Net and Acoustic Examination of Bathypelagic Nekton on the Mid-Atlantic Ridge

Spatial distributions of organisms play a key role in facilitating trophic interactions, which influence pelagic ecosystem structure and function. This study combines discrete net trawl sampling with continuous acoustic measurements to investigate the distribution of bathypelagic (1000- 3000 m depth) nekton biomass along the Mid-Atlantic Ridge from Iceland to the Azores. Two, previously unknown, acoustic scattering layers (ASLs) were observed using 18 kHz echosounder data. The first extended approximately 200 m from 2000 m depth and was ubiquitous wherever bottom depth allowed. The second, found within the 1500-2000 m depth stratum, only occurred south of the Sub-Polar Front. Backscatter from the 2000 m ASL was attributed to fish from a suite of bathypelagic species observed throughout the study area, rather than any specific group. No general increase in backscatter, as a proxy for pelagic nekton biomass, was observed in close proximity to the bottom (≤ 200 m), but previously unreported localized concentrations of backscatter were observed when bottom topography was steep. Together these observations demonstrate higher complexity in the spatial structuring of bathypelagic ecosystems than has been previously reported and is likely to affect local ecosystem function

From Random Matrices to Stochastic Operators

We propose that classical random matrix models are properly viewed as finite difference schemes for stochastic differential operators. Three particular stochastic operators commonly arise, each associated with a familiar class of local eigenvalue behavior. The stochastic Airy operator displays soft edge behavior, associated with the Airy kernel. The stochastic Bessel operator displays hard edge behavior, associated with the Bessel kernel. The article concludes with suggestions for a stochastic sine operator, which would display bulk behavior, associated with the sine kernel.Comment: 41 pages, 5 figures. Submitted to Journal of Statistical Physics. Changes in this revision: recomputed Monte Carlo simulations, added reference [19], fit into margins, performed minor editin

ColNet: Embedding the Semantics of Web Tables for Column Type Prediction

Automatically annotating column types with knowledge base(KB) concepts is a critical task to gain a basic understandingof web tables. Current methods rely on either table metadatalike column name or entity correspondences of cells in theKB, and may fail to deal with growing web tables with in-complete meta information. In this paper we propose a neu-ral network based column type annotation framework namedColNetwhich is able to integrate KB reasoning and lookupwith machine learning and can automatically train Convolu-tional Neural Networks for prediction. The prediction modelnot only considers the contextual semantics within a cell us-ing word representation, but also embeds the semantics of acolumn by learning locality features from multiple cells. Themethod is evaluated with DBPedia and two different web ta-ble datasets, T2Dv2 from the general Web and Limaye fromWikipedia pages, and achieves higher performance than thestate-of-the-art approaches

Search for direct production of charginos, neutralinos and sleptons in final states with two leptons and missing transverse momentum in pp collisions at √s = 8TeV with the ATLAS detector

Searches for the electroweak production of charginos, neutralinos and sleptons in final states characterized by the presence of two leptons (electrons and muons) and missing transverse momentum are performed using 20.3 fb−1 of proton-proton collision data at s√ = 8 TeV recorded with the ATLAS experiment at the Large Hadron Collider. No significant excess beyond Standard Model expectations is observed. Limits are set on the masses of the lightest chargino, next-to-lightest neutralino and sleptons for different lightest-neutralino mass hypotheses in simplified models. Results are also interpreted in various scenarios of the phenomenological Minimal Supersymmetric Standard Model

Deep-Pelagic Fishes and the Mid-Atlantic Ridge: Interactions and Vectoring of Gelatinous Carbon to Higher Trophic Levels?

The assemblage structure and vertical distribution of deep-pelagic fishes relative to a mid-ocean ridge system is described from an acoustic and discrete-depth trawling survey conducted as part of the international Census of Marine Life field project MAR-ECO. A survey along the Mid-Atlantic Ridge (MAR), covering the full depth range (0 to \u3e3000 m) with a combination of gear types, was conducted to understand the role of the pelagic fauna in ecosystem dynamics. A total of 205 fish species were collected by midwater sampling. Depth was by far the primary assemblage composition determinant, with ridge section secondary. The dominant ichthyofaunal component was a widespread assemblage of fishes between 750-3000 m, from Iceland to the Azores. Some zonation was apparent in the northern and southern ends of this large depth stratum, with six smaller assemblages of fishes exhibiting limited distributions. Biomass per volume reached a water column maximum in the bathypelagic zone between 1500-2300 m. This stands in stark contrast to the general “open ocean” paradigm that biomass decreases exponentially from the surface downwards. As much of the summit of the MAR extends into this depth layer, a likely explanation for this midwater maximum is ridge association. Fish density within the benthic boundary layer (within 200 m of the ridge) was nearly double that of the water column and biomass was approximately 50% higher. Of the ‘ridge-associating’ species, two species known to consume gelata, Bathylagus euryops and Scopelogadus beanii, contributed over half of the fish biomass of this layer. These data suggest that a pelagic fish-gelata trophic linkage may be a key element of benthic-pelagic coupling over mid-ocean ridges, thus supporting enhanced nekton biomass over ridges in the absence of terrigenous nutrient input. Ongoing research to better understand this trophic linkage will be presented

The silicon stable isotope distribution along the GEOVIDE section (GEOTRACES GA-01) of the North Atlantic Ocean

The stable isotope composition of dissolved silicon in seawater (δ30SiDSi) was examined at 10 stations along the GEOVIDE section (GEOTRACES GA-01), spanning the North Atlantic Ocean (40–60∘ N) and Labrador Sea. Variations in δ30SiDSi below 500 m were closely tied to the distribution of water masses. Higher δ30SiDSi values are associated with intermediate and deep water masses of northern Atlantic or Arctic Ocean origin, whilst lower δ30SiDSi values are associated with DSi-rich waters sourced ultimately from the Southern Ocean. Correspondingly, the lowest δ30SiDSi values were observed in the deep and abyssal eastern North Atlantic, where dense southern-sourced waters dominate. The extent to which the spreading of water masses influences the δ30SiDSi distribution is marked clearly by Labrador Sea Water (LSW), whose high δ30SiDSi signature is visible not only within its region of formation within the Labrador and Irminger seas, but also throughout the mid-depth western and eastern North Atlantic Ocean. Both δ30SiDSi and hydrographic parameters document the circulation of LSW into the eastern North Atlantic, where it overlies southern-sourced Lower Deep Water. The GEOVIDE δ30SiDSi distribution thus provides a clear view of the direct interaction between subpolar/polar water masses of northern and southern origin, and allow examination of the extent to which these far-field signals influence the local δ30SiDSi distribution

Imperfection and radiation damage in protein crystals studied with coherent radiation

Fringes and speckles occur within diffraction spots when a crystal is illuminated with coherent radiation during X-ray diffraction. The additional information in these features provides insight into the imperfections in the crystal at the sub-micrometre scale. In addition, these features can provide more accurate intensity measurements (e.g. by model-based profile fitting), detwinning (by distinguishing the various components), phasing (by exploiting sampling of the molecular transform) and refinement (by distinguishing regions with different unit-cell parameters). In order to exploit these potential benefits, the features due to coherent diffraction have to be recorded and any change due to radiation damage properly modelled. Initial results from recording coherent diffraction at cryotemperatures from polyhedrin crystals of approximately 2 µm in size are described. These measurements allowed information about the type of crystal imperfections to be obtained at the sub-micrometre level, together with the changes due to radiation damage

A two step algorithm for learning from unspecific reinforcement

We study a simple learning model based on the Hebb rule to cope with "delayed", unspecific reinforcement. In spite of the unspecific nature of the information-feedback, convergence to asymptotically perfect generalization is observed, with a rate depending, however, in a non- universal way on learning parameters. Asymptotic convergence can be as fast as that of Hebbian learning, but may be slower. Moreover, for a certain range of parameter settings, it depends on initial conditions whether the system can reach the regime of asymptotically perfect generalization, or rather approaches a stationary state of poor generalization.Comment: 13 pages LaTeX, 4 figures, note on biologically motivated stochastic variant of the algorithm adde

Interpreting the Spatial Distribution of Bathypelagic Nekton Along the Mid-Atlantic Ridge

The spatial distribution of organisms plays a key role in facilitating biological processes, such as trophic interactions, which govern ecosystem structure and function. Attempts to understand bathypelagic (1000-4000 m depth) ecosystem dynamics have been hampered by the coarse temporal-spatial resolution and static nature of most sampling strategies. This study combines a traditional approach, based on discrete net trawls sampling small volumes, with the continuous full water column coverage provided by fisheries acoustics to investigate the distribution of biomass along the Mid-Atlantic Ridge (MAR). The limited trawl samples have been interpreted as showing a positive relationship between the presence of the MAR in the bathypelagic depth zone and biomass of bathypelagic fish species. Using 18 kHz echosounder data we explored this apparent association, and used comparisons of trawl data with the acoustic backscatter distribution to provide insights into how the distribution of biomass may influence trophic interactions in the bathypelagos. As such, this research provides a valuable case study of the potential contribution of acoustics to ecosystem studies, both within fisheries management and in a wider biological context