Distributed k-core view materialization and maintenance for large dynamic graphs

Cataloged from PDF version of article.In graph theory, k-core is a key metric used to identify subgraphs of high cohesion, also known as the ‘dense’ regions of a graph. As the real world graphs such as social network graphs grow in size, the contents get richer and the topologies change dynamically, we are challenged not only to materialize k-core subgraphs for one time but also to maintain them in order to keep up with continuous updates. Adding to the challenge is that real world data sets are outgrowing the capacity of a single server and its main memory. These challenges inspired us to propose a new set of distributed algorithms for k-core view construction and maintenance on a horizontally scaling storage and computing platform. Our algorithms execute against the partitioned graph data in parallel and take advantage of k-core properties to aggressively prune unnecessary computation. Experimental evaluation results demonstrated orders of magnitude speedup and advantages of maintaining k-core incrementally and in batch windows over complete reconstruction. Our algorithms thus enable practitioners to create and maintain many k-core views on different topics in rich social network content simultaneously

Enhanced catalytic performance of MnxOy-Na2WO4/SiO2 for the oxidative coupling of methane using an ordered mesoporous silica support

The oxidative coupling of methane is a highly promising reaction for its direct conversion. Silica supported MnxOy–Na2WO4 is a suitable catalyst for this reaction. In this study, a variety of different SiO2 materials have been tested as supports. Surprisingly, the application of ordered mesoporous silicas, here exemplarily shown for SBA-15 as support materials, greatly enhances the catalytic performance. The CH4 conversion increased two fold and also the C2 selectivity is strongly increased

A panel of oxidative stress assays does not provide supplementary diagnostic information in Behcet's disease patients

Published onlineJournal ArticleBACKGROUND: Recent findings suggest a role of oxidative stress in the pathogenesis of Behcet's disease (BD), but the utility of oxidative stress-associated assays in offering diagnostic information or in the monitoring of disease activity is largely unassessed. OBJECTIVE AND METHODS: We aimed to measure oxidative and inflammatory markers, along with the markers of reactive nitrogen species, S-nitrosothiols and 3-nitrotyrosine, in BD patients (n = 100) and healthy volunteers (n = 50). These markers were evaluated in regard to their role in the pathogenesis of BD as well as their relation to clinical presentation, disease activity and duration. RESULTS: Median values for erythrocyte sedimentation rate (ESR), C-reactive protein, leukocyte count, and IL-18 levels, as well as myeloperoxidase (MPO) activity, were statistically higher in the patient group compared to controls. Some inflammation markers (ESR, neutrophil and leukocyte counts) were statistically higher (p 0.05 in all statistical comparisons), nor was there any difference in median levels of these oxidative stress markers in active disease versus disease remission. S-nitrosothiols and 3-nitrotyrosine were undetectable in BD plasma. CONCLUSIONS: The application of oxidative stress-associated measures to BD blood samples offered no supplemental diagnostic or disease activity information to that provided by standard laboratory measures of inflammation. S-nitrosothiols and 3-nitrotyrosine appeared not to be markers for active BD; thus the search for biochemical markers that will indicate the active period should be continued with larger studies

Multi-resolution social network community identification and maintenance on big data platform

Community identification in social networks is of great interest and with dynamic changes to its graph representation and content, the incremental maintenance of community poses significant challenges in computation. Moreover, the intensity of community engagement can be distinguished at multiple levels, resulting in a multi-resolution community representation that has to be maintained over time. In this paper, we first formalize this problem using the k-core metric projected at multiple k values, so that multiple community resolutions are represented with multiple k-core graphs. We then present distributed algorithms to construct and maintain a multi-k-core graph, implemented on the scalable big-data platform Apache HBase. Our experimental evaluation results demonstrate orders of magnitude speedup by maintaining multi-k-core incrementally over complete reconstruction. Our algorithms thus enable practitioners to create and maintain communities at multiple resolutions on different topics in rich social network content simultaneously. © 2013 IEEE

Efficient community identification and maintenance at multiple resolutions on distributed datastores

The topic of network community identification at multiple resolutions is of great interest in practice to learn high cohesive subnetworks about different subjects in a network. For instance, one might examine the interconnections among web pages, blogs and social content to identify pockets of influencers on subjects like 'Big Data', 'smart phone' or 'global warming'. With dynamic changes to its graph representation and content, the incremental maintenance of a community poses significant challenges in computation. Moreover, the intensity of community engagement can be distinguished at multiple levels, resulting in a multi-resolution community representation that has to be maintained over time. In this paper, we first formalize this problem using the k-core metric projected at multiple k-values, so that multiple community resolutions are represented with multiple k-core graphs. Recognizing that large graphs and their even larger attributed content cannot be stored and managed by a single server, we then propose distributed algorithms to construct and maintain a multi-k-core graph, implemented on the scalable Big Data platform Apache HBase. Our experimental evaluation results demonstrate orders of magnitude speedup by maintaining multi-k-core incrementally over complete reconstruction. Our algorithms thus enable practitioners to create and maintain communities at multiple resolutions on multiple subjects in rich network content simultaneously. © 2015 Elsevier B.V. All rights reserved

Graph aware caching policy for distributed graph stores

Graph stores are becoming increasingly popular among NOSQL applications seeking flexibility and heterogeneity in managing linked data. Conceptually and in practice, applications ranging from social networks, knowledge representations to Internet of things benefit from graph data stores built on a combination of relational and non-relational technologies aimed at desired performance characteristics. The most common data access pattern in querying graph stores is to traverse from a node to its neighboring nodes. This paper studies the impact of such traversal pattern to common data caching policies in a partitioned data environment where a big graph is distributed across servers in a cluster. We propose and evaluate a new graph aware caching policy designed to keep and evict nodes, edges and their metadata optimized for query traversal pattern. The algorithm distinguishes the topology of the graph as well as the latency of access to the graph nodes and neighbors. We implemented graph aware caching on a distributed data store Apache HBase in the Hadoop family. Performance evaluations showed up to 15x speedup on the benchmark datasets preferring our new graph aware policy over non-aware policies. We also show how to improve the performance of existing caching algorithms for distributed graphs by exploiting the topology information. © 2015 IEEE

Silica material variation for the Mn_xO_y-Na₂WO₄/SiO₂

The oxidative coupling of methane (OCM) is one of the best methods for the direct conversion of methane.Among the known OCM catalysts, MnxOy-Na2WO4/SiO2 is a promising candidate for an industrial appli-cation, showing a high methane conversion and C2 selectivity, with a good stability during long-termcatalytic activity tests. In the present study, some results have been already published and discussedbriefly in our previous short communication. However, we herein investigated comprehensively theinfluence of various silica support materials on the performance of the MnxOy-Na2WO4/SiO2 systemin the OCM by means of ex situ and in situ XRD, BET, SEM and TEM characterization methods andshowed new results to reveal possible support effects on the catalyst. The catalytic performance of most MnxOy-Na2WO4/SiO2 catalysts supported by different silica support materials did not differ substan-tially. However, the performance of the SBA-15 supported catalyst was outstanding and the methaneconversion was nearly twofold higher in comparison to the other silica supported catalysts at similar C2 selectivity as shown before in the communication. The reason of this substantial increase in performancecould be the ordered mesoporous structure of the SBA-15 support material, homogeneous dispersion ofactive components and high number of active sites responsible for the OCM

Computational Identification and Analysis of the Key Biosorbent Characteristics for the Biosorption Process of Reactive Black 5 onto Fungal Biomass

The performances of nine biosorbents derived from dead fungal biomass were investigated for their ability to remove Reactive Black 5 from aqueous solution. The biosorption data for removal of Reactive Black 5 were readily modeled using the Langmuir adsorption isotherm. Kinetic analysis based on both pseudo-second-order and Weber-Morris models indicated intraparticle diffusion was the rate limiting step for biosorption of Reactive Black 5 on to the biosorbents. Sorption capacities of the biosorbents were not correlated with the initial biosorption rates. Sensitivity analysis of the factors affecting biosorption examined by an artificial neural network model showed that pH was the most important parameter, explaining 22%, followed by nitrogen content of biosorbents (16%), initial dye concentration (15%) and carbon content of biosorbents (10%). The biosorption capacities were not proportional to surface areas of the sorbents, but were instead influenced by their chemical element composition. The main functional groups contributing to dye sorption were amine, carboxylic, and alcohol moieties. The data further suggest that differences in carbon and nitrogen contents of biosorbents may be used as a selection index for identifying effective biosorbents from dead fungal biomass

Water recovery with combined membrane system in textile industry, treatment and management of concentrates by hybrid advanced oxidation/membrane filtration

In this study, in addition to textile wastewater treatment by UF/NFtight/TO membrane combination of which efficiency is known, management has been performed for membrane concentrates generated with advanced oxidation combined process (Fenton and photo-Fenton (UVA-365-UVC-254))/submerged UF system of membrane concentrates generated within 75-80% water recovery ratio by oxidizing them in optimum operating conditions which were determined before. Ultimately in the studies, the conclusion has been reached that concentrate flows, generated as a result of the treatment with UF/NFtight/TO membrane configuration, were the highest performance innovative process by decreasing the sequential operated photo-Fenton (UVC-254)/UH050 hybrid process in ratios of 9.88 H2O2/TOK and 7.27 H2O2/Fe2+, in the filtration flux of 44 L/m(2). h, COD value to 167 mg/L with 86% COD removal, and TOK value to 104 mg/L with 74.2% TOC removal, after the oxidation with Fenton, photo-Fenton (UVA-365) and (UVC-254)/submerged UF system processes. When hazardous characteristics, removal/recovery methods and reuse alternatives of the concentrate remained after the oxidation of membrane concentrates generated were evaluated, it has been seen that all other concentrates of textile industry wastewater, except the concentrate generated by the treatment with photo-Fenton (UVA-365), had characteristics of hazardousness When removal/recovery methods were evaluated in detail, the conclusion has been reached that these concentrates could be removed with alternative options such as regular storage, burning and canalizing to central wastewater treatment system as long as necessary arrangements (moisture content, dehydration, suitable flow and/or mixture ratios) are made

Massive hemoptysis and deep venous thrombosis presenting in a woman with Hughes-Stovin syndrome: a case report

<p>Abstract</p> <p>Introduction</p> <p>Hughes-Stovin syndrome is a very rare disease with fewer than 30 cases reported in the literature. The disease is thought to be a variant of Behcet's disease and is defined by the presence of pulmonary artery aneurysm in association with peripheral venous thrombosis.</p> <p>Case presentation</p> <p>A previously healthy 23-year-old Saudi woman presented with massive hemoptysis a day prior to her admission to our hospital. She had a six-month history of recurrent fever, cough, dyspnea, and recurrent oral ulceration. Contrast-enhanced computed tomography scan of her chest and pulmonary angiogram demonstrated a single right-lower lobe pulmonary artery aneurysm. She underwent thoracotomy and right lower lobe resection. Her postoperative course was complicated by deep vein thrombosis. She also developed headache and papilledema, while a magnetic resonance imaging of her brain suggested vasculitis. Based on these clinical presentations, she was diagnosed and treated with Hughes-Stovin syndrome.</p> <p>Conclusion</p> <p>The majority of cases of Hughes-Stovin syndrome are reported among men, with only two cases occurring in women. A case of Hughes-Stovin syndrome occurring in a woman is presented in this report. She was treated successfully with multimodality treatment that includes surgery, steroids and cytotoxic agents.</p