Along track temperature, Salinity, backscatter, Chlorophyll Fluoresence, and normalized water leaving radiance (nLw).

On the bow of the R/V Roger Revelle was a Satlantic SeaWiFS Aircraft Simulator (MicroSAS) system, used to estimate water-leaving radiance from the ship, analogous to to the nLw derived by the SeaWiFS and MODIS satellite sensors, but free from atmospheric error (hence, it can provide data below clouds).

The system consisted of a down-looking radiance sensor and a sky-viewing radiance sensor, both mounted on a steerable holder on the bow. A downwelling irradiance sensor was mounted at the top of the ship's meterological mast, on the bow, far from any potentially shading structures. These data were used to estimate normalized water-leaving radiance as a function of wavelength. The radiance detector was set to view the water at 40deg from nadir as recommended by Mueller et al. [2003b]. The water radiance sensor was able to view over an azimuth range of ~180deg across the ship's heading with no viewing of the ship's wake. The direction of the sensor was adjusted to view the water 90-120deg from the sun's azimuth, to minimize sun glint. This was continually adjusted as the time and ship's gyro heading were used to calculate the sun's position using an astronomical solar position subroutine interfaced with a stepping motor which was attached to the radiometer mount (designed and fabricated at Bigelow Laboratory for Ocean Sciences). Protocols for operation and calibration were performed according to Mueller [Mueller et al., 2003a; Mueller et al., 2003b; Mueller et al., 2003c]. Before 1000h and after 1400h, data quality was poorer as the solar zenith angle was too low. Post-cruise, the 10Hz data were filtered to remove as much residual white cap and glint as possible (we accept the lowest 5% of the data). Reflectance plaque measurements were made several times at local apparent noon on sunny days to verify the radiometer calibrations.

Within an hour of local apparent noon each day, a Satlantic OCP sensor was deployed off the stern of the R/V Revelle after the ship oriented so that the sun was off the stern. The ship would secure the starboard Z-drive, and use port Z-drive and bow thruster to move the ship ahead at about 25cm s-1. The OCP was then trailed aft and brought to the surface ~100m aft of the ship, then allowed to sink to 100m as downwelling spectral irradiance and upwelling spectral radiance were recorded continuously along with temperature and salinity. This procedure ensured there were no ship shadow effects in the radiometry.

Instruments include a WETLabs wetstar fluorometer, a WETLabs ECOTriplet and a SeaBird microTSG.
Radiometry was done using a Satlantic 7 channel microSAS system with Es, Lt and Li sensors.

Chl data is based on inter calibrating surface discrete Chlorophyll measure with the temporally closest fluorescence measurement and applying the regression results to all fluorescence data.

Data have been corrected for instrument biofouling and drift based on weekly purewater calibrations of the system. Radiometric data has been processed using standard Satlantic processing software and has been checked with periodic plaque measurements using a 2% spectralon standard.

Lw is calculated from Lt and Lsky and is "what Lt would be if the
sensor were looking straight down". Since our sensors are mounted at
40o, based on various NASA protocols, we need to do that conversion.

Lwn adds Es to the mix. Es is used to normalize Lw. Nlw is related to Rrs, Remote Sensing Reflectance

Techniques used are as described in:
Balch WM, Drapeau DT, Bowler BC, Booth ES, Windecker LA, Ashe A (2008) Space-time variability of carbon standing stocks and fixation rates in the Gulf of Maine, along the GNATS transect between Portland, ME, USA, and Yarmouth, Nova Scotia, Canada. J Plankton Res 30:119-139

Thirteen young adults (YA group, mean age 25.5, SD 5.3, 4F/9M) and eleven elderly adults (EA group, mean age 64.2, SD 7.1, 4F/7M) were recruited for the study. All subjects had no medical history of the neural pathological conditions, i.e., stroke, head trauma or tumors.Each subject underwent the sensorimotor integration training (SIT) procedure which consisted in N repetitions of elementary sensorimotor integration task. The task required the participants to classify the duration of presented audio stimulus and execute of one of the motor actions (ME) depending on its duration. Specifically, the participant should clench left or right hand into a fist in response to short (SAS) or long (LAS) audio stimulus. The durations of SAS and LAS were 300 ms and 750 ms, respectively. During ME the hand should be held clenched until the next audio stimulus of the same duration, which informed the participant about the end of ME. The time interval required for SI and ME within single trail was chosen randomly in the range 4--5 s. The pause between the trials was also picked randomly within the range 6--8 s. See Fig. 1A for a single trial timeline. The audio stimuli were presented via audio speakers located on the table in front of the participant. During SIT each participant performed N=60 SI task repetitions (30 per stimulus). The overall duration of the experimental session was approximately 10 minutes per participant.The raw EEG recordings were filtered using the 50 Hz Notch filter. Additionally, the data were filtered using the 5th-order Butterworth filter in the range 1-100 Hz to remove low-frequency artifacts. The ocular and cardiac artifacts were removed using the independent component analysis (ICA). The filtered time-series were segmented into 60 epochs 6 s long each according to the experiment protocol. Each epoch included 3 s of prestimulus EEG and 3 s of poststimulus EEG centered at the presentation of the first audio stimulus. To evaluate the effect of SIT on cortical activation with trial progression the timeline of experimental session (N=60 epochs total, 30 per stimulus) was divided into four equal Intervals: T1 (epochs 1-15); T2 (epochs 16-30); T3 (epochs 31-45); T4 (epochs 46-60). Thus, the interval T1 represented early phase, while the interval T4 represented the last phase of the experiment. The data was then inspected manually and the epochs with the remaining artifacts were rejected. Finally, each interval contained 10 artifact-free epochs (5 epochs per stimulus), 40 total. See Fig. 1B for sampling epochs into sets.Individual epochs for each subject are stored in the attached ._epo.fif files for Python MNE package for M/EEG analysis. Prefix EA or YA in the name of the file identifies the age group, which subject belongs to. Postfix T1, T2, T3 or T4 in the name of the file indicates the interval of SIT.