mscastillo@ugr.es.

The purpose of the present study is to characterize electron contamination in photon beams in different clinical situations. Variations with field size, beam modifier (tray, shaping block) and source-surface distance (SSD) were studied. Percentage depth dose measurements with and without a purging magnet and replacing the air by helium were performed to identify the two electron sources that are clearly differentiated: air and treatment head. Previous analytical methods were used to fit the measured data, exploring the validity of these models. Electrons generated in the treatment head are more energetic and more important for larger field sizes, shorter SSD, and greater depths. This difference is much more noticeable for the 18 MV beam than for the 6 MV beam. If a tray is used as beam modifier, electron contamination increases, but the energy of these electrons is similar to that of electrons coming from the treatment head. Electron contamination could be fitted to a modified exponential curve. For machine modeling in a treatment planning system, setting SSD at 90 cm for input data could reduce errors for most isocentric treatments, because they will be delivered for SSD ranging from 80 to 100 cm. For very small field sizes, air-generated electrons must be considered independently, because of their different energetic spectrum and dosimetric influence.

The monitoring of natural electromagnetic activity in the extremely low frequency range is considered as a means of obtaining global information on the lightning activity and other parameters concerning the state of the Earth's atmosphere. In this sense, the possible application of the study of Schumann resonances (SRs) to environmental monitoring systems has already been proposed in the recent past. However, the usual lack of details existing in the literature concerning the process of extracting SR parameters hinders the development of global networks intended for environmental purposes. In this paper, the methodology used to extract SR information from data measured at the Sierra Nevada extremely low frequency station, Spain, is described in detail. The process is split in three main parts: the determination of the amplitude spectrum from the low-amplitude noisy signal measured, the anthropogenic noise elimination and, finally, the calculation of an analytical function to fit the filtered amplitude spectrum from which SR parameters can be precisely defined. Some different options in the method are considered, and their effect on the SR results has been quantified. Significant differences in the final results have been observed in some of the options considered. As a conclusion of this work, it becomes clear that, if data from different research groups are to be shared and quantitatively compared, a standardization of the process is required or, at least, some details on the station and this process should be provided together with the SR results.

Abstract-This communication proposes an E-pulse-based scheme for radar target discrimination that provides asymptotically correct results for any level of additive white noise contaminating the radar signal. After multiple sampling of the signal dispersed by the target, it is analytically shown that the cross correlation between the output signals of the E-pulse designed for the standard target, corresponding to two different sampling periods, is asymptotically null, regardless of the amount of contaminating noise. The results obtained by simulation have allowed us to propose a discrimination criterion that produces better results than the original E-pulse technique at very low signal-to-noise ratio (SNR) levels.

We present a study of the Schumann resonance (SR) regular variations (March 2013–February 2017) using the ground‐based magnetometers from the Sierra Nevada station, Spain (37°02′N, 3°19′W). The study is based on the fitting parameters obtained by the Lorentzian fit, calculated for each 10‐min interval record, namely, peak amplitudes, peak frequencies, width of the resonances, and the power spectrum integral for the first three SR modes. We consider three time‐scales in the study: seasonal, monthly, and daily variations. The processed data collected by the Sierra Nevada station are also made public with this work. The general characteristics of the long‐term evolution of the SR are confirmed, but discrepancies appear that require further study comparing recent measurements from different stations. Signatures of the influences of the El Niño phenomenon and the solar cycle to SR have been found.