Blending single beam RoxAnn and multi-beam swathe QTC hydro-acoustic discrimination techniques for the Stonehaven area, Scotland, UK

Surface properties of the seabed in a 180 km2 area of coastal waters (14-57 m depth) off northeast Scotland were mapped by hydro-acoustic discrimination using single and multi-beam echosounders linked to signal processing systems (RoxAnn for the single beam, and Questor Tangent Corporation (QTC) Multiview for the multibeam). Subsequently, two ground truthing surveys were carried out, using grab and TV sampling. The RoxAnn and QTC-Multiview outputs showed strong similarity in their classifications of seabed types. Classifications generated by QTC-Multiview were used to supervise those based on seabed roughness and hardness indices produced by the RoxAnn system and thereby develop a ‘blended’ map based on both systems. The resulting hydro-acoustic classes agreed well with a cluster analysis of data on sediment grain sizes from the grab sampling, and indicated that the area could be described by distinct regions of surface texture and surficial sediments ranging from muddy sand to boulders and rock

Complementary Symmetry Nanowire Logic Circuits: Experimental Demonstrations and in Silico Optimizations

Complementary symmetry (CS) Boolean logic utilizes both p- and n-type field-effect transistors (FETs) so that an input logic voltage signal will turn one or more p- or n-type FETs on, while turning an equal number of n- or p-type FETs off. The voltage powering the circuit is prevented from having a direct pathway to ground, making the circuit energy efficient. CS circuits are thus attractive for nanowire logic, although they are challenging to implement. CS logic requires a relatively large number of FETs per logic gate, the output logic levels must be fully restored to the input logic voltage level, and the logic gates must exhibit high gain and robust noise margins. We report on CS logic circuits constructed from arrays of 16 nm wide silicon nanowires. Gates up to a complexity of an XOR gate (6 p-FETs and 6 n-FETs) containing multiple nanowires per transistor exhibit signal restoration and can drive other logic gates, implying that large scale logic can be implemented using nanowires. In silico modeling of CS inverters, using experimentally derived look-up tables of individual FET properties, is utilized to provide feedback for optimizing the device fabrication process. Based upon this feedback, CS inverters with a gain approaching 50 and robust noise margins are demonstrated. Single nanowire-based logic gates are also demonstrated, but are found to exhibit significant device-to-device fluctuations

Effect of Ga Content on Defect States in CuIn\u3csub\u3e1-x\u3c/sub\u3eGa\u3csub\u3ex\u3c/sub\u3eSe\u3csub\u3e2\u3c/sub\u3e Photovoltaic Devices

Defects in the band gap of CuIn1-xGaxSe2 have been characterized using transient photocapacitance spectroscopy. The measured spectra clearly show response from a band of defects centered around 0.8 eV from the valence band edge as well as an exponential distribution of band tail states. Despite Ga contents ranging from Ga/(In+Ga)=0.0 to 0.8, the defect bandwidth and its position relative to the valence band remain constant. This defect band may act as an important recombination center, contributing to the decrease in device efficiency with increasing Ga content

Scoping the impact of tidal and wave energy extraction on suspended sediment concentrations and underwater light climate

The depth to which sunlight penetrates below the sea surface is one of the key factors determining the species composition and productivity of marine ecosystems. The effects range from the rate and fate of primary production, through the performance of visual predators such as fish, the potential for refuge from predators by migrating to depth, to the scope for seabed stabilisation by algal mats. Light penetration depends partly on spectral absorption by seawater and dissolved substances, but mainly on the scattering caused by suspended particulate material (SPM). Some of this SPM may be of biological origin, but in coastal waters the majority is mineral material originating ultimately from seabed disturbance and land erosion, the latter being deposited in the sea by rivers and aerial processes. SPM is maintained in the water column or deposited on the seabed depending on combinations of hydrodynamic processes including baroclinic (density-driven) or barotropic (mainly tidal and wind driven) currents, and wave action (Ward et al. 1984; Huettel et al. 1996). Since tidal and wave energy extraction must alter these hydrodynamic properties at some scales depending on the nature of the extraction process, we can expect some kind of impact on the concentration of the SPM. If these are large enough, we may have to consider the extent to which these may impact the underwater light environment and the local or regional ecology. Whilst several coupled hydrodynamic-sediment models exist to predict SPM distributions in aquatic systems, their skill level in open coastal and offshore marine waters is acknowledged to be relatively low. This is largely because the processes are not well understood and the formulations are largely based on empirical relationships rather than fundamental physical principles. The models are also highly demanding in terms of calibration data and computational resources. Hence their utility for predicting relatively subtle effects arising from changes in flow or wave environments due to energy extraction devices seems rather low. Here, we summarise the key mathematical functions describing the processes involved in sediment suspension, and propose a lightweight one-dimensional (vertical) model which can be used to scope the effects of changes in flow and wave energy on SPM

Can a galaxy redshift survey measure dark energy clustering?

(abridged) A wide-field galaxy redshift survey allows one to probe galaxy clustering at largest spatial scales, which carries an invaluable information on horizon-scale physics complementarily to the cosmic microwave background (CMB). Assuming the planned survey consisting of z~1 and z~3 surveys with areas of 2000 and 300 square degrees, respectively, we study the prospects for probing dark energy clustering from the measured galaxy power spectrum, assuming the dynamical properties of dark energy are specified in terms of the equation of state and the effective sound speed c_e in the context of an adiabatic cold dark matter dominated model. The dark energy clustering adds a power to the galaxy power spectrum amplitude at spatial scales greater than the sound horizon, and the enhancement is sensitive to redshift evolution of the net dark energy density, i.e. the equation of state. We find that the galaxy survey, when combined with Planck, can distinguish dark energy clustering from a smooth dark energy model such as the quintessence model (c_e=1), when c_e<0.04 (0.02) in the case of the constant equation of state w_0=-0.9 (-0.95). An ultimate full-sky survey of z~1 galaxies allows the detection when c_e<0.08 (0.04) for w_0=0.9 (-0.95). We also investigate a degeneracy between the dark energy clustering and the non-relativistic neutrinos implied from the neutrino oscillation experiments, because the two effects both induce a scale-dependent modification in the galaxy power spectrum shape at largest spatial scales accessible from the galaxy survey. It is shown that a wider redshift coverage can efficiently separate the two effects by utilizing the different redshift dependences, where dark energy clustering is apparent only at low redshifts z<1.Comment: 14 pages, 7 figures; minor changes to match the published versio

GridWeaver: A Fully-Automatic System for Microarray Image Analysis Using Fast Fourier Transforms

Experiments using microarray technology generate large amounts of image data that are used in the analysis of genetic function. An important stage in the analysis is the determination of relative intensities of spots on the images generated. This paper presents GridWeaver, a program that reads in images from a microarray experiment, automatically locates subgrids and spots in the images, and then determines the spot intensities needed in the analysis of gene function. Automatic gridding is performed by running Fast Fourier Transforms on pixel intensity sums. Tests on several data sets show that the program responds well even on images that have significant noise, both random and systemic