Optimal Microgrid Topology Design and Siting of Distributed Generation Sources Using a Multi-Objective Substrate Layer Coral Reefs Optimization Algorithm

n this work, a problem of optimal placement of renewable generation and topology design for a Microgrid (MG) is tackled. The problem consists of determining the MG nodes where renewable energy generators must be optimally located and also the optimization of the MG topology design, i.e., deciding which nodes should be connected and deciding the lines’ optimal cross-sectional areas (CSA). For this purpose, a multi-objective optimization with two conflicting objectives has been used, utilizing the cost of the lines, C, higher as the lines’ CSA increases, and the MG energy losses, E, lower as the lines’ CSA increases. To characterize generators and loads connected to the nodes, on-site monitored annual energy generation and consumption profiles have been considered. Optimization has been carried out by using a novel multi-objective algorithm, the Multi-objective Substrate Layers Coral Reefs Optimization algorithm (Mo-SL-CRO). The performance of the proposed approach has been tested in a realistic simulation of a MG with 12 nodes, considering photovoltaic generators and micro-wind turbines as renewable energy generators, as well as the consumption loads from different commercial and industrial sites. We show that the proposed Mo-SL-CRO is able to solve the problem providing good solutions, better than other well-known multi-objective optimization techniques, such as NSGA-II or multi-objective Harmony Search algorithm.This research was partially funded by Ministerio de Economía, Industria y Competitividad, project number TIN2017-85887-C2-1-P and TIN2017-85887-C2-2-P, and by the Comunidad Autónoma de Madrid, project number S2013ICE-2933_02

Synchronous unilateral parotid neoplasms. : a case report

The parotid gland is the most usual location of benign neoplasms affecting major salivary glands and quite often the recurrence of these tumours is noticed, specially in the case of pleomorphic adenoma. The occurrence of multiple tumours in the parotid glands is rare and the majority of these are multifocal Warthin`s tumors (papillary cystadenoma lymphomatosum). The simultaneous development of tumours with different histological types is unusual and when it occurs, the most common combination is a pleomorphic adenoma and a Warthin`s tumor. There are many articles about Multiple Parotid Tumors (MPT) but only a few of them are focused on unilateral synchronous benings tumors, being pleomorphic adenoma and Warthin´s these tumors. The report describes a 55 year old female with a pleomorphic adenoma occurring synchronously with a Warthin`s tumor within the superficial lobe of her left parotid gland

Optimal generation scheduling in hydro-power plants with the Coral Reefs Optimization algorithm

Hydro-power plants are able to produce electrical energy in a sustainable way. A known format for producing energy is through generation scheduling, which is a task usually established as a Unit Commitment problem. The challenge in this process is to define the amount of energy that each turbine-generator needs to deliver to the plant, to fulfill the requested electrical dispatch commitment, while coping with the operational restrictions. An optimal generation scheduling for turbine-generators in hydro-power plants can offer a larger amount of energy to be generated with respect to non-optimized schedules, with significantly less water consumption. This work presents an efficient mathematical modelling for generation scheduling in a real hydro-power plant in Brazil. An optimization method based on different versions of the Coral Reefs Optimization algorithm with Substrate Layers (CRO) is proposed as an effective method to tackle this problem.This approach uses different search operators in a single population to refine the search for an optimal scheduling for this problem. We have shown that the solution obtained with the CRO using Gaussian search in exploration is able to produce competitive solutions in terms of energy production. The results obtained show a huge savings of 13.98 billion (liters of water) monthly projected versus the non-optimized scheduling.European CommissionMinisterio de Economía y CompetitividadComunidad de Madri

An improved C-DEEPSO algorithm for optimal active-reactive power dispatch in microgrids with electric vehicles

In the last years, our society's high energy demand has led to the proposal of novel ways of consuming and producing electricity. In this sense, many countries have encouraged micro generation, including the use of renewable sources such as solar irradiation and wind generation, or considering the insertion of electric vehicles as dispatchable units on the grid. This work addresses the Optimal active&-reactive power dispatch (OARPD) problem (a type of optimal power flow (OPF) task) in microgrids considering electric vehicles. We used the modified IEEE 57 and IEEE 118 bus-systems test scenarios, in which thermoelectric generators were replaced by renewable generators. In particular, under the IEEE 118 bus system, electric vehicles were integrated into the grid. To solve the OARDP problem, we proposed the use and improvement of the Canonical Differential Evolutionary Particle Swarm Optimization (C-DEEPSO) algorithm. For further refinement in the search space, C-DEEPSO relies on local search operators. The results indicated that the proposed improved C-DEEPSO was able to show generation savings (in terms ofmillions of dollars) acting as a dispatch controller against two algorithms based on swarm intelligence.European CommissionAgencia Estatal de InvestigaciónComunidad de Madri

Colistin versus meropenem in the empirical treatment of ventilator-associated pneumonia (Magic Bullet study): an investigator-driven, open-label, randomized, noninferiority controlled trial.

Background: Colistin is recommended in the empirical treatment of ventilator-associated pneumonia (VAP) with a high prevalence of carbapenem-resistant gram-negative bacilli (CR-GNB). However, the efficacy and safety of colistin are not well defined. Methods: A multicenter prospective randomized trial conducted in 32 European centers compared the efficacy and safety of colistin (4.5 million unit loading dose followed by a maintenance dose of 3 million units every 8 h) versus meropenem (2 g every 8 h), both in combination with levofloxacin (500 mg every 12 h) for 7–14 days in patients with late VAP. Between May 2012 and October 2015, 232 patients were randomly assigned to the 2 treatment groups. The primary endpoint was mortality at 28 days after randomization in the microbiologically modified intention-to-treat (mMITT) population. Secondary outcomes included clinical and microbiological cure, renal function at the end of the treatment, and serious adverse events. The study was interrupted after the interim analysis due to excessive nephrotoxicity in the colistin group; therefore, the sample size was not achieved. Results: A total of 157 (67.7%) patients were included in the mMITT population, 36 of whom (22.9%) had VAP caused by CR-GNB. In the mMITT population, no significant difference in mortality between the colistin group (19/82, 23.2%) and the meropenem group (19/75, 25.3%) was observed, with a risk difference of − 2.16 (− 15.59 to 11.26, p = 0.377); the noninferiority of colistin was not demonstrated due to early termination and limited number of patients infected by carbapenem-resistant pathogens. Colistin plus levofloxacin increased the incidence of renal failure (40/120, 33.3%, versus 21/112, 18.8%; p = 0.012) and renal replacement therapy (11/120, 9.1%, versus 2/112, 1.8%; p = 0.015). Conclusions: This study did not demonstrate the noninferiority of colistin compared with meropenem, both combined with levofloxacin, in terms of efficacy in the empirical treatment of late VAP but demonstrated the greater nephrotoxicity of colistin. These findings do not support the empirical use of colistin for the treatment of late VAP due to early termination.Seventh Framework Program of the European Commission. Magic Bullet: 278232

Evaluating the use of a Net-Metering mechanism in microgrids to reducepower generation costs with a swarm-intelligent algorithm

The micro-generation of electricity arises as a clean and efficient alternative to provide electrical power. However, the unpredictability of wind and solar radiation poses a challenge to attend load demand, while maintaining a stable operation of the microgrids (MGs). This paper proposes the modeling and optimization, using a swarm-intelligent algorithm, of a hybrid MG system (HMGS) with a Net-Metering compensation policy. Using real industrial and residential data from a Spanish region, a HMGS with a generic ESS is used to analyze the influence of four different Net-Metering compensation levels regarding costs, percentage of renewable energy sources (RESs), and LOLP. Furthermore, the performance of two ESSs, Lithium Titanate Spinel (Li4Ti5O12 (LTO)) and Vanadium redox flow batteries (VRFB), is assessed in terms of the final $/kWh costs provided by the MG. The results obtained indicate that the Net-Metering policy reduces the surplus from over 14$ dollars of savings, when compared to a MG using a LTO system without Net-Metering.European CommissionAgencia Estatal de InvestigaciónComunidad de Madri

Prevalence of chronic head, neck and low back pain and associated factors in women residing in the Autonomous Region of Madrid (Spain)

AbstractObjectiveTo compare the prevalence of chronic headache (CH), chronic neck pain (CNP) and chronic low back pain (CLBP) in the autonomous region of Madrid by analyzing gender differences and to determine the factors associated with each pain location in women in 2007.MethodsWe analyzed data obtained from adults aged 16 years or older (n = 12,190) who participated in the 2007 Madrid Regional Health Survey. This survey includes data from personal interviews conducted in a representative population residing in family dwellings in Madrid. The presence CH, CNP, and CLBP was analyzed. Sociodemographic features, self-perceived health status, lifestyle habits, psychological distress, drug consumption, use of healthcare services, the search for alternative solutions, and comorbid diseases were analyzed by using logistic regression models.ResultsThe prevalence of CH, CNP and CLBP was significantly higher (P<0.001) in women (7.3%, 8.4%, 14.1%, respectively) than in men (2.2%, 3.2%, 7.8%, respectively). In women, CH, CNP and CBLP were significantly associated with having ≥3 chronic diseases (OR 7.1, 8.5, 5.8, respectively), and with the use of analgesics and drugs for inflammation (OR: 3.5, 1.95, 2.5, respectively). In the bivariate analysis, the factors associated with pain in distinct body locations differed between men and women.ConclusionsThis study found that CH, CNP and CLBP are a major public health problem in women in central Spain. Women have a higher overall prevalence of chronic pain than men. Chronic pain was associated with a higher use of analgesics and healthcare services

A Review of Classification Problems and Algorithms in Renewable Energy Applications

Classification problems and their corresponding solving approaches constitute one of the fields of machine learning. The application of classification schemes in Renewable Energy (RE) has gained significant attention in the last few years, contributing to the deployment, management and optimization of RE systems. The main objective of this paper is to review the most important classification algorithms applied to RE problems, including both classical and novel algorithms. The paper also provides a comprehensive literature review and discussion on different classification techniques in specific RE problems, including wind speed/power prediction, fault diagnosis in RE systems, power quality disturbance classification and other applications in alternative RE systems. In this way, the paper describes classification techniques and metrics applied to RE problems, thus being useful both for researchers dealing with this kind of problem and for practitioners of the field

Stricter Adherence to Dietary Approaches to Stop Hypertension (DASH) and Its Association with Lower Blood Pressure, Visceral Fat, and Waist Circumference in University Students

We are grateful to the university students for their participation in this study.How diet affects blood pressure (BP) in young adults has not been studied in sufficient depth. For this purpose, we analyzed adherence to the Dietary Approaches to Stop Hypertension (DASH) dietary pattern and BP in Spanish university students. The sample population of our cross-sectional study consisted of 244 subjects (18–31 years old), who were in good health. Measurements were taken of their systolic and diastolic BP. A food frequency questionnaire and 72 h food record were used to assess their dietary intake in the previous year. The resulting DASH score was based on foodstuffs that were emphasized or minimized in the DASH diet. Analysis of covariance adjusted for potential confounding factors showed that the mean values for systolic BP, visceral fat rating, and waist circumference (WC) of the subjects in the upper third of the DASH score were significantly lower than those of the subjects in the lower third (for systolic BP: mean difference −4.36 mmHg, p = 0.004; for visceral fat rating: mean difference −0.4, p = 0.024; for waist circumference: mean difference −3.2, p = 0.019). Stricter adherence to the DASH dietary pattern led to a lower BP, visceral fat rating, and WC values in these university students. Nevertheless, further prospective studies are needed to confirm these results.This study was funded by the Programme Contract (2015–2017) of the Faculty of Nursing of Melilla (University of Granada), specifically the research line “Lifestyles and health care in a multicultural population”

An efficient multi-objective evolutionary approach for solving the operation of multi-reservoir system scheduling in hydro-power plants

This paper tackles the short-term hydro-power unit commitment problem in a multi-reservoir system ? a cascade-based operation scenario. For this, we propose a new mathematical modeling in which the goal is to maximize the total energy production of the hydro-power plant in a sub-daily operation, and, simultaneously, to maximize the total water content (volume) of reservoirs. For solving the problem, we discuss the Multi-objective Evolutionary Swarm Hybridization (MESH) algorithm, a recently proposed multi-objective swarm intelligence-based optimization method which has obtained very competitive results when compared to existing evolutionary algorithms in specific applications. The MESH approach has been applied to find the optimal water discharge and the power produced at the maximum reservoir volume for all possible combinations of turbines in a hydro-power plant. The performance of MESH has been compared with that of well-known evolutionary approaches such as NSGA-II, NSGA-III, SPEA2, and MOEA/D in a realistic problem considering data from a hydro-power energy system with two cascaded hydro-power plants in Brazil. Results indicate that MESH showed a superior performance than alternative multi-objective approaches in terms of efficiency and accuracy, providing a profit of $412,500 per month in a projection analysis carried out.European CommissionMinisterio de Economía y CompetitividadComunidad de Madri