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Aim: To measure the prevalence of 3,4-methylenedioxymethamphetamine (MDMA) and other drug use in young males entering compulsory military service in Asturias (northern Spain) and to define trends in MDMA use in this group during the period from 1995 to 1999. We also sought to determine whether MDMA users have distinct personality features or higher levels of sensation seeking. Methods: 3,634 conscripts [mean age (SD) = 20.19 years (2.52)] who entered military service during the period between 1995 and 1999 were evaluated using the World Health Organization (WHO) questionnaire for drug consumption, the Eysenck Personality Questionnaire-A (EPQ-A), and the Zuckerman Sensation Seeking Scale. Results and Conclusions: The prevalence of lifetime, previous year and previous month MDMA use among military recruits between 1995 and 1999 was 10.9, 7.8 and 4.5%, ranking fifth among illicit drugs ever used. Once individuals used MDMA for the first time, they were likely to use it again, with 71% of individuals who had ever used MDMA reporting that they had used it during the past year (ranking second only to hallucinogens), and 41% reporting having used it in the last month. Compared to recruits who had never used MDMA (but who may have used other illicit drugs), MDMA users had a more extensive drug abuse history. Recruits who had used MDMA during the year prior to study had significantly higher scores on the Neuroticism and Psychoticism Subscales of the EPQ-A, and reported higher levels of sensation seeking.

With photovoltaic (PV) systems proliferating in the last few years due to the high prices of fossil fuels and pollution issues, among others, it is extremely important to monitor the efficiency of these plants and optimize the energy production process. This will also result in improvements related to the maintenance and security of the installation. In order to do so, the main parameters in the plant must be continuously monitored so that the appropriate actions can be carried out. This monitoring should not only be carried out at a global level, but also at panel-level, so that a better understanding of what is actually happening in the PV plant can be obtained. This paper presents a system based on a wireless sensor network (WSN) that includes all the components required for such monitoring as well as a power supply obtaining the energy required by the sensors from the photovoltaic panels. The system proposed succeeds in identifying all the nodes in the network and provides real-time monitoring while tracking efficiency, features, failures and weaknesses from a single cell up to the whole infrastructure. Thus, the decision-making process is simplified, which contributes to reducing failures, wastes and, consequently, costs.

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