Task sensitivity in EEG biometric recognition

This work explores the sensitivity of electroencephalographic-based biometric recognition to the type of tasks required by subjects to perform while their brain activity is being recorded. A novel wavelet-based feature is used to extract identity information from a database of 109 subjects who performed four different motor movement/imagery tasks while their data was recorded. Training and test of the system was performed using a number of experimental protocols to establish if training with one type of task and tested with another would significantly affect the recognition performance. Also, experiments were conducted to evaluate the performance when a mixture of data from different tasks was used for training. The results suggest that performance is not significantly affected when there is a mismatch between training and test tasks. Furthermore, as the amount of data used for training is increased using a combination of data from several tasks, the performance can be improved. These results indicate that a more flexible approach may be incorporated in data collection for EEG-based biometric systems which could facilitate their deployment and improved performance

Impacts of climate warming on the long-term dynamics of key fish species in 24 European lakes

Fish play a key role in the trophic dynamics of lakes. With climate warming, complex changes in fish assemblage structure may be expected owing to direct effects of temperature and indirect effects operating through eutrophication, water level changes, stratification and salinisation. We reviewed published and new long-term (10–100 years) fish data series from 24 European lakes (area: 0.04–5,648 km2; mean depth: 1–177 m; a north–south gradient from Sweden to Spain). Along with an annual temperature increase of about 0.15–0.3°C per decade profound changes have occurred in either fish assemblage composition, body size and/or age structure during recent decades and a shift towards higher dominance of eurythermal species. These shifts have occurred despite a reduction in nutrient loading in many of the lakes that should have benefited the larger-sized individuals and the fish species typically inhabiting cold-water, low-nutrient lakes. The cold-stenothermic Arctic charr has been particularly affected and its abundance has decreased in the majority of the lakes where its presence was recorded. The harvest of cool-stenothermal brown trout has decreased substantially in two southern lakes. Vendace, whitefish and smelt show a different response depending on lake depth and latitude. Perch has apparently been stimulated in the north, with stronger year classes in warm years, but its abundance has declined in the southern Lake Maggiore, Italy. Where introduced, roach seems to take advantage of the higher temperature after years of low population densities. Eurythermal species such as common bream, pike–perch and/or shad are apparently on the increase in several of the lakes. The response of fish to the warming has been surprisingly strong and fast in recent decades, making them ideal sentinels for detecting and documenting climate-induced modifications of freshwater ecosystems

Effects of water ingestion throughout exercise and recovery on cardiac autonomic modulation during and after exercise

Purpose: To analyze the effects of water intake on heart rate variability (HRV) during and after exercise. Methods: Thirty-one young males performed three different procedures: I) a maximal exercise test to determine the load for the protocols; II) the control protocol (CP); III) the experimental protocol (EP). The protocols comprised 10 minutes at rest, 90 minutes of treadmill exercise (60% of VO2 peak), and 60 minutes of recovery. No rehydration beverage consumption was allowed during the CP. During the EP, the participants were given water every 15 minutes, being that the amount of water to be ingested by each volunteer was divided over the time of exercise and recovery. For the analysis of HRV data, time and frequency domain indices were investigated in the following moments (M): M1 (5 minutes final of rest), M2 (25-30 minutes of exercise), M3 (55-60 minutes of exercise), M4 (85-90 minutes of exercise), M5 (5-10 minutes of recovery), M6 (15-20 minutes of recovery), M7 (25-30 minutes of recovery), M8 (40-45 minutes of recovery), and M9 (55-60 minutes of recovery). Results: There was no statistically significant difference between the groups that were examined during the exercise. HRV values for the CP and EP at the end of the exercise period were as follows SDNN (5.95±1.89 vs 6.89±2.11); RMSSD (3.29±0.78 vs 3.39±0.95); HF [nu] (24.06±14.26 vs 19.10±11.94); LF [nu] (75.93±14.26 vs 80.89±11.94); HF [ms2] (0.90±1.16 vs 0.94±0.89); LF [ms2] (4.65±5.94 vs 5.35±5.09); and LF/HF ratio (4.64±3.15 vs 6.95±5.57). HRV values for the CP and the EP at the end of the recovery period were as follows: SDNN (39.63±19.63 vs 49.95±17.79); RMSSD (21.63±15.55 vs 36.43±22.73); HF [ms2] (285.51±392.27 vs 699.29±699.66); LF [nu] (74.55±13.25 vs 61.19±19.27); and HF [nu] (25.44±13.25 vs 38.8±19.27). Conclusion: The hydration with water was not enough to significantly influence the linear HRV indices during exercise; however, it promoted faster recovery of these variables after exercise.Foundation for Research Support of São Paulo StateUniversidade Federal de São PauloUniversidade Estadual Paulista Julio de Mesquita FilhoFaculdade de Medicina do ABCUniversidade Estadual Paulista Julio de Mesquita FilhoFoundation for Research Support of São Paulo State: 2011/10887-