Abstract
Satellite altimetry allows the study of sea-level long-term variability on a global and spatially uniform basis. Here quantile regression is applied to derive robust median regression trends of mean sea level as well as trends in extreme quantiles from radar altimetry time series. In contrast with ordinary least squares regression, which only provides an estimate on the rate of change of the mean of data distribution, quantile regression allows the estimation of trends at different quantiles of the data distribution, yielding a more complete picture of long-term variability. Trends derived from basin-wide averaged regional mean sea level time series are robust and similar for all quantiles, indicating that all parts of the data distribution are changing at the same rate. In contrast, trends are not robust and diverge across quantiles in the case of local time series. Trends are under- (over-)estimated in the western (eastern) equatorial Pacific. Furthermore, trends in the lowermost quantile (0.05) are larger than the median trend in the western Pacific, while trends in the uppermost quantile (0.95) are lower than the median trend in the eastern Pacific. These differences in trends in extreme mean sea level quantiles are explained by the exceptional effect of the strong 1997-1998 El Nino-Southern Oscillation (ENSO) event.

Abstract
The classification ofmultivariate time series in terms of their corresponding temporal dependence patterns is a common problem in geosciences, particularly for large datasets resulting from environmental monitoring networks. Here a wavelet-based clustering approach is applied to sea level and atmospheric pressure time series at tide gauge locations in the Baltic Sea. The resulting dendrogram discriminates three spatially-coherent groups of stations separating the southernmost tide gauges, reflecting mainly high-frequency variability driven by zonal wind, from the middle-basin stations and the northernmost stations dominated by lower-frequency variability and the response to atmospheric pressure.

Abstract
The seasonal cycle accounts for about 40 % of the total sea level variability in the Baltic Sea. In a climate change context, changes are expected to occur, not only in mean levels but also in the seasonal characteristics of sea level. The present study addresses the quantification of changes in the seasonal cycle of sea level from a set of century-long tide gauge records in the Baltic Sea. In order to obtain robust estimates of the changes in amplitude and phase of the seasonal cycle, we apply different methods, including continuous wavelet filtering, multi-resolution decomposition based on the maximal overlap discrete wavelet transform, auto-regressive-based decomposition, singular spectrum analysis and empirical mode decomposition. The results show that all methods generally trace a similar long-term variability of the annual cycle amplitudes, and we focus on discrete wavelet analysis as the natural counterpart of classical moving Fourier analysis. In contrast to previous studies suggesting the existence of long-term changes in the seasonal cycle, in particular an increase of the annual amplitude, we find alternating periods of high and low amplitudes without any clear indication of systematic long-term trends. The derived seasonal patterns are spatially coherent, discriminating the stations in the Baltic entrance from the remaining stations in the Baltic basin, for which zonal wind accounts for typically more than 40 % of the variations in amplitude.

Abstract
Atmospheric Electric Potential Gradient (PG) measurements were carried out in three sites forming a triangular array in Southern Portugal. The campaign was performed during the summer, characterized by Saharan dust outbreaks; 16th-17th July 2014 dust event is considered. Short time-scale oscillations of the PG at two of the stations and a mid time-scale suppression of the PG in the three stations are found. Results are interpreted as evidencing long-range dust electrification; attributed to the air-Earth electrical current creating a bipolar charge distribution inside of the dust layer. The relevance of using arrays of sensors, instead of single sited, is highlighted.

Abstract
The knowledge on diet composition of the freshwater mussel Diplodon enno (Ortmann) would aid in its culture and propagation allowing, this way, the replacement of natural endangered populations in Brazil. Microalgae are the main food source for captive mussels and unionids have displayed an ability to sort algae based on the cellular characteristics prior to ingestion. The main objective of the present work is to analyze the phytoplankton composition of the water from and of the gastrointestinal contents of the mussel D. enno, as an initial step for development of a suitable rearing diet. Therefore, water samples and bivalve specimens were collected from S. Francisco River, city of Paulo Afonso, Bahia, Brazil. The microalgal composition found in water and stomach/gut content samples was very diverse being represented by the following divisions: Cyanophyta, Chlorophyta, Dinophyta and Heterokontophyta (Diatoms). Concerning the relative abundance of microalgae divisions, it is possible to state, for the water and gastrointestinal contents, that Cyanophyta represents 15% and 14%, Chlorophyta 54% in both, Heterokontophyta 31% and 27% and Dinophyta 0% and 5%, respectively. According to the Brazilian CETESB criteria for phytoplankton species classification, 50% of Cyanophyta and 15% of Chlorophyta species observed in the water samples were classified as "very frequent", as were 68% of Heterokontophyta and 33% of Chlorophyta species in the gut/stomach tract samples. Focusing at a species level, although in the water only Coelastrum sp. and Chroococcus sp. were observed in 100% and 75% of the samples, respectively, in the gastrointestinal tract the species Staurastrum sp., Aulacoseira sp., Scenedesmus sp. and Fragilaria crotonensis occurred in 80% to 100% of the samples. The present results showed that D. enno feeds not only on small chlorophytes microalgae, due to their convenient size that facilitates higher feeding rates, but also on large size diatoms, due to a possible nutritional advantage for the bivalves. Thus, a diet composed by large diatoms and small chlorophytes microalgae may be considered as the most reasonable for the maintenance of D. enno populations.

Abstract
The detection of thrombin based on aptamer binding is studied using two different optical fiber-based configurations: long period gratings coated with a thin layer of titanium dioxide and surface plasmon resonance devices in optical fibers coated with a multilayer of gold and titanium dioxide. These structures are functionalized and the performance to detect thrombin in the range 10 to 100 nM is compared in transmission mode. The sensitivity to the surrounding refractive index (RI) of the plasmonic device is higher than 3100 nmRIU(-1) in the RI range 1.335 to 1.355, a factor of 20 greater than the sensitivity of the coated grating. The detection of 10 nM of thrombin was accomplished with a wavelength shift of 3.5 nm and a resolution of 0.54 nM. (C) 2016 Society of Photo-Optical Instrumentation Engineers (SPIE)