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In this paper, the Sun and its behavior are studied by means of complex networks. The complex network was built using the Visibility Graph algorithm. This method maps time series into graphs in which every element of the time series is considered as a node and a visibility criterion is defined in order to connect them. Using this method, we construct complex networks for magnetic field and sunspots time series encompassing four solar cycles, and various measures such as degree, clustering coefficient, mean path length, betweenness centrality, eigenvector centrality and decay exponents were calculated. In order to study the system in several time scales, we perform both a global, where the network contains information on the four solar cycles, and a local analysis, involving moving windows. Some metrics correlate with solar activity, while others do not. Interestingly, those metric which seem to respond to varying levels of solar activity in the global analysis, also do in the moving windows analysis. Our results suggest that complex networks can provide a useful way to follow solar activity, and reveal new features on solar cycles.

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In this paper, we study solar magnetic activity by means of a complex network approach. A complex network was built based on information on the space and time evolution of sunspots provided by image recognition algorithms on solar magnetograms taken during the complete 23rd solar cycle. Both directed and undirected networks were built, and various measures such as degree distributions, clustering coefficient, average shortest path, various centrality measures, and Gini coefficients calculated for all them. We find that certain measures are correlated with solar activity and others are anticorrelated, while several measures are essentially constant along the solar cycle. Thus, we show that complex network analysis can yield useful information on the evolution of solar activity and reveal universal features valid at any stage of the solar cycle; the implications of this research for the prediction of solar maxima are discussed as well.

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Background: This work was focused on measuring environmental inefficiency in Mexican dairy farms, considering climate change variables related to the emission of greenhouse gases (GHG) and planetary geomagnetic activity. Methods: The applied methodology measures the eco-efficiency of Mexican dairy farms using the empirical application of a stochastic frontier model of the bioeconomy. The productive sector of the bioeconomy studied was the eco-intensification of the livestock production system (dairies). The environmental inefficiency effect was assumed to be a distribution-independent truncation of a normal distribution with constant variance, while the mean was a linear environmental function of the observable variable. Results: The results showed that the coefficients of the frontier model were highly significant, highlighting the investment in livestock (50%). The inefficiency model had an impact on climate variation with greenhouse gas emissions CH4 (1.96%). The results of the environmental technical efficiency in geometric average were 81.28%. The producers that reached the border with a technical efficiency equal to 1 are the references for the rest, marking the relative technical efficiency. Conclusions: It was concluded that the coefficients in the model were very significant, showing the level of investment in livestock (50%). The low-performance model estimates the impact of climate change on GHG emissions CH4 (1.96%) explaining the trend of increasing GHG emissions, keeping in view that the management of food and cattle during the study period were affected by summer feeding, which allowed considering the activity of GHG emissions. According to the results, the geometric mean environmental performance of engineering is 81.28%.

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Resumen Introducción: Este trabajo presenta las relaciones entre la actividad solar y la incidencia de hospitalizaciones por cuadros depresivos en el registro del Ministerio de Salud de Chile donde se registran todos los egresos hospitalarios entre los años 2001 a 2008. La actividad solar está representada por el número de Wolf, mediante la fórmula R = K (10g+f), donde g corresponde al grupo de manchas solares y f es el número total de manchas solares. Método: Las bases de datos del Ministerio de Salud muestran todos los egresos hospitalarios, tanto de causa psiquiátrica como por otros diagnósticos, incluyendo tantos hospitales públicos como también privados. Para el análisis muestral se seleccionaron los casos que tuvieron como diagnóstico algún episodio depresivo según la clasificación CIE 10 desde F320 hasta F339, ambos incluidos. Se examinó la correlación entre la incidencia anual de hospitalizaciones por depresiones y el número de Wolf promedio para ese determinado año durante el período comprendido entre los años 2001 a 2008, ambos inclusive, lo que corresponde aproximadamente a la mitad de un ciclo solar de 16 años. Resultados: Una menor intensidad de la actividad solar se correlaciona con una mayor frecuencia de hospitalizaciones por depresión en Chile. Conclusiones: Los desórdenes depresivos poseen una correlación inversa significativa con la actividad solar.

Introduction: This paper presents the relations between solar activity and the incidence of hospitalizations for depressive disorder found in the register of the Ministry of Health of Chile, where all the hospital discharges from 2001 to 2008 are kept. Solar activity is represented by the Wolf number, with the formula R = K (10g+f), where g refers to the group of sunspots and f is the total number of sunspots. Method: The databases of the Ministry of Health show all the hospital discharges, whether for psychiatric causes or other diagnoses, including data from public as well as private hospitals. For the sample analysis, two cases diagnosed as depressive disorder according to the classification CIE 10, ranging from F320 to F339, both included, were selected. The correlation between annual incidence of hospitalizations for depression and the average of the Wolf number for that particular year between the period spanning from 2001 to 2008, both included, which corresponds to approximately half of a solar cycle of 16 years. Results: Less intensity of solar activity correlates to a higher frequency of hospitalizations for depression in Chile. Conclusions: Depressive disorders have a significant inverse correlation to solar activity.

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We performed a study of the systolic and diastolic arterial blood pressure behavior under natural variables such as the atmospheric pressure and the horizontal geomagnetic field component. We worked with a group of eight adult hypertensive volunteers, four men and four women, with ages between 18 and 27 years in Mexico City during a geomagnetic storm in 2014. The data was divided by gender, age, and day/night cycle. We studied the time series using three methods: correlations, bivariate analysis, and superposed epoch (within a window of 2 days around the day of occurrence of a geomagnetic storm) analysis, between the systolic and diastolic blood pressure and the natural variables. The correlation analysis indicated a correlation between the systolic and diastolic blood pressure and the atmospheric pressure and the horizontal geomagnetic field component, being the largest during the night. Furthermore, the correlation and bivariate analyses showed that the largest correlations are between the systolic and diastolic blood pressure and the horizontal geomagnetic field component. Finally, the superposed epoch analysis showed that the largest number of significant changes in the blood pressure under the influence of geomagnetic field occurred in the systolic blood pressure for men.

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We discuss the importance of small solar observatories for EPO (Education and Public Outreach), mentioning why they are relevant and what kind of equipment and software require. We stress the fact that technological advances have made them affordable and that they should be widely available. This work is a result of our experience with one: The Carl Sagan Solar Observatory (CSSO). We briefly describe its status and the solar data obtained daily with students participation. We present examples of the data obtained in the visible, Ca II and two in Hα. Data which is widely used for education. Finally we talk about the capability for remote operation as an open invitation for collaboration in educational and scientific projects.

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Background: Exposure to solar activity may be associated with incidence of depressive and manic disorders. Aim: To assess the link between solar activity and appearance of affective disorders. Material and Methods: We examined 1862 clinical records of a psychiatric clinic located in Santiago, Chile. Patients with major depression and manic disorders were included in the study, only when they were admitted at the clinic for the first time. Solar activity was calculated using the Wolf number, which is given by the formula R= K(10g+f), where “g” stands for the groups of sunspots and “f ” is the total number of sunspots. We examined the correlation between annual incidence of hospital admissions and average Wolf numbers for the period 1990-2005, which corresponds to approximately one and half solar cycles of 16 years. Results: A total of 450 medical records corresponding to 299 patients (199 women) with depressive symptoms and 151 patients (73 women) with mania, were analyzed. There was a higher number of admissions for depression during the years with lower solar activity. Admissions due to mania tended to increase in the years with high solar activity. There was a negative correlation between the number of hospital admissions due to depression and solar activity (Spearman r =-0.812, p < 0.01). The association between the latter parameter and admissions due to mania did not reach statistical significance. Conclusions: There is a significant negative association between the rate of hospital admissions due to depressive disorders and solar activity.

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