Response of H2 production and Hox-hydrogenase activity to external factors in the unicellular cyanobacterium Synechocystis sp. strain PCC 6803

The effects of external factors on both H₂ production and bidirectional Hox-hydrogenase activity were examined in the non-N₂-fixing cyanobacterium Synechocystis PCC 6803. Exogenous glucose and increased osmolality both enhanced H₂ production with optimal production observed at 0.4% and 20 mosmol kg⁻¹, respectively. Anaerobic condition for 24 h induced significant higher H₂ase activity with cells in BG11₀ showing highest activities. Increasing the pH resulted in an increased Hox-hydrogenase activity with an optimum at pH 7.5. The Hox-hydrogenase activity gradually increased with increasing temperature from 30 ^○C to 60 ^○C with the highest activity observed at 70 ^○C. A low concentration at 100 μM of either DTT or β-mercaptoethanol resulted in a minor stimulation of H₂ production. β-Mercaptoethanol added to nitrogen- and sulfur-deprived cells stimulated H₂ production significantly. The highest Hox-hydrogenase activity was observed in cells in BG11₀-S-deprived condition and 750 μM β-mercaptoethanol measured at a temperature of 70 °C; 14.32 μmol H₂ mg chl a⁻¹ min⁻¹.     

Secondary organic aerosol formation from aromatic precursors. 1. Mechanisms for individual hydrocarbons

Quantitative kinetic and physical phase partitioning models of secondary organic aerosol (SOA) formation resulting from the reactions of aromatic species were integrated into a mechanism for gas-phase reactions. Using the resulting model, analyses of the sensitivity of SOA formation to several parameters (e.g., VOC/NOx ratio, rate parameters) were performed. Results indicated that aerosol yield (SOA formed per amount of hydrocarbons reacted) depends on the extent of conversion of parent hydrocarbons, partitioning coefficient, initial aerosol mass concentration, and rate parameters. On the basis of the sensitivity studies, models for SOA yield were developed for 11 aromatic compounds. Comparison of the results from current SOA models to the results from this study suggests that mechanisms describing SOA formation from aromatic species must incorporate the reactions of reactive intermediates.     

Compounding of poly(dimethyl siloxane) to reduce tack in natural rubber

Tack in natural rubber latex was reduced by compounding poly(dimethyl siloxane) (PDMS) emulsion in concentrated latex. Sheet and dipped film surfaces were examined with Fourier transform infrared spectroscopy using attenuated total reflection (FTIR–ATR) and by contact angle measurements. Autohesive tack and tensile properties were also determined. For both sheet and dipped film, FTIR–ATR showed that the PDMS concentration was higher at the glass surface than at the air surface. The contact angle of ethylene glycol on the rubber decreased with increasing PDMS content. Autohesive tack for sheet and dipped film also decreased with increasing PDMS amount; however, annealing for 1 week at 70°C in air did cause tack to rise in the sheets. The rubber surface could be made nonadhesive by addition of sufficient PDMS. PDMS caused a decrease in tensile strength for the sheet, especially after annealing; however, PDMS did not cause a substantial decrease in percentage elongation for the sheets, except at relatively high PDMS contents. The tensile strength and percentage elongation for dipped film was not affected by PDMS over the much more limited PDMS concentration range studied. © 2001 John Wiley & Sons, Inc. J Appl Polym Sci 82: 519–526, 2001     

Reinforcement learning for resource allocation in LEO satellite networks.

In this paper, we develop and assess online decision-making algorithms for call admission and routing for low Earth orbit (LEO) satellite networks. It has been shown in a recent paper that, in a LEO satellite system, a semi-Markov decision process formulation of the call admission and routing problem can achieve better performance in terms of an average revenue function than existing routing methods. However, the conventional dynamic programming (DP) numerical solution becomes prohibited as the problem size increases. In this paper, two solution methods based on reinforcement learning (RL) are proposed in order to circumvent the computational burden of DP. The first method is based on an actor-critic method with temporal-difference (TD) learning. The second method is based on a critic-only method, called optimistic TD learning. The algorithms enhance performance in terms of requirements in storage, computational complexity and computational time, and in terms of an overall long-term average revenue function that penalizes blocked calls. Numerical studies are carried out, and the results obtained show that the RL framework can achieve up to 56% higher average revenue over existing routing methods used in LEO satellite networks with reasonable storage and computational requirements.     

Worker assignment in cellular manufacturing considering technical and human skills

This paper considers the problem of assigning workers to manufacturing cells in order to maximize the effectiveness of the organization. Organization effectiveness is assumed to be a function of the productivity, output quality, and training costs associated with a particular worker assignment. Traditionally, these worker assignments have been based only on the technical skills of the workers. The proposed model also includes human skills and permits the ability to change the skill levels of workers by providing them with additional training. The problem is formulated as a mixed integer programming problem. A total of 32 test problems were developed and varied with regard to the total training time, the available training time for each worker, the training costs, the productivity coefficients and the quality level coefficients. Results indicate that this model provides better worker assignments than one that only considers technical skills.     

Secondary organic aerosol formation from aromatic precursors. 2. Mechanisms for lumped aromatic hydrocarbons

Quantitative kinetic and physical phase partitioning models of secondary organic aerosol (SOA) formation resulting from the reactions of lumped aromatic species were integrated into a state of the art mechanism for gas-phase reactions (SAPRC). Aromatic and aerosol precursor species were aggregated based on their rate of reaction with OH radicals. Model parameters for the lumped model species were estimated based on the properties of individual compounds making up the lumped parameters. The model was applied to estimate the contribution of aromatic precursors to the formation of SOA in Houston, TX.