Spatial management of the Mediterranean bottom-trawl fisheries: the case of the southern Aegean Sea

A time series of survey abundance indices for commercially important demersal fish and cephalopod species, inhabiting the narrow continental shelf of the southern Aegean Sea, is analyzed in relation to the topography of the area in order to evaluate the impact of different spatial fishery bans on the bottom-trawl fishery. With reference to the current situation, results suggested that implementation of the 1967/2006 EC Regulation, which bans bottom-trawl activities within 1.5 NM off the coast, will significantly increase (20–80%, depending on the species) the proportion of the populations that are inaccessible to the bottom-trawl fishery. It might also result in shifting of fishing activities toward deeper waters, adding fishing pressure onto slope resources inhabiting the slope. As depth determines, to a large extent, the distribution pattern of the species, it constitutes a variable of crucial importance for the spatial management of marine fisheries and should be taken into account when adopting relevant management regimes.     

Structure-revealing data fusion

Background

Analysis of data from multiple sources has the potential to enhance knowledge discovery by capturing underlying structures, which are, otherwise, difficult to extract. Fusing data from multiple sources has already proved useful in many applications in social network analysis, signal processing and bioinformatics. However, data fusion is challenging since data from multiple sources are often (i) heterogeneous (i.e., in the form of higher-order tensors and matrices), (ii) incomplete, and (iii) have both shared and unshared components. In order to address these challenges, in this paper, we introduce a novel unsupervised data fusion model based on joint factorization of matrices and higher-order tensors.

Results

While the traditional formulation of coupled matrix and tensor factorizations modeling only shared factors fails to capture the underlying structures in the presence of both shared and unshared factors, the proposed data fusion model has the potential to automatically reveal shared and unshared components through modeling constraints. Using numerical experiments, we demonstrate the effectiveness of the proposed approach in terms of identifying shared and unshared components. Furthermore, we measure a set of mixtures with known chemical composition using both LC-MS (Liquid Chromatography - Mass Spectrometry) and NMR (Nuclear Magnetic Resonance) and demonstrate that the structure-revealing data fusion model can (i) successfully capture the chemicals in the mixtures and extract the relative concentrations of the chemicals accurately, (ii) provide promising results in terms of identifying shared and unshared chemicals, and (iii) reveal the relevant patterns in LC-MS by coupling with the diffusion NMR data.

Conclusions

We have proposed a structure-revealing data fusion model that can jointly analyze heterogeneous, incomplete data sets with shared and unshared components and demonstrated its promising performance as well as potential limitations on both simulated and real data.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-239) contains supplementary material, which is available to authorized users.     

New generic proposal for the European Neogene large testudinids (Cryptodira) and the first phylogenetic hypothesis for the medium and large representatives of the European Cenozoic record

Fossil testudinids are known in Europe since the Eocene, with several taxa of medium size (from more than 0.3 m to less than 0.7 m) recognized in the Palaeogene record, most of them being poorly known. The size of several European Neogene taxa was larger (between 1 and 2 m). These large testudinids were relatively abundant and diverse, ranging from the early Miocene to the Pleistocene. However, there is a nomenclatural gap at the generic level for the Neogene forms, as their generally used assignment to the more primitive Eocene Cheirogaster cannot be sustained. This is because relatively little material has been assigned to the described species, and also because of the absence of a detailed study comparing all of the European taxa. Here, the European Cenozoic taxa are incorporated for the first time in a data matrix, so that a hypothesis on their phylogenetic relationships is justified. This study identified the large testudinids from the Neogene of Europe as belonging to a monophyletic clade, assigned to the new genus T itanochelon . The hitherto poorly understood ‘Testudo’ bolivari, proposed nearly a century ago but lacking diagnosis, is analysed in detail. It is recognized as the best‐represented large testudinid from the European record, and is identified as the type species of T itanochelon gen. nov. Its comparison with the other Neogene species allowed a detailed study of the new genus and an analysis of its phylogenetic relationships with the other European taxa. © 2014 The Linnean Society of London     

On using network RAM as a non‐volatile buffer

File systems and databases usually make several synchronous disk write accesses in order to make sure that the disk always has a consistent view of their data, so that it can be recovered in the case of a system crash. Since synchronous disk operations are slow, some systems choose to employ asynchronous disk write operations that improve performance at the cost of low reliability: in case of a system crash all data that have not yet been written to disk are lost. In this paper we describe a softwarebased NonVolatile RAM system that achieves the high performance of asynchronous write operations without sacrificing the reliability of synchronous write operations. Our system takes a set of volatile main memories residing in independent workstations and transforms it into a nonvolatile memory buffer – much like RAIDS do with magnetic disks. It then uses this nonvolatile buffer as an intermediate storage space in order to acknowledge synchronous write operations before actually writing the data to magnetic disk, but after writing the data to (intermediate) stable storage. We demonstrate the performance advantages of our system using both simulation and experimental evaluation.     

Acetic acid-catalyzed hydrothermal pretreatment of corn stover for the production of bioethanol at high-solids content

Corn stover (CS) was hydrothermally pretreated using CH₃COOH (0.3 %, v/v), and subsequently its ability to be utilized for conversion to ethanol at high-solids content was investigated. Pretreatment conditions were optimized employing a response surface methodology (RSM) with temperature and duration as independent variables. Pretreated CS underwent a liquefaction/saccharification step at a custom designed free-fall mixer at 50 °C for either 12 or 24 h using an enzyme loading of 9 mg/g dry matter (DM) at 24 % (w/w) DM. Simultaneous enzymatic saccharification and fermentation (SSF) of liquefacted corn stover resulted in high ethanol concentration (up to 36.8 g/L), with liquefaction duration having a negligible effect. The threshold of ethanol concentration of 4 % (w/w), which is required to reduce the cost of ethanol distillation, was surpassed by the addition of extra enzymes at the start up of SSF achieving this way ethanol titer of 41.5 g/L.     

Clinical evaluation of three denture cushion adhesives by complete denture wearers

doi: 10.1111/j.1741‐2358.2010.436.x Clinical evaluation of three denture cushion adhesives by complete denture wearers Objective: The aim of this study was the clinical evaluation of three denture cushion adhesives and whether the results were correlated to Kapur Index for denture‐supporting tissues. Background: Various types of denture adhesives are used among denture patients. However, information on the clinical behaviour of denture cushions is limited. Materials and methods: Thirty edentulous patients had their denture‐supporting tissues scored by Kapur Index and their old dentures replaced. They received three brands of denture cushion adhesives (Fittydent^®, Protefix^® and Seabond^®) and were instructed to use them in a sequence according to the group they were randomly assigned to. Each brand of adhesive was used for 48 h on the lower denture according to the manufacturer’s suggestions. After each brand was used, participants spent 24 h without applying any sort of adhesive. Finally, a questionnaire evaluating and comparing the performance of each brand was filled out. Results: Denture adhesives generally improved patient satisfaction and masticatory ability, especially in participants with poor Kapur Index and those who reported a poor retention of their old dentures. Conclusion: Fittydent^® was the most preferred adhesive, showing the best retention and the longest duration of its effect, but also reported as difficult to remove from the denture‐bearing area.     

GMBlock: Optimizing data movement in a block-level storage sharing system over Myrinet

We present gmblock, a block-level storage sharing system over Myrinet which uses an optimized I/O path to transfer data directly between the storage medium and the network, bypassing the host CPU and main memory bus of the storage server. It is device driver independent and retains the protection and isolation features of the OS. We evaluate the performance of a prototype gmblock server and find that: (a) the proposed techniques eliminate memory and peripheral bus contention, increasing remote I/O bandwidth significantly, in the order of 20–200% compared to an RDMA-based approach, (b) the impact of remote I/O to local computation becomes negligible, (c) the performance characteristics of RAID storage combined with limited NIC resources reduce performance. We introduce synchronized send operations to improve the degree of disk to network I/O overlapping. We deploy the OCFS2 shared-disk filesystem over gmblock and show gains for various application benchmarks, provided I/O scheduling can eliminate the disk bottleneck due to concurrent access.     

NORMA: The Network Makeup Artist — A Web Tool for Network Annotation Visualization

The Network Makeup Artist (NORMA) is a web tool for interactive network annotation visualization and topological analysis, able to handle multiple networks and annotations simultaneously. Precalculated annotations (e.g., Gene Ontology, Pathway enrichment, community detection, or clustering results) can be uploaded and visualized in a network, either as colored pie-chart nodes or as color-filled areas in a 2D/3D Venn-diagram-like style. In the case where no annotation exists, algorithms for automated community detection are offered. Users can adjust the network views using standard layout algorithms or allow NORMA to slightly modify them for visually better group separation. Once a network view is set, users can interactively select and highlight any group of interest in order to generate publication-ready figures. Briefly, with NORMA, users can encode three types of information simultaneously. These are 1) the network, 2) the communities or annotations of interest, and 3) node categories or expression values. Finally, NORMA offers basic topological analysis and direct topological comparison across any of the selected networks. NORMA service is available at http://norma.pavlopouloslab.info, whereas the code is available at https://github.com/PavlopoulosLab/NORMA.