Maintenance of Strongly Connected Component in Shared-memory Graph

In this paper, we present an on-line fully dynamic algorithm for maintaining strongly connected component of a directed graph in a shared memory architecture. The edges and vertices are added or deleted concurrently by fixed number of threads. To the best of our knowledge, this is the first work to propose using linearizable concurrent directed graph and is build using both ordered and unordered list-based set. We provide an empirical comparison against sequential and coarse-grained. The results show our algorithm's throughput is increased between 3 to 6x depending on different workload distributions and applications. We believe that there are huge applications in the on-line graph. Finally, we show how the algorithm can be extended to community detection in on-line graph.Comment: 29 pages, 4 figures, Accepted in the Conference NETYS-201

Mixed adsorption and surface tension prediction of nonideal ternary surfactant systems

To deal with the mixed adsorption of nonideal ternary surfactant systems, the regular solution approximation for nonideal binary surfactant systems is extended and a pseudo-binary system treatment is also proposed. With both treatments, the compositions of the mixed monolayer and the solution concentrations required to produce given surface tensions can be predicted based only on the gamma-LogC curves of individual surfactants and the pair interaction parameters. Conversely, the surface tensions of solutions with different bulk compositions can be predicted by the surface tension equations for mixed surfactant systems. Two ternary systems: SDS/Hyamine 1622/AEO7, composed of homogeneous surfactants, and AES/DPCl/AEO9, composed of commercial surfactants, in the presence of excess NaCl, are examined for the applicability of the two treatments. The results show that, in general, the pseudo-binary system treatment gives better prediction than the extended regular solution approximation, and the applicability of the latter to typical anionic/cationic/nonionic nonideal ternary surfactant systems seems to depend on the combined interaction parameter, $${\mathop {(\beta }\nolimits_{an}^s } + {\mathop \beta \nolimits_{cn}^s })/2 - {\mathop \beta \nolimits_{ac}^s }/4$$ : the more it deviates from zero, the larger the prediction difference. If $${\mathop {(\beta }\nolimits_{an}^s } + {\mathop \beta \nolimits_{cn}^s })/2 - {\mathop \beta \nolimits_{ac}^s }/4$$ rarr0, good agreements between predicted and experimental results can be obtained and both treatments, though differently derived, are interrelated and tend to be equivalent

Expression of human α1-proteinase inhibitor in Aspergillus niger

This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

Theoretically Efficient Parallel Graph Algorithms Can Be Fast and Scalable

There has been significant recent interest in parallel graph processing due to the need to quickly analyze the large graphs available today. Many graph codes have been designed for distributed memory or external memory. However, today even the largest publicly-available real-world graph (the Hyperlink Web graph with over 3.5 billion vertices and 128 billion edges) can fit in the memory of a single commodity multicore server. Nevertheless, most experimental work in the literature report results on much smaller graphs, and the ones for the Hyperlink graph use distributed or external memory. Therefore, it is natural to ask whether we can efficiently solve a broad class of graph problems on this graph in memory. This paper shows that theoretically-efficient parallel graph algorithms can scale to the largest publicly-available graphs using a single machine with a terabyte of RAM, processing them in minutes. We give implementations of theoretically-efficient parallel algorithms for 20 important graph problems. We also present the optimizations and techniques that we used in our implementations, which were crucial in enabling us to process these large graphs quickly. We show that the running times of our implementations outperform existing state-of-the-art implementations on the largest real-world graphs. For many of the problems that we consider, this is the first time they have been solved on graphs at this scale. We have made the implementations developed in this work publicly-available as the Graph-Based Benchmark Suite (GBBS).Comment: This is the full version of the paper appearing in the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 201

Low metabolic activity of biofilm formed by Enterococcus faecalis isolated from healthy humans and wild mallards (Anas platyrhynchos)

It is widely known that Enterococcus faecalis virulence is related to its biofilm formation. Although Enterococci are common commensal organisms of the gastrointestinal tract, the difference between commensal and pathogen strains remain unclear. In this study, we compare the biochemical profile of the biofilms formed by two groups of medical and two groups of commensal strains. The medical strains were isolated as pathogens from infections of urinary tract and other infections (wounds, pus and bedsores), and the commensal strains were taken from faeces of healthy volunteers and faeces of wild mallards (Anas platyrhynchos) living in an urban environment. The properties of biofilms formed by medical and commensal strains differed significantly. Commensal strains showed lower metabolic activity and glucose uptake and higher biofilm biomass than the medical ones. Consistent with glucose uptake experiments, we found that the glucose dehydrogenase gene was more expressed in medical strains. These results indicate that higher metabolic activity and lower protein concentration of E. faecalis cells within biofilms are formed during infections.This work was supported by the Medical University of Gdansk research grant (GUMed W-65) and was financed partly by University of Gdansk research grant (BW 1440-5-0099-7). We are grateful to Katarzyna Zolkos for her help in catching mallards and Magdalena Remisiewicz for correcting the English. Catarina Seabra helped in preparing assays

The genome sequence of E. coli W (ATCC 9637): comparative genome analysis and an improved genome-scale reconstruction of E. coli

Background: Escherichia coli is a model prokaryote, an important pathogen, and a key organism for industrial biotechnology. E. coli W (ATCC 9637), one of four strains designated as safe for laboratory purposes, has not been sequenced. E. coli W is a fast-growing strain and is the only safe strain that can utilize sucrose as a carbon source. Lifecycle analysis has demonstrated that sucrose from sugarcane is a preferred carbon source for industrial bioprocesses