31st July 2017. 19 pages, 5 figures. Accepted by ApJS on 28th Nov 2017 (this is the "post-print" and "post-proofs" version; minor corrections only from v1, and most of errors found in proofs corrected