Folding a Polymer via Two-Point Interaction with an External Folding Agent: Use of H-Bonding and Charge-Transfer Interactions

A polymer containing electron-rich aromatic donors (1,5-dialkoxynaphthalene (DAN)) was coerced into a folded state by an external folding agent that contained an electron-deficient aromatic acceptor (pyromellitic diimide (PM)) unit. The donor-containing polymer was designed to carry a tertiary amine moiety in the linking segment, which served as an H-bonding site for reinforcing the interaction with the acceptor containing folding agent that also bore a carboxylic acid group. The H-bonding interaction of the carboxylic acid and the tertiary amine brings the PDI unit between two adjacent DAN units along the polymer backbone to induce charge-transfer (C-T) interactions, and this in turn causes the polymer chain to form a pleated structure. Evidence for the formation of such a pleated structure was obtained from NMR titration studies and also by monitoring the C-T band in their UV-visible spectra. By varying the length of the segment that links the PDI acceptor to the carboxylic acid group, we showed that the most effective folding agent was the one that had a single carbon spacer, as evident from the highest value of the association constant. Control experiments with propionic acid clearly demonstrated the importance of the additional C-T interactions for venerating the folded structures. Further, solution viscosity measurements in the presence of varying amounts of the folding agent revealed a gradual stiffening of the chain in the case of the PDI carrying carboxylic acid, whereas no such affect was seen in the case of simple propionic acid. These observations were supported by D FT calculations of the interactions of a dimeric model of the polymer with the various folding agents; here too the stability of the complex was seen to be highest in the case of the single carbon spacer.

Two-agent cooperative search using game models with endurance-time constraints

In this article, the problem of two Unmanned Aerial Vehicles (UAVs) cooperatively searching an unknown region is addressed. The search region is discretized into hexagonal cells and each cell is assumed to possess an uncertainty value. The UAVs have to cooperatively search these cells taking limited endurance, sensor and communication range constraints into account. Due to limited endurance, the UAVs need to return to the base station for refuelling and also need to select a base station when multiple base stations are present. This article proposes a route planning algorithm that takes endurance time constraints into account and uses game theoretical strategies to reduce the uncertainty. The route planning algorithm selects only those cells that ensure the agent will return to any one of the available bases. A set of paths are formed using these cells which the game theoretical strategies use to select a path that yields maximum uncertainty reduction. We explore non-cooperative Nash, cooperative and security strategies from game theory to enhance the search effectiveness. Monte-Carlo simulations are carried out which show the superiority of the game theoretical strategies over greedy strategy for different look ahead step length paths. Within the game theoretical strategies, non-cooperative Nash and cooperative strategy perform similarly in an ideal case, but Nash strategy performs better than the cooperative strategy when the perceived information is different. We also propose a heuristic based on partitioning of the search space into sectors to reduce computational overhead without performance degradation.

Self assessment schemes for multi-agent cooperative search

In this paper, we present self assessment schemes (SAS) for multiple agents performing a search mission on an unknown terrain. The agents are subjected to limited communication and sensor ranges. The agents communicate and coordinate with their neighbours to arrive at route decisions. The self assessment schemes proposed here have very low communication and computational overhead. The SAS also has attractive features like scalability to large number of agents and fast decision-making capability. SAS can be used with partial or complete information sharing schemes during the search mission. We validate the performance of SAS using simulation on a large search space consisting of 100 agents with different information structures and self assessment schemes. We also compare the results obtained using SAS with that of a previously proposed negotiation scheme. The simulation results show that the SAS is scalable to large number of agents and can perform as good as the negotiation schemes with reduced communication requirement (almost 20% of that required for negotiation).

Polymer–filler interactions in hydroxy-terminated polybutadiene–ammonium perchlorate system in the presence of a bonding agent

Bonding between ammonium perchlorate (AP) and hydroxy-terminated polybutadiene (HTPB), constituting a nonreinforcing filler system, has been studied in the presence of a unique bonding agent (BA)–a switter ion molecule, 2,4-dinitrophenylhydrazone derivative of 1,1′-bisacetylferrocene (DNPHD AF). Extensive conjugation and a permanent ionic character makes the DNPHD AF to bond strongly with the ionic oxidizer AP. Through its terminal OH group, HTPH bonds with the NO2 groups of DNPHD AF. Bonding sites in the molecules have been located from IR studies and from the first-order rate constant measurements of the bonding of DNPHD AF and other model BAs with HTPB and AP. The bonding ability of DNPHD AF is further evidenced from SEM micrographs.

The Biocontrol Agent Phlebiopsis gigantea: Efficacy and Impacts on the Stump Bacterial Biota and Conifer tree Defences

Phlebiopsis gigantea has been for a long time known as a strong competitor against Heterobasidion annosum and intensively applied as a biological control agent on stump surfaces of Picea abies in Fennoscandia. However, the mechanism underlying its antagonistic activity is still unknown. A primary concern is the possible impact of P. gigantea treatment on resident non-target microbial biota of conifer stumps. Additional risk factor is the potential of P. gigantea to acquire a necrotrophic habit through adaptation to living wood tissues. This study focused on the differential screening of several P. gigantea isolates from diverse geographical sources as well as the use of breeding approach to enhance the biocontrol efficacy against H. annosum infection. The results showed a significant positive correlation between growth rate in wood and high biocontrol efficacy. Furthermore, with aid of breeding approach, several progeny strains were obtained that had better growth rate and control efficacy than parental isolates. To address the issue of the potential of P. gigantea to acquire necrotrophic capability, a combination of histochemical, molecular and transcript profiling (454 sequencing) were used to investigate the interactions between these two fungi and ten year old P. sylvestris seedlings. The results revealed that both P. gigantea and H. annosum provoked strong necrotic lesions, but after prolonged incubation, P. gigantea lesions shrank and ceased to expand further. Tree seedlings pre-treated with P. gigantea further restricted H. annosum-induced necrosis and had elevated transcript levels of genes important for lignification, cell death regulation and jasmonic acid signalling. These suggest that induced localized resistance is a contributory factor for the biocontrol efficacy of P.gigantea, and it has a comparatively limited necrotrophic capability than H. annosum. Finally, to investigate the potential impact of P. gigantea on the stump bacterial biota, 16S rDNA isolated from tissue samples from stumps of P. abies after 1-, 6- and 13-year post treatment was sequenced using bar-coded 454 Titanium pyrosequencing. Proteobacteria were found to be the most abundant at the initial stages of stump decay but were selectively replaced by Acidobacteria at advanced stages of the decay. Moreover, P. gigantea treatment significantly decreased the bacterial richness at initial decay stage in the stumps. Over time, the bacterial community in the stumps gradually recovered and the negative effects of P. gigantea was attenuated.

Control of Agent Swarms using Generalized Centroidal Cyclic Pursuit Laws

One of the major tasks in swarm intelligence is to design decentralized but homogenoeus strategies to enable controlling the behaviour of swarms of agents. It has been shown in the literature that the point of convergence and motion of a swarm of autonomous mobile agents can be controlled by using cyclic pursuit laws. In cyclic pursuit, there exists a predefined cyclic connection between agents and each agent pursues the next agent in the cycle. In this paper we generalize this idea to a case where an agent pursues a point which is the weighted average of the positions of the remaining agents. This point correspond to a particular pursuit sequence. Using this concept of centroidal cyclic pursuit, the behavior of the agents is analyzed such that, by suitably selecting the agents' gain, the rendezvous point of the agents can be controlled, directed linear motion of the agents can be achieved, and the trajectories of the agents can be changed by switching between the pursuit sequences keeping some of the behaviors of the agents invariant. Simulation experiments are given to support the analytical proofs.

Multi-Agent Rendezvous Algorithm with Rectilinear Decision Domain

The aim of this paper is to develop a computationally efficient decentralized rendezvous algorithm for a group of autonomous agents. The algorithm generalizes the notion of sensor domain and decision domain of agents to enable implementation of simple computational algorithms. Specifically, the algorithm proposed in this paper uses a rectilinear decision domain (RDD) as against the circular decision domain assumed in earlier work. Because of this, the computational complexity of the algorithm reduces considerably and, when compared to the standard Ando's algorithm available in the literature, the RDD algorithm shows very significant improvement in convergence time performance. Analytical results to prove convergence and supporting simulation results are presented in the paper.

Positional Consensus of Multi-Agent Systems Using Linear Programming Based Decentralized Control with Rectilinear Decision Domain

In this paper we develop a Linear Programming (LP) based decentralized algorithm for a group of multiple autonomous agents to achieve positional consensus. Each agent is capable of exchanging information about its position and orientation with other agents within their sensing region. The method is computationally feasible and easy to implement. Analytical results are presented. The effectiveness of the approach is illustrated with simulation results.

Microwave assisted synthesis and UV-Vis spectroscopic studies of silver nanoparticles synthesized using vanillin as a reducing agent

The present investigation explores the adaptability of a microwave assisted route to obtain silver nanoparticles by the reduction of AgNO3 with vanillin, an environmentally benign material. Anionic surfactants such as AOT and SDS were used separately for encapsulating AgNPs and their role was compared. The UV-Visible absorption spectra present a broad SPR band consisting of two peaks suggesting the formation of silver nanoparticle with bimodal size distribution. The TEM image shows particles with spherical and hexagonal morphologies which confirms the results of UV-Vis studies. The anisotropy in the particle morphology can be attributed to the surface oxidation which in turn produces Ag@Ag2O core-shell nanostructures. Thus an intriguing feature of this system is that the obtained colloid is a mixture of AgNPs with and without Ag2O layers. Studies on the influence of pH on the stability of the synthesized nanoparticles revealed that the presence of excess Ag2O layers has a profound influence on it. Ag2O layers can be removed from AgNPs' surface by changing the solution pH to the acidic regime. The present study attests the enhanced ability of AOT in stabilizing the AgNPs in aqueous media. (C) 2011 Elsevier B.V. All rights reserved.

Automated Multi-Agent Search Using Centroidal Voronoi Configuration

This paper addresses the problem of automated multiagent search in an unknown environment. Autonomous agents equipped with sensors carry out a search operation in a search space, where the uncertainty, or lack of information about the environment, is known a priori as an uncertainty density distribution function. The agents are deployed in the search space to maximize single step search effectiveness. The centroidal Voronoi configuration, which achieves a locally optimal deployment, forms the basis for the proposed sequential deploy and search strategy. It is shown that with the proposed control law the agent trajectories converge in a globally asymptotic manner to the centroidal Voronoi configuration. Simulation experiments are provided to validate the strategy. Note to Practitioners-In this paper, searching an unknown region to gather information about it is modeled as a problem of using search as a means of reducing information uncertainty about the region. Moreover, multiple automated searchers or agents are used to carry out this operation optimally. This problem has many applications in search and surveillance operations using several autonomous UAVs or mobile robots. The concept of agents converging to the centroid of their Voronoi cells, weighted with the uncertainty density, is used to design a search strategy named as sequential deploy and search. Finally, the performance of the strategy is validated using simulations.

Synthesis of epoxy-terminated polymers by radical polymerization using alpha-(t-butylperoxymethyl)styrene as chain transfer agent

Epoxy-terminated polystyrene has been synthesized by radical polymerization using alpha-(t-butylperoxymethyl) styrene (TPMS) as the chain transfer agent. The chain transfer constants were found to be 0.66 and 0.80 at 60 and 70 degrees C, respectively. The presence of epoxy end groups was confirmed by functional group modification of epoxide to aldehyde by treatment with BF3.Et(2)O. Thermal stability of TPMS was followed by differential scanning calorimetry and iodimetry. Thermal decomposition of TPMS in toluene follows first order kinetics with an activation energy of 23 kcal/mol. (C) 1996 John Wiley & Sons, Inc.

Post-seizure EEG fractal dimension of first ECT predicts antidepressant response at two weeks

Background: Duration of seizure by itself is an insufficient criterion for a therapeutically adequate seizure in ECT. Therefore, measures of seizure EEG other than its duration need to be explored as indices of seizure adequacy and predictors of treatment response. We measured the EEG seizure using a geometrical method-fractal dimension (FD) and examined if this measure predicted remission. Methods: Data from an efficacy study on melancholic depressives (n = 40) is used for the present exploration. They received thrice or once weekly ECTs, each schedule at two energy levels - high or low energy level. FD was computed for early-, mid- and post-seizure phases of the ictal EEG. Average of the two channels was used for analysis. Results: Two-thirds of the patients (n = 25) were remitted at the end of 2 weeks. As expected, a significantly higher proportion of patients receiving thrice weekly ECT remitted than in patients receiving once weekly ECT. Smaller post-seizure FD at first ECT is the only variable which predicted remission status after six ECTs. within the once weekly ECT group too, smaller post-seizure FD was associated with remission status. Conclusions: Post-seizure FD is proposed as a novel measure of seizure adequacy and predictor of treatment response. Clinical implications: Seizure measures at first ECT may guide selection of ECT schedule to optimize ECT. Limitations: The study examined short term antidepressant effects only. The results may not be generalized to medication-resistant depressives. (C) 1999 Elsevier Science B.V. All rights reserved.

Propargyloxycarbonyl (Poc) amino acid chlorides as efficient coupling reagents for the synthesis of 100% diastereopure peptides and resin bound tetrathiomolybdate as an effective deblocking agent for the Poc group

Synthesis of short peptides using propargyloxycarbonyl amino acid chlorides as effective coupling reagents and polymer supported tetrathiomolybdate as an efficient deblocking agent are reported.

Multi-agent search using?sensors with heterogeneous capabilities

In this thesis we address the problem of multi-agent search. We formulate two deploy and search strategies based on optimal deployment of agents in search space so as to maximize the search effectiveness in a single step. We show that a variation of centroidal Voronoi configuration is the optimal deployment. When the agents have sensors with different capabilities, the problem will be heterogeneous in nature. We introduce a new concept namely, generalized Voronoi partition in order to formulate and solve the heterogeneous multi-agent search problem. We address a few theoretical issues such as optimality of deployment, convergence and spatial distributedness of the control law and the search strategies. Simulation experiments are carried out to compare performances of the proposed strategies with a few simple search strategies.

Multi-agent Search using Voronoi partitions

This paper addresses the problem of multiagent search in an unknown environment. The agents are autonomous in nature and are equipped with necessary sensors to carry out the search operation. The uncertainty, or lack of information about the search area is known a priori as a probability density function. The agents are deployed in an optimal way so as to maximize the one step uncertainty reduction. The agents continue to deploy themselves and reduce uncertainty till the uncertainty density is reduced over the search space below a minimum acceptable level. It has been shown, using LaSalle’s invariance principle, that a distributed control law which moves each of the agents towards the centroid of its Voronoi partition, modified by the sensor range leads to single step optimal deployment. This principle is now used to devise search trajectories for the agents. The simulations were carried out in 2D space with saturation on speeds of the agents. The results show that the control strategy per step indeed moves the agents to the respective centroid and the algorithm reduces the uncertainty distribution to the required level within a few steps.