Artificial oxygen fluxes measured by the eddy correlation method using stirring-sensitive oxygen microsensor and oxygen optodes in a flume experiment

In the last decade, the aquatic eddy correlation (EC) technique has proven to be a powerful approach for non-invasive measurements of oxygen fluxes across the sediment water interface. Fundamental to the EC approach is the correlation of turbulent velocity and oxygen concentration fluctuations measured with high frequencies in the same sampling volume. Oxygen concentrations are commonly measured with fast responding electrochemical microsensors. However, due to their own oxygen consumption, electrochemical microsensors are sensitive to changes of the diffusive boundary layer surrounding the probe and thus to changes in the ambient flow velocity. The so-called stirring sensitivity of microsensors constitutes an inherent correlation of flow velocity and oxygen sensing and thus an artificial flux which can confound the benthic flux determination. To assess the artificial flux we measured the correlation between the turbulent flow velocity and the signal of oxygen microsensors in a sealed annular flume without any oxygen sinks and sources. Experiments revealed significant correlations, even for sensors designed to have low stirring sensitivities of ~0.7%. The artificial fluxes depended on ambient flow conditions and, counter intuitively, increased at higher velocities because of the nonlinear contribution of turbulent velocity fluctuations. The measured artificial fluxes ranged from 2 - 70 mmol m**-2 d**-1 for weak and very strong turbulent flow, respectively. Further, the stirring sensitivity depended on the sensor orientation towards the flow. Optical microsensors (optodes) that should not exhibit a stirring sensitivity were tested in parallel and did not show any significant correlation between O2 signals and turbulent flow. In conclusion, EC data obtained with electrochemical sensors can be affected by artificial flux and we recommend using optical microsensors in future EC-studies. Flume experiments were conducted in February 2013 at the Institute for Environmental Sciences, University of Koblenz-Landau Landau. Experiments were performed in a closed oval-shaped acrylic glass flume with cross-sectional width of 4 cm and height of 10 cm and total length of 54 cm. The fluid flow was induced by a propeller driven by a motor and mean flow velocities of up to 20 cm s-1 were generated by applying voltages between 0 V and 4 V DC. The flume was completely sealed with an acrylic glass cover. Oxygen sensors were inserted through rubber seal fittings and allowed positioning the sensors with inclinations to the main flow direction of ~60°, ~95° and ~135°. A Clark type electrochemical O2 microsensor with a low stirring sensitivity (0.7%) was tested and a fast-responding needle-type O2 optode (PyroScience GmbH, Germany) was used as reference as optodes should not be stirring sensitive. Instantaneous three-dimensional flow velocities were measured at 7.4 Hz using stereoscopic particle image velocimetry (PIV). The velocity at the sensor tip was extracted. The correlation of the fluctuating O2 sensor signals and the fluctuating velocities was quantified with a cross-correlation analysis. A significant cross-correlation is equivalent to a significant artificial flux. For a total of 18 experiments the flow velocity was adjusted between 1.7 and 19.2 cm s**-1, and 3 different orientations of the electrochemical sensor were tested with inclination angles of ~60°, ~95° and ~135° with respect to the main flow direction. In experiments 16-18, wavelike flow was induced, whereas in all other experiments the motor was driven by constant voltages. In 7 experiments, O2 was additionally measured by optodes. Although performed simultaneously with the electrochemical sensor, optode measurements are listed as separate experiments (denoted by the attached 'op' in the filename), because the velocity time series was extracted at the optode tip, located at a different position in the flume.

qPCR counts of mRNA for hepatic reference gene selection in adult female Atlantic salmon from perturbation experiments under artificial temperature conditions

The dataset contains raw data (quantification cycle) for a study which determined the most suitable hepatic reference genes for normalisation of qPCR data orginating from adult (entire reproductive season) Atlantic salmon (14 days) exposed to 14 and 22 degrees C. These results will be useful for anyone wanting to study the effects of climate change/elevated temperature on reproductive physiology of fish (and perhaphs other vertebrates). In addition, a target gene (vitellogenin) has normalised using an inappropriate and an 'ideal' reference gene to demonstrate the consequences of using an unstable reference gene for normalisation. For the adult experiment, maiden and repeat adult females were held at the Salmon Enterprises of Tasmania (SALTAS) Wayatinah Hatchery (Tasmania, Australia) at ambient temperature and photoperiod in either 200 (maidens) or 50 (repeats) m3 circular tanks at stocking densities of 12-18, and 24-36 kg m-3 for maidens and repeats, respectively, until transfered to the experimental tanks.

Seawater carbonate chemistry and early development of the sea urchin Lytechinus variegatus in a laboratory experiment using artificial seawater

Land-based aquaculture facilities often utilize additional bicarbonate sources such as commercial sea salts that are designed to boost alkalinity in order to buffer seawater against reductions in pH. Despite these preventative measures, many facilities are likely to face occasional reductions in pH and corresponding reductions in carbonate saturation states due to the accumulation of metabolic waste products. We investigated the impact of reduced carbonate saturation states (Omega Ca, Omega Ar) on embryonic developmental rates, larval developmental rates, and echinoplutei skeletal morphometrics in the common edible sea urchin Lytechinus variegatus under high alkalinity conditions. Commercial artificial seawater was bubbled with a mixture of air and CO2 gas to reduce the carbonate saturation state. Rates of embryonic and larval development were significantly delayed in both the low and extreme low carbonate saturation state groups relative to the control at a given time. Although symmetry of overall skeletal body lengths was not affected, allometric relationships were significantly different between treatment groups. Larvae reared under ambient conditions had significantly greater postoral arm and overall body lengths relative to body lengths than larvae grown under extreme low carbonate saturation state conditions, indicating that extreme changes in the carbonate system affected not only developmental rates but also larval skeletal shape. Reduced rates of embryonic development and delayed and altered larval skeletal growth are likely to negatively impact larval culturing of L. variegatus in land-based, intensive culture situations where calcite and aragonite saturation states are lowered by the accumulation of metabolic waste products.

Counts and abundance of macrozoobenthic organisms settled in artificial soft sediment at Brandal, Kongsfjorden, Spitsbergen

In the Arctic the currently observed rising air temperature results in more frequent calving of icebergs. The latter are derived from tidewater glaciers. Arctic macrozoobenthic soft-sediment communities are considerably disturbed by direct hits and sediment reallocation caused by iceberg scouring. With the aim to describe the primary succession of macrozoobenthic communities following these events, scientific divers installed 28 terracotta containers in the soft-sediment off Brandal (Kongsfjorden, Svalbard, Norway) at 20 m water depth in 2002. The containers were filled with a bentonite-sand-mixture resembling the natural sediment. Samples were taken annually between 2003 and 2007. A shift from pioneering species (e.g. Cumacea: Lamprops fuscatus) towards more specialized taxa, as well as from surface-detritivores towards subsurface-detritivores was observed. This is typical for an ecological succession following the facilitation and inhibition succession model. Similarity between experimental and non-manipulated communities from 2003 was significantly highest after three years of succession. In the following years similarity decreased, probably due to elevated temperatures, which prevented the fjord-system from freezing. Some organisms numerically important in the non-manipulated community (e.g., the polychaete Dipolydora quadrilobata) did not colonies the substrate during the experiment. This suggests that the community had not fully matured within the first three years. Later, the settlement was probably impeded by consequences of warming temperatures. This demonstrates the long-lasting effects of severe disturbances on Arctic macrozoobenthic communities. Furthermore, environmental changes, such as rising temperatures coupled with enhanced food availability due to an increasing frequency of ice-free days per year, may have a stronger effect on succession than exposure time.

Dendritic-Like Reliable Computation in Artificial Neurons

Dendritic computation is a term that has been in neuro physiological research for a long time [1]. It is still controversial and far for been clarified within the concepts of both computation and neurophysiology [2], [3]. In any case, it hasnot been integrated neither in a formal computational scheme or structure, nor into formulations of artificial neural nets. Our objective here is to formulate a type of distributed computation that resembles dendritic trees, in such a way that it shows the advantages of neural network distributed computation, mostly the reliability that is shown under the existence of holes (scotomas) in the computing net, without ?blind spots?.

Image sub-segmentation by PFCM and Artificial Neural Networks to detect pore space in 2D and 3D CT soil images

The image by Computed Tomography is a non-invasive alternative for observing soil structures, mainly pore space. The pore space correspond in soil data to empty or free space in the sense that no material is present there but only fluids, the fluid transport depend of pore spaces in soil, for this reason is important identify the regions that correspond to pore zones. In this paper we present a methodology in order to detect pore space and solid soil based on the synergy of the image processing, pattern recognition and artificial intelligence. The mathematical morphology is an image processing technique used for the purpose of image enhancement. In order to find pixels groups with a similar gray level intensity, or more or less homogeneous groups, a novel image sub-segmentation based on a Possibilistic Fuzzy c-Means (PFCM) clustering algorithm was used. The Artificial Neural Networks (ANNs) are very efficient for demanding large scale and generic pattern recognition applications for this reason finally a classifier based on artificial neural network is applied in order to classify soil images in two classes, pore space and solid soil respectively.

First steps in the discovery of patterns in the academic results of telecommunication engineering students in the subjects Analysis of Circuits and Mathematics

In this paper, the results of six years of research in engineering education, in the application of the European Higher Education Area (EHEA) to improve the performance of the students in the subject Analysis of Circuits of Telecommunication Engineering, are analysed taking into consideration the fact that there would be hidden variables that both separate students into subgroups and show the connection among several basic subjects such as Analysis of Circuits (AC) and Mathematics (Math). The discovery of these variables would help us to explain the characteristics of the students through the teaching and learning methodology, and would show that there are some characteristics that instructors do not take into account but that are of paramount importance