Investigation of bounds on particle packing in pebble-bed high temperature reactors

Models and methods are presented for determining practical limits of the packing density of TRISO particles in fuel pebbles for a pebble-bed reactor (PBR). These models are devised for designing and interpreting fuel testing experiments. Two processes for particle failure are accounted for: failure of touching particles at the pressing stage in the pebble manufacturing process and failure due to inner pressure buildup during irradiation. The second process gains importance with increasing fuel temperature, which limits the particle packing density and the corresponding fuel enrichment. Suggestions for improvements to the models are presented.     

A survey on algorithms for mining frequent itemsets over data streams

The increasing prominence of data streams arising in a wide range of advanced applications such as fraud detection and trend learning has led to the study of online mining of frequent itemsets (FIs). Unlike mining static databases, mining data streams poses many new challenges. In addition to the one-scan nature, the unbounded memory requirement and the high data arrival rate of data streams, the combinatorial explosion of itemsets exacerbates the mining task. The high complexity of the FI mining problem hinders the application of the stream mining techniques. We recognize that a critical review of existing techniques is needed in order to design and develop efficient mining algorithms and data structures that are able to match the processing rate of the mining with the high arrival rate of data streams. Within a unifying set of notations and terminologies, we describe in this paper the efforts and main techniques for mining data streams and present a comprehensive survey of a number of the state-of-the-art algorithms on mining frequent itemsets over data streams. We classify the stream-mining techniques into two categories based on the window model that they adopt in order to provide insights into how and why the techniques are useful. Then, we further analyze the algorithms according to whether they are exact or approximate and, for approximate approaches, whether they are false-positive or false-negative. We also discuss various interesting issues, including the merits and limitations in existing research and substantive areas for future research.     

Applications of percolation theory to fungal spread with synergy

There is increasing interest in the use of the percolation paradigm to analyse and predict the progress of disease spreading in spatially structured populations of animals and plants. The wider utility of the approach has been limited, however, by several restrictive assumptions, foremost of which is a strict requirement for simple nearest-neighbour transmission, in which the disease history of an individual is influenced only by that of its neighbours. In a recent paper, the percolation paradigm has been generalized to incorporate synergistic interactions in host infectivity and susceptibility, and the impact of these interactions on the invasive dynamics of an epidemic has been demonstrated. In the current paper, we elicit evidence that such synergistic interactions may underlie transmission dynamics in real-world systems by first formulating a model for the spread of a ubiquitous parasitic and saprotrophic fungus through replicated populations of nutrient sites and subsequently fitting and testing the model using data from experimental microcosms. Using Bayesian computational methods for model fitting, we demonstrate that synergistic interactions are necessary to explain the dynamics observed in the replicate experiments. The broader implications of this work in identifying disease-control strategies that deflect epidemics from invasive to non-invasive regimes are discussed.     

Lignin solvated in zwitterionic Good's buffers displays antibacterial synergy against Staphylococcus aureus

The volume of industrial lignin is expected to increase with the deployment of biorefineries that convert lignocellulosic biomass to renewable chemicals and fuels. Interest in using lignin for value-added biomedical applications requires understanding of its effects on mammalian and microbial cells, which has been impaired by the toxicity of the solvents used to solubilize lignin. In this study, lignin is solvated in zwitterionic Good's buffers compatible with culture media. Up to 100 mg lignin can be solvated in 1 ml of 3-morpholinopropane-1-sulfonic acid (MOPS, pH 7.2) within 60 min at room temperature, whereby MOPS acts as a chaotropic agent. The addition of MOPS-solvated lignin to cultures of Staphylococcus aureus UAMS-1 containing a subinhibitory concentration of tunicamycin reduced growth more than 99% compared to tunicamycin alone, making lignin of interest as an antibiotic adjuvant. This effect of lignin is attributed to damage to the bacterial cell membrane.     

Structure prediction of subtilisin BPN' mutants using molecular dynamics methods

In this paper we describe the achievements and pitfalls encounteredin doing structure predictions of protein mutants using moleculardynamics simulation techniques in which properties of atomsare slowly changed as a function of time. Basically the methodconsists of a thermodynamic integration (slow growth) calculationused for free energy determination, but aimed at structure prediction;this allows for a fast determination of the mutant structure.We compared the calculated structure of the mutants Met222Ala,Met222Phe and Met222Gln of subtilisin BPN' with the respectiveX-ray structures and found good agreement between predictedand X-ray structure. The conformation of the residue subjectto the mutation is relatively easy to predict and is mainlydetermined by packing criteria. When the side chain has polargroups its exact orientation may pose problems; long-range Coulombinteractions may generate a polarization feedback involvingsystem relaxation times beyond the simulation time. Changesinduced in the environment are harder to predict using thismethod. In particular, rearrangement of the hydration structurewas difficult to predict correctly, probably because of thelong relaxation times. In all conversions made the changes observedin the environment were found to be history-dependent and inparticular the hydrogen bonding patterns provided evidence formetastable substates. In all cases the structure predicted wascompared with available kinetic data and the reduced activitycould be explained in terms of changes in the configurationof the active site.     

Prediction of the multimeric assembly of staphylococcal enterotoxin A with cell-surface protein receptors

Staphylococcal enterotoxin A (SEA) cross-links two class II major histocompatibility complex (MHC) molecules and forms a multimeric assembly with T-cell receptors (TcRs). The X-ray crystal structure of SEA has been solved, yet details describing molecular recognition and association remain unclear. We present a structural model for the interactions of SEA with cell-surface proteins. Molecular docking calculations predicting SEA association with the class II MHC molecule HLA-DR1 were performed by using a rigid-body docking method. Docked orientations were evaluated by a Poisson-Boltzmann model for the electrostatic free energy of binding and the hydrophobic effect calculated from molecular surface areas. We found that the best-scoring SEA conformers for the DR1alpha interface display a binding mode similar to that determined crystallographically for staphylococcal enterotoxin B bound to HLA-DR1. For the zinc-binding site of SEA, docking DR1beta yielded several orientations exhibiting tetrahedral-like coordination geometries. Combining the two interfaces, tetramers were modeled by docking an alphabeta TcR with trimolecular complexes DR1beta-SEA-DR1alpha and SEA-betaDR1alpha-SEA. Our results indicate that the complex DR1beta-SEA-DR1alpha provides a more favorable assembly for the engagement of TcRs, forming SEA molecular contacts that are in accord with reported mutagenesis studies. In contrast, the cooperative association of two SEA molecules on a single DR1 molecule sterically inhibits interactions with TcRs. We suggest that signal transduction stimulated by SEA through large-scale assembly is limited to four or five TcR-(DR1beta-SEA-DR1alpha) tetramers and requires the dimerization of class II MHC molecules, while TcR dimerization is unlikely.