941 resultados para POLYMERIC REINFORCEMENT


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On introduit une nouvelle classe de schémas de renforcement des automates d'apprentissage utilisant les estimations des caractéristiques aléatoires de l'environnement. On montre que les algorithmes convergent en probabilité vers le choix optimal des actions. On présente les résultats de simulation et on suggère des applications à un environnement à plusieurs apprentissages

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An easy access to a library of simple organic salts derived from tert-butoxycarbonyl (Boc)-protected L-amino acids and two secondary amines (dicyclohexyl- and dibenzyl amine) are synthesized following a supramolecular synthon rationale to generate a new series of low molecular weight gelators (LMWGs). Out of the 12 salts that we prepared, the nitrobenzene gel of dicyclohexylammonium Boc-glycinate (GLY.1) displayed remarkable load-bearing, moldable and self-healing properties. These remarkable properties displayed by GLY.1 and the inability to display such properties by its dibenzylammonium counterpart (GLY.2) were explained using microscopic and rheological data. Single crystal structures of eight salts displayed the presence of a 1D hydrogen-bonded network (HBN) that is believed to be important in gelation. Powder X-ray diffraction in combination with the single crystal X-ray structure of GLY.1 clearly established the presence of a 1D hydrogen-bonded network in the xerogel of the nitrobenzene gel of GLY.1. The fact that such remarkable properties arising from an easily accessible (salt formation) small molecule are due to supramolecular (non-covalent) interactions is quite intriguing and such easily synthesizable materials may be useful in stress-bearing and other applications.

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A methodology using sensitivity analysis is proposed to measure the effective permeability which includes the interaction of the resin and the reinforcement. Initially, mold-filling experiments were performed at isothermal conditions on the test specimen and the positions of the flow front were tracked with time using a flow visualization method. Following this, mold-filling experiments were simulated using a commercial software to obtain the positions of the flow front with time at the process conditions used for experiments. Several iterations were performed using different trial values of the permeability until the experimentally tracked and simulated positions of the flow front with time were matched. Finally, the value of the permeability thus obtained was validated by comparing the positions obtained by performing the experiments at different process conditions with the positions obtained by simulating the experiments. In this study, woven roving and chopped strand mats of E-class glass fiber and unsaturated polyester resin were used for the experiments. From the results, it was found that the measured permeabilities were consistent with varying process conditions. POLYM. COMPOS., 2012. (c) 2012 Society of Plastics Engineers

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We consider the problem of finding the best features for value function approximation in reinforcement learning and develop an online algorithm to optimize the mean square Bellman error objective. For any given feature value, our algorithm performs gradient search in the parameter space via a residual gradient scheme and, on a slower timescale, also performs gradient search in the Grassman manifold of features. We present a proof of convergence of our algorithm. We show empirical results using our algorithm as well as a similar algorithm that uses temporal difference learning in place of the residual gradient scheme for the faster timescale updates.

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In the present investigation an attempt has been made to develop a new co-polymeric material for controlled release tablet formulations. The acrylamide grafting was successfully performed on the backbone of sago starch. The modified starch was tested for acute toxicity and drug-excipient compatibility study. The grafted material was used in making of controlled release tablets of lamivudine. The formulations were evaluated for physical characteristics such as hardness, friability, %drug content and weight variations. The in vitro release study showed that the optimized formulation exhibited highest correlation (R) value in case of Higuchi model and the release mechanism of the optimized formulation predominantly exhibited combination of diffusion and erosion process. There was a significant difference in the pharmacokinetic parameters (T-max, C-max, AUC, V-d, T-1/2 and MDT) of the optimized formulation as compared to the marketed conventional tablet Lamivir (R) was observed. The pharmacokinetics parameters were showed controlled pattern and better bioavailability. The optimized formulation exhibited good stability and release profile at the accelerated stability conditions. (c) 2013 Elsevier B.V. All rights reserved.

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We report the first synthesis of a photodegradable hyperbranched polyacetal, wherein every repeat unit carries a photo-labile 2-nitro-benzyloxy moiety. The pristine HBP serves as a positive photoresist to create micron-size patterns; furthermore, by changing the terminal groups to dipropargyl acetal, clickable photo-patterned substrates can be generated.

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In the present investigation, the corrosive behaviour of Al 6061-TiN particulate composites prepared by liquid metallurgy has been studied in chloride medium using electroanalytical techniques such as Tafel, cyclic polarization and electrochemical impedance spectroscopy (EIS). Surface morphology of the sample electrodes was examined using scanning electron micrography and energy dispersive X-ray methods. X-ray diffraction technique was used to confirm inclusion of TiN particulates in the matrix alloy and identify the alloying elements and intermetallic compounds in the Al 6061 composites. Polarization studies indicate an increase in the corrosion resistance in composites compared to the matrix alloy. EIS study reveals that the polarization resistance (R (p)) increases with increase in TiN content in composites, thus confirming improved corrosion resistance in composites. The observed decrease in corrosion rate in the case of composites is due to decoupling between TiN particles and Al 6061 alloy. It is understood that after the initiation of corrosion, interfacial corrosion products may have decoupled the conducting ceramic TiN from Al 6061 matrix alloy thus eliminating the galvanic effect between them.

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The study of models for ``metal-enzyme-substrate'' interaction has been a proactive area of research owing to its biological and pharmacological importance. In this regard the ternary copper uracil complex with 1,10-phenanthroline represents metal-enzyme-substrate system for DNA binding enzymes. The synthesis of the complex, followed by slow evaporation of the reaction mixture forms two concomitant solvatomorph crystals viz., {Cu(phen)(mu-ura)(H2O)](n)center dot H2O (1a)} and {Cu(phen)(mu-ura)(H2O)](n)center dot CH3OH (1b)}. Both complexes are structurally characterized, while elemental analysis, IR and EPR spectra were recorded for 1b (major product). In both complexes, uracil coordinates uniquely via N1 and N3 nitrogen atom acting as a bidentate bridging ligand forming a 1-D polymer. The two solvatomorphs were quantitatively analyzed for the differences with the aid of Hirshfeld surface analysis. (C) 2014 Elsevier B.V. All rights reserved.

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The aim in this paper is to allocate the `sleep time' of the individual sensors in an intrusion detection application so that the energy consumption from the sensors is reduced, while keeping the tracking error to a minimum. We propose two novel reinforcement learning (RL) based algorithms that attempt to minimize a certain long-run average cost objective. Both our algorithms incorporate feature-based representations to handle the curse of dimensionality associated with the underlying partially-observable Markov decision process (POMDP). Further, the feature selection scheme used in our algorithms intelligently manages the energy cost and tracking cost factors, which in turn assists the search for the optimal sleeping policy. We also extend these algorithms to a setting where the intruder's mobility model is not known by incorporating a stochastic iterative scheme for estimating the mobility model. The simulation results on a synthetic 2-d network setting are encouraging.

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Graphene oxide (GO), prepared by chemical oxidation of graphite, serves as a building block for developing polymeric nanocomposites. However, their application in electrical conductivity is limited by the fact that the oxygen sites on GO trap electrons and impede charge transport. Conducting nanocomposites can be developed by reducing GO. Various strategies have been adopted to either reduce GO ex situ, before the composite preparation, or in situ during the development of the nanocomposites. The current state of research on in situ reduction of GO during the preparation of conducting polymeric nanocomposites is discussed in this review. The mechanism and the efficiency of reduction is discussed with respect to various strategies employed during the preparation of the nanocomposite, the type of polymer used, and the processing conditions employed, etc. Its overall effect on the electrical conductivity of the nanocomposites is also discussed and the future outlook in this area is presented.

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In this work, porous membranes were designed by selectively etching the PEO phase, by water, from a melt-mixed PE/PEO blend. The pure water flux and the resistance across the membrane were systematically evaluated by employing an indigenously developed cross flow membrane setup. Both the phase morphology and the cross sectional morphology of the membranes was assessed by scanning electron microscopy and an attempt was made to correlate the observed morphology with the membrane performance. In order to design antibacterial membranes for water purification, partially reduced graphene oxide (rGO), silver nanoparticles (Ag) and silver nanoparticles decorated with rGO (rGO-Ag) were synthesized and incorporated directly into the blends during melt mixing. The loss of viability of bacterial cells was determined by the colony counting method using E. coli as a model bacterium. SEM images display that the direct contact with the rGO-Ag nanoparticles disrupts the cell membrane. In addition, the rGO-Ag nanoparticles exhibited a synergistic effect with respect to bacterial cell viability in comparison to both rGO and Ag nanoparticles. The possible mechanism associated with the antibacterial activity in the membranes was discussed. This study opens new avenues in designing antibacterial membranes for water purification.

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Nanoparticles of different shapes can induce peculiar morphologies in binary polymer blends depending on their position. It is envisaged that the increased yield stress of the filled phase slows down the relaxation resulting in arresting the peculiar morphologies which otherwise is thermodynamically unfavourable due to the increased interfacial area. This essentially means that the highly irregular structures can be preserved even without altering the interfacial tension between the phases! On the other hand, in the case of interfacially adsorbed particles, the resulting solid-like interface can also preserve the irregular structures. These phenomenal transitions in filled blends are very different from the classical copolymer compatibilized polymer blends. Moreover, these irregular structures can further pave way in designing conducting polymer blends involving conducting nanoparticles and revisiting our understanding of the concept of double percolation!

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Optimal control of traffic lights at junctions or traffic signal control (TSC) is essential for reducing the average delay experienced by the road users amidst the rapid increase in the usage of vehicles. In this paper, we formulate the TSC problem as a discounted cost Markov decision process (MDP) and apply multi-agent reinforcement learning (MARL) algorithms to obtain dynamic TSC policies. We model each traffic signal junction as an independent agent. An agent decides the signal duration of its phases in a round-robin (RR) manner using multi-agent Q-learning with either is an element of-greedy or UCB 3] based exploration strategies. It updates its Q-factors based on the cost feedback signal received from its neighbouring agents. This feedback signal can be easily constructed and is shown to be effective in minimizing the average delay of the vehicles in the network. We show through simulations over VISSIM that our algorithms perform significantly better than both the standard fixed signal timing (FST) algorithm and the saturation balancing (SAT) algorithm 15] over two real road networks.

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The work reports the preparation of fly ash cenospheres bearing polymer composites, using various polymer matrix materials namely, low density polyethylene, high density polyethylene, polystyrene and polymethylmethacrylate followed by evaluation of properties. The composites are synthesized by including about 18% by weight fly ash cenospheres, into various polymer matrices using brabender facility in the temperature range 120-160 degrees C and at a mixing pressure of 50 MPa. Subsequently, they are cast into sheets through compression moulding. The test samples, made from the sheets, are characterized for physical as well as mechanical properties such as density, hardness, compression strength, impact response, wear and friction. The investigation reveals that the addition of fly ash cenospheres to various polymer matrices results in reduction of density. Further, improvements in the slide wear resistance and decrease in the co-efficient of friction values are noticed. As for interpreting the slide wear data, recourse to examination under scanning electron microscope is made in this paper. As regards the mechanical properties, hardness increases while the compression strength and impact energy decreases with inclusion of cenospheres in all the four types of samples investigated.

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With increasing energy demand, it necessitates to generate and transmit the electrical power with minimal losses. High voltage power transmission is the most economical way of transmitting bulk power over long distances. Transmission insulator is one of the main components used as a mechanical support and to electrically isolate the conductor from the tower. Corona from the hardware and conductors can significantly affect the performance of the polymeric insulators. In the present investigation a methodology is presented to evaluate the corona performance of the polymeric shed material under different environment conditions for both ac and dc excitation. The results of the comprehensive analysis on various polymeric samples and the power released from the corona electrode for both the ac and dc excitation are presented. Some interesting results obtained from the chemical analysis confirmed the presence of nitric acid species on the treated sample which in long term will affect the strength of the insulator, also the morphological changes were found to be varying for different experimental conditions. (C) 2015 The Authors. Published by Elsevier Ltd.