Sympathetic inhibition of accommodation after sustained nearwork in subjects with myopia and emmetropia

PURPOSE. The purposes of the present study were to assess the effect of a sympathetic inhibitory pharmacologic agent, timolol maleate, on the magnitude of nearwork-induced transient myopia (NITM) and its decay in different refractive groups for an extended near task duration and to determine the proportion of the young adult population manifesting effective sympathetic access under naturalistic closed-loop viewing conditions. METHODS. Ten subjects with emmetropia and 10 with myopia were tested. They read binocularly for 1 hour at a distance of 35 to 40 cm. NITM was calculated as the difference in distance refractive state after task as compared with before task immediately after reading. All subjects received timolol maleate to block the sympathetic nervous system and betaxolol as a control agent in independent test sessions separated by at least 3 days. Forty minutes after drug instillation, the NITM measurement procedure was repeated. RESULTS. Initial NITM magnitude was larger in subjects with myopia than in subjects with emmetropia before and after timolol instillation. Furthermore, NITM magnitude in subjects with sympathetic access was increased after timolol instillation. In contrast, with the control agent betaxolol, there was no increase. NITM decay duration to baseline was increased after timolol instillation in the subjects with myopia only. Only 15% of the subjects (n = 3 subjects with myopia) demonstrated effective and significant access to sympathetic facility. CONCLUSIONS. Subjects with myopia demonstrated an increase in decay duration with timolol, thus suggesting impaired sympathetic inhibition of accommodation. This may be a precursor for myopia progression in some persons.

Effects of glutathione, N-acetyl-cysteine, α-lipoic acid and dihydrolipoic acid on the cytotoxicity of a 2-pyridylcarboxamidrazone antimycobacterial agent in human mononuclear leucocytes in vitro

A series of antioxidants was used to explore the cytotoxicity of one particularly toxic antimycobacterial 2-pyridylcarboxamidrazone anti-tuberculosis agent against human mononuclear leucocytes (MNL), in comparison with isoniazid (INH) to aid future compound design. INH caused a significant reduction of nearly 40% in cell recovery compared with control (P < 0.0001), although the co-incubation with either glutathione (GSH, 1 mM) or (NAC, 1 mM) showed abolition of INH toxicity. In contrast, the addition of GSH or NAC 1 h after INH failed to protect the cells from INH toxicity (P < 0.0001). The 2-pyridyl-carboxamidrazone 'Compound 1' caused a 50% reduction in cell recovery compared with control (P < 0.001), although this was abolished by the presence of either GSH or NAC. A 1 h post incubation with either NAC or GSH after Compound 1 addition failed to protect the cells from toxicity (P < 0.001). Co-administration of lipoic acid (LA) abolished Compound 1-mediated toxicity, although again, this effect did not occur after LA addition 1 h post incubation with Compound 1 (P < 0.001). However, co-administration of dihydrolipoic acid (DHLA) prevented Compound 1-mediated cell death when incubated with the compound and also after 1 h of Compound 1 alone. Pre-treatment with GSH, then removal of the antioxidant resulted in abolition of Compound 1 toxicity (vehicle control, 63.6 ± 16.7 versus Compound 1 alone 26.1 ± 13.6% versus GSH pre-treatment, 65.7 ± 7.3%). In a cell-free incubation, NMR analysis revealed that GSH does not react with Compound 1, indicating that this agent is not likely to directly deplete membrane thiols. Compound 1's MNL toxicity is more likely to be linked with changes in cell membrane conformation, which may induce consequent thiol depletion that is reversible by exogenous thiols. © 2004 Elsevier B.V. All rights reserved.

A multi-agent system using iterative bidding mechanism to enhance manufacturing agility

The global market has become increasingly dynamic, unpredictable and customer-driven. This has led to rising rates of new product introduction and turbulent demand patterns across product mixes. As a result, manufacturing enterprises were facing mounting challenges to be agile and responsive to cope with market changes, so as to achieve the competitiveness of producing and delivering products to the market timely and cost-effectively. This paper introduces a currency-based iterative agent bidding mechanism to effectively and cost-efficiently integrate the activities associated with production planning and control, so as to achieve an optimised process plan and schedule. The aim is to enhance the agility of manufacturing systems to accommodate dynamic changes in the market and production. The iterative bidding mechanism is executed based on currency-like metrics; each operation to be performed is assigned with a virtual currency value and agents bid for the operation if they make a virtual profit based on this value. These currency values are optimised iteratively and so does the bidding process based on new sets of values. This is aimed at obtaining better and better production plans, leading to near-optimality. A genetic algorithm is proposed to optimise the currency values at each iteration. In this paper, the implementation of the mechanism and the test case simulation results are also discussed. © 2012 Elsevier Ltd. All rights reserved.

Agent Based Models of Competition and Collaboration

Swarm intelligence is a popular paradigm for algorithm design. Frequently drawing inspiration from natural systems, it assigns simple rules to a set of agents with the aim that, through local interactions, they collectively solve some global problem. Current variants of a popular swarm based optimization algorithm, particle swarm optimization (PSO), are investigated with a focus on premature convergence. A novel variant, dispersive PSO, is proposed to address this problem and is shown to lead to increased robustness and performance compared to current PSO algorithms. A nature inspired decentralised multi-agent algorithm is proposed to solve a constrained problem of distributed task allocation. Agents must collect and process the mail batches, without global knowledge of their environment or communication between agents. New rules for specialisation are proposed and are shown to exhibit improved eciency and exibility compared to existing ones. These new rules are compared with a market based approach to agent control. The eciency (average number of tasks performed), the exibility (ability to react to changes in the environment), and the sensitivity to load (ability to cope with differing demands) are investigated in both static and dynamic environments. A hybrid algorithm combining both approaches, is shown to exhibit improved eciency and robustness. Evolutionary algorithms are employed, both to optimize parameters and to allow the various rules to evolve and compete. We also observe extinction and speciation. In order to interpret algorithm performance we analyse the causes of eciency loss, derive theoretical upper bounds for the eciency, as well as a complete theoretical description of a non-trivial case, and compare these with the experimental results. Motivated by this work we introduce agent "memory" (the possibility for agents to develop preferences for certain cities) and show that not only does it lead to emergent cooperation between agents, but also to a signicant increase in efficiency.

An iterative agent bidding mechanism for responsive manufacturing

In today's market, the global competition has put manufacturing businesses in great pressures to respond rapidly to dynamic variations in demand patterns across products and changing product mixes. To achieve substantial responsiveness, the manufacturing activities associated with production planning and control must be integrated dynamically, efficiently and cost-effectively. This paper presents an iterative agent bidding mechanism, which performs dynamic integration of process planning and production scheduling to generate optimised process plans and schedules in response to dynamic changes in the market and production environment. The iterative bidding procedure is carried out based on currency-like metrics in which all operations (e.g. machining processes) to be performed are assigned with virtual currency values, and resource agents bid for the operations if the costs incurred for performing them are lower than the currency values. The currency values are adjusted iteratively and resource agents re-bid for the operations based on the new set of currency values until the total production cost is minimised. A simulated annealing optimisation technique is employed to optimise the currency values iteratively. The feasibility of the proposed methodology has been validated using a test case and results obtained have proven the method outperforming non-agent-based methods.

Making motes intelligent:an agent-based approach to wireless sensor networks

In-Motes is a mobile agent middleware that generates an intelligent framework for deploying applications in Wireless Sensor Networks (WSNs). In-Motes is based on the injection of mobile agents into the network that can migrate or clone following specific rules and performing application specific tasks. By doing so, each mote is given a certain degree of perception, cognition and control, forming the basis for its intelligence. Our middleware incorporates technologies such as Linda-like tuplespaces and federated system architecture in order to obtain a high degree of collaboration and coordination for the agent society. A set of behavioral rules inspired by a community of bacterial strains is also generated as the means for robustness of the WSN. In this paper, we present In-Motes and provide a detailed evaluation of its implementation for MICA2 motes.