Massive data delivery in unstructured peer-to-peer networks with network coding

With more and more multimedia applications on the Internet, such as IPTV, bandwidth becomes a vital bottleneck for the booming of large scale Internet based multimedia applications. Network coding is recently proposed to take advantage to use network bandwidth efficiently. In this paper, we focus on massive multimedia data, e.g. IPTV programs, transportation in peer-to-peer networks with network coding. By through study of networking coding, we pointed out that the prerequisites of bandwidth saving of network coding are: 1) one information source with a number of concurrent receivers, or 2) information pieces cached at intermediate nodes. We further proof that network coding can not gain bandwidth saving at immediate connections to a receiver end; As a result, we propose a novel model for IPTV data transportation in unstructured peer-to-peer networks with network coding. Our preliminary simulations show that the proposed architecture works very well.

Clustering massive high dimensional data with dynamic feature maps

This paper presents an algorithm based on the Growing Self Organizing Map (GSOM) called the High Dimensional Growing Self Organizing Map with Randomness (HDGSOMr) that can cluster massive high dimensional data efficiently. The original GSOM algorithm is altered to accommodate for the issues related to massive high dimensional data. These modifications are presented in detail with experimental results of a massive real-world dataset.

New effective catalysts based on mesoporous nanofibrous carbon for selective oxidation of hydrogen sulfide

The systems based on granular mesoporous nanofibrous carbonaceous (NFC) materials synthesized by decomposition of hydrocarbons over nickel- containing catalysts are promising catalysts for selective oxidation of hydrogen sulfide. Sample series of nanofibrous carbon with three main types of their fiber structures and different contents of metal catalysts inherited from the catalysts for their synthesis were studied in this reaction. The correlation between NFC structure and its activity and selectivity in hydrogen sulfide oxidation was determined. The metal inherited from the initial catalysts for the synthesis of NFC influences the activity and selectivity of the resulting carbon catalysts. A particular influence is observed in the case of the catalyst withdrawn from the synthesis reactor at the stage of stationary operation of the metal catalyst (low specific carbon yields per unit weight of the catalyst). The presence of the metal phase results in an increase in the carbon catalyst activity and in a decrease in the selectivity to sulfur. NFC samples with the highest activity and selectivity are nanotubes and those with graphite planes perpendicular to the axis of the fibers. Carbon nanotubes have high selectivity, while samples obtained on copper–nickel catalysts also possess high activity. The promising NFC catalysts provide high conversion and selectivity (almost independent of the molar oxygen/hydrogen sulfide ratio) when a large excess of oxygen is contained in the reaction mixture.

Silver sulfide as a staining agent for scanning electron microscopy of nylon 6/MXD6 blends

BACKGROUND: In transmission and scanning electron microscopy imaging, the ability to obtain sufficient contrast between the components of a blend when they are both of a similar chemical structure still remains problematic. This paper investigates the domain morphology of a polymer blend containing two polyamides, nylon 6 and the semi-aromatic polyamide poly(m-xylene adipamide) (MXD6), using scanning electron microscopy in backscattered electron imaging mode. The efficiency of three staining agents, ruthenium tetroxide, phosphotungstic acid and silver sulfide, in obtaining optimum phase contrast between the two polymers is discussed.
RESULTS: The use of silver sulfide as a staining agent was found to be a fast and reliable approach which required basic sample preparation and provided excellent compositional contrast between the phases present in the nylon 6/MXD6 blends compared to the other staining agents.
CONCLUSIONS: The technique described in this paper is believed to be a novel and versatile method that has the potential to further improve the ability to study complex polymer blends where one polymer contains an aromatic ring.

Hydrogen sulfide attenuates carbon tetrachloride-induced hepatotoxicity, liver cirrhosis and portal hypertension in rats

BACKGROUND : Hydrogen sulfide (H(2)S) displays vasodilative, anti-oxidative, anti-inflammatory and cytoprotective activities. Impaired production of H(2)S contributes to the increased intrahepatic resistance in cirrhotic livers. The study aimed to investigate the roles of H(2)S in carbon tetrachloride (CCl(4))-induced hepatotoxicity, cirrhosis and portal hypertension.

METHODS AND FINDINGS : Sodium hydrosulfide (NaHS), a donor of H(2)S, and DL-propargylglycine (PAG), an irreversible inhibitor of cystathionine γ-lyase (CSE), were applied to the rats to investigate the effects of H(2)S on CCl(4)-induced acute hepatotoxicity, cirrhosis and portal hypertension by measuring serum levels of H(2)S, hepatic H(2)S producing activity and CSE expression, liver function, activity of cytochrome P450 (CYP) 2E1, oxidative and inflammatory parameters, liver fibrosis and portal pressure. CCl(4) significantly reduced serum levels of H(2)S, hepatic H(2)S production and CSE expression. NaHS attenuated CCl(4)-induced acute hepatotoxicity by supplementing exogenous H(2)S, which displayed anti-oxidative activities and inhibited the CYP2E1 activity. NaHS protected liver function, attenuated liver fibrosis, inhibited inflammation, and reduced the portal pressure, evidenced by the alterations of serum alanine aminotransferase (ALT), aspartate aminotransferase (AST), hyaluronic acid (HA), albumin, tumor necrosis factor (TNF)-α, interleukin (IL)-1β, IL-6 and soluble intercellular adhesion molecule (ICAM)-1, liver histology, hepatic hydroxyproline content and α-smooth muscle actin (SMA) expression. PAG showed opposing effects to NaHS on most of the above parameters.

CONCLUSIONS :  Exogenous H2S attenuates CCl4-induced hepatotoxicity, liver cirrhosis and portal hypertension by its multiple functions including anti-oxidation, anti-inflammation, cytoprotection and anti-fibrosis, indicating that targeting H2S may present a promising approach, particularly for its prophylactic effects, against liver cirrhosis and portal hypertension.

Oxygen dependency of hydrogen sulfide-mediated vasoconstriction in cyclostome aortas

Hydrogen sulfide (H₂S) has been proposed to mediate hypoxic vasoconstriction (HVC), however, other studies suggest the vasoconstrictory effect indirectly results from an oxidation product of H₂S. Here we examined the relationship between H₂S and O₂ in isolated hagfish and lamprey vessels that exhibit profound hypoxic vasoconstriction. In myographic studies, H₂S (Na₂S) dose-dependently constricted dorsal aortas (DA) and efferent branchial arteries (EBA) but did not affect ventral aortas or afferent branchial arteries; effects similar to those produced by hypoxia. Sensitivity of H₂S-mediated contraction in hagfish and lamprey DA was enhanced by hypoxia. HVC in hagfish DA was enhanced by the H₂S precursor cysteine and inhibited by amino-oxyacetate, an inhibitor of the H₂S-synthesizing enzyme, cystathionine β-synthase. HVC was unaffected by propargyl glycine, an inhibitor of cystathionine λ-lyase. Oxygen consumption (ṀO₂) of hagfish DA was constant between 15 and 115 mmHg P_O2 (1 mmHg=0.133 kPa), decreased when P_O2 <15 mmHg, and increased after P_O2 exceeded 115 mmHg. 10 μmol l^–1 H₂S increased and ⩾100μ mol l^–1 H₂S decreased ṀO₂. Consistent with the effects on HVC, cysteine increased and amino-oxyacetate decreased Ṁ_O2. These results show that H₂S is a monophasic vasoconstrictor of specific cyclostome vessels and because hagfish lack vascular NO, and vascular sensitivity to H₂S was enhanced at low P_O2, it is unlikely that H₂S contractions are mediated by either H₂S–NO interaction or an oxidation product of H₂S. These experiments also provide additional support for the hypothesis that the metabolism of H₂S is involved in oxygen sensing/signal transduction in vertebrate vascular smooth muscle.

Emergent effects in massive agent swarms in real-time game environments

 Computational efficiency and hence the scale of agent-based swarm simulations is bound by the nearest neighbour computation for each agent. This article proposes the use of GPU texture memory to implement lookup tables for a spatial partitioning based k-Nearest Neighbours algorithm. These improvements allow simulation of swarms of 220 agents at higher rates than the current best alternative algorithms. This approach is incorporated into an existing framework for simulating steering behaviours allowing for a complete implementation of massive agent swarm simulations, with per agent behaviour preferences, on a Graphics Processing Unit. These simulations have enabled an investigation of the emergent dynamics that occur when massive swarms interact with a choke point in their environment. Various modes of sustained dynamics with temporal and spatial coherence are identified when a critical mass of agents is simulated and some elementary properties are presented. The algorithms presented in this article enable researchers and content designers in games and movies to implement truly massive agent swarms in real time and thus provide a basis for further identification and analysis of the emergent dynamics in these swarms. This will improve not only the scale of swarms used in commercial games and movies but will also improve the reliability of swarm behaviour with respect to content design goals.

A novel parallel algorithm for frequent itemsets mining in massive small files datasets

In big data analysis, frequent itemsets mining plays a key role in mining associations, correlations and causality. Since some traditional frequent itemsets mining algorithms are unable to handle massive small files datasets effectively, such as high memory cost, high I/O overhead, and low computing performance, we propose a novel parallel frequent itemsets mining algorithm based on the FP-Growth algorithm and discuss its applications in this paper. First, we introduce a small files processing strategy for massive small files datasets to compensate defects of low read-write speed and low processing efficiency in Hadoop. Moreover, we use MapReduce to redesign the FP-Growth algorithm for implementing parallel computing, thereby improving the overall performance of frequent itemsets mining. Finally, we apply the proposed algorithm to the association analysis of the data from the national college entrance examination and admission of China. The experimental results show that the proposed algorithm is feasible and valid for a good speedup and a higher mining efficiency, and can meet the actual requirements of frequent itemsets mining for massive small files datasets. © 2014 ISSN 2185-2766.

A general method to eliminate laboratory induced recombinants during massive, parallel sequencing of cDNA library.

Massive, parallel sequencing is a potent tool for dissecting the regulation of biological processes by revealing the dynamics of the cellular RNA profile under different conditions. Similarly, massive, parallel sequencing can be used to reveal the complexity of viral quasispecies that are often found in the RNA virus infected host. However, the production of cDNA libraries for next-generation sequencing (NGS) necessitates the reverse transcription of RNA into cDNA and the amplification of the cDNA template using PCR, which may introduce artefact in the form of phantom nucleic acids species that can bias the composition and interpretation of original RNA profiles.