Influence of a 1,800 MHz electromagnetic field on the EEG energy

The present study investigated the influence of electromagnetic fields (EMF), similar to that emitted by mobile phones, on brain activity. Ten women and ten men, matched for age and educational level, performed a short memory task (Wechsler test), with simultaneous Electroencephalogram (EEG) recordings at 15 scalp electrodes, both without (baseline) and with exposure to an 1,800 MHz signal. The EEG energy was found concentrated at the four basic EEG bands [α (8–13 Hz), β (14–30 Hz), δ (0–4 Hz), and θ (5–7 Hz)]. The analysis revealed that in the presence of EMF, the energy of the β band was significantly greater for females than for males at the majority of the electrodes. Since beta oscillation is associated with the shift of attention during the perception, these findings may indicate that the particular EMF (1,800 MHz signal) exerts an influence on this brain activity, which appears to be gender-related.     

Feathers of white stork Ciconia ciconia chicks in North‐Eastern Greece,as indicators of geographical variation in mercury contamination

Variations in mercury contamination of ecosystems were assessed among areas of northeast Greece by sampling and analysing feathers of White Stork chicks. Mercury concentrations in stork chick feathers were highest in an area known to be affected by riverborne mercury pollution, and were lowest in an inland area away from rivers or lakes. Although regurgitated pellets indicated a predominantly terrestrial diet among White Stork adults, variation in mercury concentrations among localities seemed to relate to pollution of aquatic rather than terrestrial foods of storks. Toxic thresholds of mercury in this species are unknown, but the highest concentrations, observed in chicks from the Axios Delta (up to 4.1 μg.g^‐1 in feathers) were well above levels having toxic effects in gamebirds. Mercury concentrations in chick feathers increased slightly with chick age and with brood size, but these trends were small by comparison with variations among localities.     

Modeling the formation of chlorination by-products in river waters with different quality

Water chlorination results in formation of a variety of organic compounds, known as chlorination by-products (CBPs), mainly trihalomethanes (THMs) and haloacetic acids (HAAs). Factors affecting their concentrations have been found to be organic matter content of water, pH, temperature, chlorine dose, contact time and bromide concentration, but the mechanisms of their formation are still under investigation. Within this scope, chlorination experiments have been conducted with river waters from Lesvos island, Greece, with different water quality regarding bromide concentration and organic matter content. The factors studied were pH, time and chlorine dose. The determination of CBPs was carried out by gas chromatography techniques. Statistical analysis of the results was focused on the development of multiple regression models for predicting the concentrations of total trihalomethanes and total HAAs based on the use of pH, reaction time and chlorine dose. The developed models, although providing satisfactory estimations of the concentrations of the CBPs, showed lower correlation coefficients than the multiple regression models developed for THMs only during previous study. It seems that the different water quality characteristics of the two river waters in the present study is responsible for this phenomenon. The results indicate that under these conditions the formation of THMs and HAAs in water has a more stochastic character, which is difficult to be described by the conventional regression techniques.     

Heteroscedastic semiparametric models for domestic water consumption aggregated data

Heteroscedastic additive and multiplicative models are proposed to disaggregate household data on water consumption from Athens and provide individual consumption estimates. The models adjust for heteroscedasticity assuming that variances relate to covariates. Household characteristics that can influence consumption are also included into models in order to allow for a clearer measurement of individual characteristics effects. Estimation is accomplished through a penalized least squares approach. The method is applied to a sample of real data related to domestic water consumption in Athens. The results show a greater consumption of water for males while the single-female households are these that use the lowest quantities of water. The consumption curves by age and gender are constructed presenting differences between the two sexes.