Solución de un modelo de arreglos fotovoltaicos serie-paralelo utilizando algoritmos de optimización global

Models of series-parallel (SP) photovoltaic (PV) arrays focus on the system of nonlinear equations that represents the array’s electrical behavior. The solution of the system of nonlinear equations can be posed as an optimization problem and solved with different methods; however, the models do not formulate the optimization problem and do not evaluate different optimization algorithms for its solution. This paper proposes a solution, using global optimization algorithms, of the mathematical model that describes the electrical behavior of a SP generator, operating under uniform and partial shading conditions. Such a model is constructed by dividing the generator into strings and representing each module in the string with the single-diode model. Consequently, for each string a system of nonlinear equations is build applying the Kirchhoff’s laws, where the unknowns are the modules’ voltages. The solution of the resulting nonlinear equation system is posed as an optimization problem, where the objective function is defined as the sum of the squared of each nonlinear equation. Minimum and maximum values of each voltage are defined from the datasheet information of the modules and bypass diodes. As a demonstrative example, we arbitrarily select two well-known algorithms to solve this problem: Genetic Algorithms and Particle Swarm Optimization. Simulation results show that both algorithms solve the optimization problem and allow the reproduction of the generator’s characteristic curves. Moreover, the results also indicate that the optimization problem is correctly defined, which opens the possibility explore other optimization algorithms to reduce the computation time.Los modelos de arreglos fotovoltaicos (FV) en serie-paralelo (SP) se enfocan en el sistema de ecuaciones no lineales que represental comportamiento eléctrico del arreglo. La solución del sitemas de ecuaciones se puede plantear como un problema de optimización y resolverse con diferentes métodos; sin embargo, los modelos no formulan el problema de optimización y no evaluan diferentes algoritmos de optimización para su solución. Este artículo propone una solución, utilizando algoritmos de optimización global, del modelo matemático que describe el comportamiento eléctrico de un generador fotovoltaico en serie-paralelo, que opera bajo condiciones uniformes y de sombreados parciales. Dicho modelo se construye dividiendo el generador en cadenas y representando cada módulo en la cadena con el modelo de diodo-único. En consecuencia, para cada cadena se construye un sistema de ecuaciones no lineales aplicando las leyes de Kirchhoff, en donde las incógnitas son los voltajes de los módulos. La solución del sistema de ecuaciones no lineales resultante se plantea como un problema de optimización, donde la función objetivo se define como la suma del cuadrado de cada ecuación no lineal. Los valores mínimos y máximos de cada voltaje se definen a partir de la información de la hoja de datos de los módulos y de los diodos de derivación. Como ejemplo demostrativo, se seleccionaron arbitrariamente dos algoritmos bien conocidos para resolver este problema: Algoritmos Genéticos y Optimización por Enjambre de Partículas. Los resultados de simulación muestran que los dos algoritmos ambos algoritmos resuelven el problema de optimización y permiten la reproducción de las curvas características del generador. Adicionalmente, los resultados también indican que el problema de optimización se definió correctamente, lo cual abre la posibilidad de explorar otros algoritmos de optimización para reducir el tiempo de cómputo

Solución de un modelo de arreglos fotovoltaicos serie-paralelo utilizando algoritmos de optimización global

Models of series-parallel (SP) photovoltaic (PV) arrays focus on the system of nonlinear equations that represents the array’s electrical behavior. The solution of the system of nonlinear equations can be posed as an optimization problem and solved with different methods; however, the models do not formulate the optimization problem and do not evaluate different optimization algorithms for its solution. This paper proposes a solution, using global optimization algorithms, of the mathematical model that describes the electrical behavior of a SP generator, operating under uniform and partial shading conditions. Such a model is constructed by dividing the generator into strings and representing each module in the string with the single-diode model. Consequently, for each string a system of nonlinear equations is build applying the Kirchhoff’s laws, where the unknowns are the modules’ voltages. The solution of the resulting nonlinear equation system is posed as an optimization problem, where the objective function is defined as the sum of the squared of each nonlinear equation. Minimum and maximum values of each voltage are defined from the datasheet information of the modules and bypass diodes. As a demonstrative example, we arbitrarily select two well-known algorithms to solve this problem: Genetic Algorithms and Particle Swarm Optimization. Simulation results show that both algorithms solve the optimization problem and allow the reproduction of the generator’s characteristic curves. Moreover, the results also indicate that the optimization problem is correctly defined, which opens the possibility explore other optimization algorithms to reduce the computation time.Los modelos de arreglos fotovoltaicos (FV) en serie-paralelo (SP) se enfocan en el sistema de ecuaciones no lineales que represental comportamiento eléctrico del arreglo. La solución del sitemas de ecuaciones se puede plantear como un problema de optimización y resolverse con diferentes métodos; sin embargo, los modelos no formulan el problema de optimización y no evaluan diferentes algoritmos de optimización para su solución. Este artículo propone una solución, utilizando algoritmos de optimización global, del modelo matemático que describe el comportamiento eléctrico de un generador fotovoltaico en serie-paralelo, que opera bajo condiciones uniformes y de sombreados parciales. Dicho modelo se construye dividiendo el generador en cadenas y representando cada módulo en la cadena con el modelo de diodo-único. En consecuencia, para cada cadena se construye un sistema de ecuaciones no lineales aplicando las leyes de Kirchhoff, en donde las incógnitas son los voltajes de los módulos. La solución del sistema de ecuaciones no lineales resultante se plantea como un problema de optimización, donde la función objetivo se define como la suma del cuadrado de cada ecuación no lineal. Los valores mínimos y máximos de cada voltaje se definen a partir de la información de la hoja de datos de los módulos y de los diodos de derivación. Como ejemplo demostrativo, se seleccionaron arbitrariamente dos algoritmos bien conocidos para resolver este problema: Algoritmos Genéticos y Optimización por Enjambre de Partículas. Los resultados de simulación muestran que los dos algoritmos ambos algoritmos resuelven el problema de optimización y permiten la reproducción de las curvas características del generador. Adicionalmente, los resultados también indican que el problema de optimización se definió correctamente, lo cual abre la posibilidad de explorar otros algoritmos de optimización para reducir el tiempo de cómputo

Metodología para la solución de modelos masa-resorte-amortiguador (MRA), mediante algoritmos de optimización global

This article describes one way to solve the mathematical model of a system, which is made up of a Mass-Spring-Dashpot (MSD), by using the virtual firefly metaheuristic algorithm. By employing this strategy, the MSD problems are transformed into problems of minimization of the system’s maximum frequency for all its natural frequencies in such a way that the value found corresponds to the global minimum. The viability of this strategy was demonstrated by solving some typical examples of MSD systems. It was concluded that this algorithm is helpful, for it allows the user to dedicate more time to the analysis of the system itself rather than to the solution methods of the model. It was also significant as an unconventional way to resolve this kind of problems numerically.En el presente artículo se propone una metodología para resolver el modelo matemático de un sistema compuesto de masa-resorte-amortiguador (MRA), mediante el uso de un método de optimización global, que, como ejemplo ilustrativo, se utilizó el algoritmo de la luciérnaga virtual (ALV). Con esta estrategia, los problemas MRA se transforman en problemas de optimización (minimización de la frecuencia máxima del sistema para todas sus frecuencias naturales), de tal forma que el valor encontrado es el mínimo global. Se demostró la viabilidad de esta estrategia, mediante la solución de algunos ejemplos demostrativos de sistemas MRA descritos en el artículo. Se concluye que esta estrategia resultó ser de gran ayuda, pues permite concentrar al usuario en el análisis del mecanismo propiamente, en lugar de la metodología de solución del modelo. Resultó igualmente útil como una forma no convencional de resolver este tipo de problemas numéricamente

Obstetricia integral siglo XXI. Tomo II

El libro Obstetricia Integral siglo XXI, Tomo II, es una publicación virtual de la Facultad de Medicina, se trata de la continuación sobre el análisis detallado de los principales tópicos en el área de la obstetricia, realizada por un grupo interdisciplinario de investigadores comprometidos con el mejoramiento de la calidad en el cuidado de la salud de la mujer gestante. Se ha procurado un balance entre los aspectos básicos de fisiopatología y las guías de atención clínica soportadas en evidencias científicas, con el ánimo de brindarle al lector un equilibrio entre las bases biopsico-sociales de la salud y la enfermedad y los aspectos prácticos de la atención clínica.Vargas Fiesco, Diana Carolina and Rubio Romero, Jorge Andrés and Ruiz Parra, Ariel Iván and Rodríguez, Luis Martín and Aragón, Miguel Eduardo and Arteaga Díaz, Clara Eugenia and Riaño, Jorge Enrique and Arenas Gamboa, Jaime and Ramírez Martínez, Javier Andrés and Amaya Guío, Jairo and Gaitán , Magda Alexandry and Gallego Arbeláez, Jaime and Cortés Díaz, Daniel Otálvaro and Ángel Müller, Edith and Bracho Ch., Alcides C. and Bautista Charry, Alejandro and Rodríguez Ramos, Marcela and Navarro Milanés, Alfonso and Díaz Cruz, Luz Amparo and Mercado Pedroza, Manuel Esteban and Gaitán Duarte, Hernando and Gómez Sánchez, Pio Iván and Peña, Diana Marcela and Calvo Gómez, José Manuel and Parra Pineda, Mario Orlando and Cárdenas Muñoz, María Luisa (2010) Obstetricia integral siglo XXI. Tomo II. Facultad de Medicina, Universidad Nacional de Colombia, Bogotá. ISBN 978958447618

Treatment with tocilizumab or corticosteroids for COVID-19 patients with hyperinflammatory state: a multicentre cohort study (SAM-COVID-19)

Objectives: The objective of this study was to estimate the association between tocilizumab or corticosteroids and the risk of intubation or death in patients with coronavirus disease 19 (COVID-19) with a hyperinflammatory state according to clinical and laboratory parameters. Methods: A cohort study was performed in 60 Spanish hospitals including 778 patients with COVID-19 and clinical and laboratory data indicative of a hyperinflammatory state. Treatment was mainly with tocilizumab, an intermediate-high dose of corticosteroids (IHDC), a pulse dose of corticosteroids (PDC), combination therapy, or no treatment. Primary outcome was intubation or death; follow-up was 21 days. Propensity score-adjusted estimations using Cox regression (logistic regression if needed) were calculated. Propensity scores were used as confounders, matching variables and for the inverse probability of treatment weights (IPTWs). Results: In all, 88, 117, 78 and 151 patients treated with tocilizumab, IHDC, PDC, and combination therapy, respectively, were compared with 344 untreated patients. The primary endpoint occurred in 10 (11.4%), 27 (23.1%), 12 (15.4%), 40 (25.6%) and 69 (21.1%), respectively. The IPTW-based hazard ratios (odds ratio for combination therapy) for the primary endpoint were 0.32 (95%CI 0.22-0.47; p < 0.001) for tocilizumab, 0.82 (0.71-1.30; p 0.82) for IHDC, 0.61 (0.43-0.86; p 0.006) for PDC, and 1.17 (0.86-1.58; p 0.30) for combination therapy. Other applications of the propensity score provided similar results, but were not significant for PDC. Tocilizumab was also associated with lower hazard of death alone in IPTW analysis (0.07; 0.02-0.17; p < 0.001). Conclusions: Tocilizumab might be useful in COVID-19 patients with a hyperinflammatory state and should be prioritized for randomized trials in this situatio

Clonal chromosomal mosaicism and loss of chromosome Y in elderly men increase vulnerability for SARS-CoV-2

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, COVID-19) had an estimated overall case fatality ratio of 1.38% (pre-vaccination), being 53% higher in males and increasing exponentially with age. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, we found 133 cases (1.42%) with detectable clonal mosaicism for chromosome alterations (mCA) and 226 males (5.08%) with acquired loss of chromosome Y (LOY). Individuals with clonal mosaic events (mCA and/or LOY) showed a 54% increase in the risk of COVID-19 lethality. LOY is associated with transcriptomic biomarkers of immune dysfunction, pro-coagulation activity and cardiovascular risk. Interferon-induced genes involved in the initial immune response to SARS-CoV-2 are also down-regulated in LOY. Thus, mCA and LOY underlie at least part of the sex-biased severity and mortality of COVID-19 in aging patients. Given its potential therapeutic and prognostic relevance, evaluation of clonal mosaicism should be implemented as biomarker of COVID-19 severity in elderly people. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, individuals with clonal mosaic events (clonal mosaicism for chromosome alterations and/or loss of chromosome Y) showed an increased risk of COVID-19 lethality

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Penilaian Kinerja Keuangan Koperasi di Kabupaten Pelalawan

This paper describe development and financial performance of cooperative in District Pelalawan among 2007 - 2008. Studies on primary and secondary cooperative in 12 sub-districts. Method in this stady use performance measuring of productivity, efficiency, growth, liquidity, and solvability of cooperative. Productivity of cooperative in Pelalawan was highly but efficiency still low. Profit and income were highly, even liquidity of cooperative very high, and solvability was good

Impacts of the Tropical Pacific/Indian Oceans on the Seasonal Cycle of the West African Monsoon

The current consensus is that drought has developed in the Sahel during the second half of the twentieth century as a result of remote effects of oceanic anomalies amplified by local land–atmosphere interactions. This paper focuses on the impacts of oceanic anomalies upon West African climate and specifically aims to identify those from SST anomalies in the Pacific/Indian Oceans during spring and summer seasons, when they were significant. Idealized sensitivity experiments are performed with four atmospheric general circulation models (AGCMs). The prescribed SST patterns used in the AGCMs are based on the leading mode of covariability between SST anomalies over the Pacific/Indian Oceans and summer rainfall over West Africa. The results show that such oceanic anomalies in the Pacific/Indian Ocean lead to a northward shift of an anomalous dry belt from the Gulf of Guinea to the Sahel as the season advances. In the Sahel, the magnitude of rainfall anomalies is comparable to that obtained by other authors using SST anomalies confined to the proximity of the Atlantic Ocean. The mechanism connecting the Pacific/Indian SST anomalies with West African rainfall has a strong seasonal cycle. In spring (May and June), anomalous subsidence develops over both the Maritime Continent and the equatorial Atlantic in response to the enhanced equatorial heating. Precipitation increases over continental West Africa in association with stronger zonal convergence of moisture. In addition, precipitation decreases over the Gulf of Guinea. During the monsoon peak (July and August), the SST anomalies move westward over the equatorial Pacific and the two regions where subsidence occurred earlier in the seasons merge over West Africa. The monsoon weakens and rainfall decreases over the Sahel, especially in August.Peer reviewe