SiO2-Based Nanofluids for the Inhibition of Wax Precipitation in Production Pipelines.

Wax deposition in high-wax (waxy) crude oil has been an important challenge in the oil and gas industry due to the repercussions in flow assurance during oil extraction and transportation. However, the nanotechnology has emerged as a potential solution for the optimization of conventional wax removal and/or inhibition processes due to its exceptional performance in the alteration of wax morphology and co-crystallization behavior. In this sense, this study aims to study the performance of two commercial wax inhibitor treatments (WT1 and WT2) on the wax formation and crystallization due to the addition of SiO2 nanoparticles. Differential scanning calorimetry experiments and cold finger tests were carried out to study the effect of the WT on wax appearance temperature (WAT) and the wax inhibition efficiency (WIE) in a scenario with an initial temperature difference. In the first stage, the behavior of both WT in the inhibition of wax deposition was achieved, ranging in the concentration of the WT in the waxy crude (WC) oil from 5000 to 50,000 mg·L-1. Then, NanoWT was prepared by the addition of SiO2 nanoparticles on WT1 and WT2 for concentrations between 1000 and 500 mg·L-1, and the performance of the prepared NanoWT was studied at the best concentration of WIT in the absence of nanoparticles. Finally, the role of the nanofluid concentration in wax inhibition was accomplished for the best NanoWT. Selected NanoWT with nanoparticle dosage of 100 mg·L-1 added to WC oil at 5000 mg·L-1 displays reductions in WAT and WIE of 15.3 and 71.6 for NanoWT1 and -2.2 and 42.5% for NanoWT2. In flow loop experiments for the crude oil at temperatures above (30 °C) and below (16 °C), the WAT value indicates an increase of 8.3 times the pressure drops when the crude oil is flowing at a temperature below the WAT value. Therefore, when NanoWT1 is added to the crude oil, a reduction of 31.8% was found in the pressure drop in comparison with the scenario below the WAT value, ensuring the flow assurance in the pipeline in an unfavorable environment. Based on the pressure-drop method, a reduction greater than 5% in the wax deposit thickness confirms the wax deposition inhibitory character of the designed NanoWT.

An IoT and Fog Computing-Based Monitoring System for Cardiovascular Patients with Automatic ECG Classification Using Deep Neural Networks.

Telemedicine and all types of monitoring systems have proven to be a useful and low-cost tool with a high level of applicability in cardiology. The objective of this work is to present an IoT-based monitoring system for cardiovascular patients. The system sends the ECG signal to a Fog layer service by using the LoRa communication protocol. Also, it includes an AI algorithm based on deep learning for the detection of Atrial Fibrillation and other heart rhythms. The automatic detection of arrhythmias can be complementary to the diagnosis made by the physician, achieving a better clinical vision that improves therapeutic decision making. The performance of the proposed system is evaluated on a dataset of 8.528 short single-lead ECG records using two merge MobileNet networks that classify data with an accuracy of 90% for atrial fibrillation.

ME3CA: A Cognitive Assistant for Physical Exercises that Monitors Emotions and the Environment.

Recent studies show that the elderly population has increased considerably in European society in recent years. This fact has led the European Union and many countries to propose new policies for caring services directed to this group. The current trend is to promote the care of the elderly in their own homes, thus avoiding inverting resources on residences. With this in mind, there are now new solutions in this direction, which try to make use of the continuous advances in computer science. This paper tries to advance in this area by proposing the use of a personal assistant to help older people at home while carrying out their daily activities. The proposed personal assistant is called ME3CA, and can be described as a cognitive assistant that offers users a personalised exercise plan for their rehabilitation. The system consists of a sensorisation platform along with decision-making algorithms paired with emotion detection models. ME3CA detects the users' emotions, which are used in the decision-making process allowing for more precise suggestions and an accurate (and unbiased) knowledge about the users' opinion towards each exercise.

EMERALD-Exercise Monitoring Emotional Assistant.

The increase in the elderly population in today's society entails the need for new policies to maintain an adequate level of care without excessively increasing social spending. One of the possible options is to promote home care for the elderly. In this sense, this paper introduces a personal assistant designed to help elderly people in their activities of daily living. This system, called EMERALD, is comprised of a sensing platform and different mechanisms for emotion detection and decision-making that combined produces a cognitive assistant that engages users in Active Aging. The contribution of the paper is twofold-on the one hand, the integration of low-cost sensors that among other characteristics allows for detecting the emotional state of the user at an affordable cost; on the other hand, an automatic activity suggestion module that engages the users, mainly oriented to the elderly, in a healthy lifestyle. Moreover, by continuously correcting the system using the on-line monitoring carried out through the sensors integrated in the system, the system is personalized, and, in broad terms, emotionally intelligent. A functional prototype is being currently tested in a daycare centre in the northern area of Portugal where preliminary tests show positive results.

Intubación orotraqueal sin relajante muscular: propofol o etomidato en combinación con remifentanilo / Orotracheal Intubation without the use of muscle relaxant: propofol or etomidate in combination with remifentanil

Introducción. El remifentanilo en combinación con propofol provee adecuadas condiciones para la intubación orotraqueal sin relajante neuromuscular. Otros agentes inductores no han sido adecuadamente evaluados. El propósito del estudio fue evaluar las condiciones de intubación y los cambios hemodinámicos tras la inducción anestésica con remifentanilo-propofol o remifentanilo- etomidato. Métodos. En este estudio prospectivo, doble ciego y aleatorio, participaron 90 pacientes con clasificación ASA I/II. Recibieron 0,03 mg/kg de midazolam y 7 ml/kg de lactato de Ringer, y posteriormente, 3 mg/kg de remifentanilo seguidos de 1 mg/kg de lidocaína. A continuación, se distribuyeron en forma aleatoria en los siguientes grupos de pacientes: los que recibieron 2 mg/kg de propofol (grupo propofol, n=29), 0,3 mg/ kg de etomidato (grupo etomidato 3, n=31) o 0,4 mg/kg de etomidato (grupo etomidato 4, n=30). Después se realizó laringoscopia e intubación orotraqueal. Las condiciones para la intubación se evaluaron utilizando un sistema cualitativo de puntaje. Se registraron la presión arterial media y la frecuencia cardiaca previa a la inducción, posterior a la inducción, inmediatamente después de la intubación y cada minuto hasta 5 minutos después de la intubación. Resultados. Tres pacientes del grupo etomidato 3 y dos del grupo etomidato 4 no pudieron ser intubados en el primer intento. Se alcanzaron condiciones clínicamente aceptables de intubación en 100%, 74% y 80%, en los grupo propofol, etomidato 3 y etomidato 4, respectivamente (p=0,016). El descenso en la presión arterial media fue significativamente mayor en el grupo propofol comparado con el grupo etomidato 3. Conclusiones. Para la intubación orotraqueal sin relajante neuromuscular, el uso de remifentanilo-propofol es superior al de remifentanilo-etomidato, 0,3 mg/kg o 0,4 mg/kg. Con 0,3 mg/kg de etomidato se obtiene un mejor perfil hemodinámico.

Introduction: Remifentanil followed by propofol provides adequate conditions for tracheal intubation without using muscle relaxants. Other hypnotic drugs have not been thoroughly evaluated in this regard. The purpose of this study was to assess intubating conditions and cardiovascular changes after induction of anesthesia with remifentanil-propofol or. Methods: 90 ASA I/II patients were enrolled in this random, prospective, double-blind study. Subjects received 0.03 mg/kg of midazolam followed by a 7 ml/kg infusion of RingerLs lactate. After that, 3 ƒÊg/kg of remifentanil were injected followed by lydocaine, 1 mg/kg. Then, patients received either propofol (2 mg/ kg) (Propofol Group, n= 29), or etomidate (0.3 mg/kg) (Etomidate 3 Group, n=31) or etomidate (0.4 mg/kg) (Etomidate 4 Group, n=30). Subsequent laryngoscope and intubation were performed. Intubating conditions were assessed using a quality scoring system. Mean arterial pressure and heart rates pre-induction, post-induction were recorded immediately after intubation and every 1 to 5 minutes after intubation. Results: Three patients in the etomidate 3 Group and two patients in the etomidate 4 Group were not able to beintubated in the first attempt. Clinically acceptable intubating conditions were observed in 100%, 74%, 80% in the Propofol, Etomidate 3 and etomodate 4 groups, respectively (p=0.01 6). The decrease in mean arterial pressure was significantly higher in the propofol group as compared to the etomidate 3 group (p<0.05). Conclusions: The use of lydocaine-remifentanil-propofol for tracheal intubation without muscle relaxants is superior to 0.3 or 0.4 mg/kg lydocaine-remifentanil plus etomidate. However, etomidate 0.3 mg/kg produces a better hemodynamic profile when compared to propofol.