988 resultados para Inverse modeling
Resumo:
Two oxazolidine-2-thiones, thio-analogs of linezolid, were synthesized and their antibacterial properties evaluated. Unlike oxazolidinones, the thio-analogs did not inhibit the growth of Gram positive bacteria. A molecular modeling study has been carried out to aid understanding of this unexpected finding.
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Platelet endothelial cell adhesion molecule 1 (PECAM-1) has many functions, including its roles in leukocyte extravasation as part of the inflammatory response and in the maintenance of vascular integrity through its contribution to endothelial cell−cell adhesion. PECAM-1 has been shown to mediate cell−cell adhesion through homophilic binding events that involve interactions between domain 1 of PECAM-1 molecules on adjacent cells. However, various heterophilic ligands of PECAM-1 have also been proposed. The possible interaction of PECAM-1 with glycosaminoglycans (GAGs) is the focus of this study. The three-dimensional structure of the extracellular immunoglobulin (Ig) domains of PECAM-1 were constructed using homology modeling and threading methods. Potential heparin/heparan sulfate-binding sites were predicted on the basis of their amino acid consensus sequences and a comparison with known structures of sulfate-binding proteins. Heparin and other GAG fragments have been docked to investigate the structural determinants of their protein-binding specificity and selectivity. The modeling has predicted two regions in PECAM-1 that appear to bind heparin oligosaccharides. A high-affinity binding site was located in Ig domains 2 and 3, and evidence for a low-affinity site in Ig domains 5 and 6 was obtained. These GAG-binding regions were distinct from regions involved in PECAM-1 homophilic interactions.
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A number of analogues of diaryl dihydropyrazole-3-carboxamides have been synthesized. Their activities were evaluated for appetite suppression and body weight reduction in animal models. Depending on the chemical modification of the selected dihydropyrazole scaffold, the lead compoundsthe bisulfate salt of (±)-5-(4-chlorophenyl)-1-(2,4-dichlorophenyl)-4,5-dihydro-1H-pyrazole-3-carboxylic acid morpholin-4-ylamide 26 and the bisulfate salt of (−)-5-(4-chlorophenyl)-1-(2,4-dichlorophenyl)-4,5-dihydro-1H-pyrazole-3-carboxylic acid morpholin-4-ylamide 30showed significant body weight reduction in vivo, which is attributed to their CB1 antagonistic activity and exhibited a favorable pharmacokinetic profile. The molecular modeling studies also showed interactions of two isomers of (±)-5-(4-chlorophenyl)-1-(2,4-dichlorophenyl)-4,5-dihydro-1H-pyrazole-3-carboxylic acid morpholin-4-ylamide 9 with CB1 receptor in the homology model similar to those of N-piperidino-5-(4-chlorophenyl)-1-(2,4-dichlorophenyl)-4-methyl-3-pyrazole-carboxamide (rimonabant) 1 and 4S-(−)-3-(4-chlorophenyl)-N-methyl-N‘-[(4-chlorophenyl)-sulfonyl]-4-phenyl-4,5-dihydro-1H-pyrazole-1-carboxamidine (SLV-319) 2.
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Genetic engineering of Bacillus thuringiensis (Bt) Cry proteins has resulted in the synthesis of various novel toxin proteins with enhanced insecticidal activity and specificity towards different insect pests. In this study, a fusion protein consisting of the DI–DII domains of Cry1Ac and garlic lectin (ASAL) has been designed in silico by replacing the DIII domain of Cry1Ac with ASAL. The binding interface between the DI–DII domains of Cry1Ac and lectin has been identified using protein–protein docking studies. Free energy of binding calculations and interaction profiles between the Cry1Ac and lectin domains confirmed the stability of fusion protein. A total of 18 hydrogen bonds was observed in the DI–DII–lectin fusion protein compared to 11 hydrogen bonds in the Cry1Ac (DI–DII–DIII) protein. Molecular mechanics/Poisson–Boltzmann (generalized-Born) surface area [MM/PB (GB) SA] methods were used for predicting free energy of interactions of the fusion proteins. Protein–protein docking studies based on the number of hydrogen bonds, hydrophobic interactions, aromatic–aromatic, aromatic–sulphur, cation–pi interactions and binding energy of Cry1Ac/fusion proteins with the aminopeptidase N (APN) of Manduca sexta rationalised the higher binding affinity of the fusion protein with the APN receptor compared to that of the Cry1Ac–APN complex, as predicted by ZDOCK, Rosetta and ClusPro analysis. The molecular binding interface between the fusion protein and the APN receptor is well packed, analogously to that of the Cry1Ac–APN complex. These findings offer scope for the design and development of customized fusion molecules for improved pest management in crop plants.
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This paper highlights the Hybrid agent construction model being developed that allows the description and development of autonomous agents in SAGE (Scalable, fault Tolerant Agent Grooming Environment) - a second generation FIPA-Compliant Multi-Agent system. We aim to provide the programmer with a generic and well defined agent architecture enabling the development of sophisticated agents on SAGE, possessing the desired properties of autonomous agents - reactivity, pro-activity, social ability and knowledge based reasoning. © Springer-Verlag Berlin Heidelberg 2005.
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Spatial variations in the concentration of a reactive solute in solution are often encountered in a catalyst particle, and this leads to variation in the freezing point of the solution. Depending on the operating temperature, this can result in freezing of the solvent oil a portion of catalyst, rendering that part of the active area ineffective Freezing call occur by formation of a sharp front or it mush that separates the solid and fluid phases. In this paper, we model the extent of reduction in the active area due to freezing. Assuming that the freezing point decreases linearly with solute concentration, conditions for freezing to occur have been derived. At steady state, the ineffective fraction of catalyst pellet is found to be the same irrespective of the mode of freezing. Progress of freezing is determined by both the heat of reaction and the latent heat of fusion Unlike in freezing of alloys where the latter plays a dominant role, the exothermicity of the reaction has a significant effect on freezing in the presence of chemical reactions. A dimensionless group analogous to the Stefan number could be defined to capture the combined effect of both of these.
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We propose a self-regularized pseudo-time marching strategy for ill-posed, nonlinear inverse problems involving recovery of system parameters given partial and noisy measurements of system response. While various regularized Newton methods are popularly employed to solve these problems, resulting solutions are known to sensitively depend upon the noise intensity in the data and on regularization parameters, an optimal choice for which remains a tricky issue. Through limited numerical experiments on a couple of parameter re-construction problems, one involving the identification of a truss bridge and the other related to imaging soft-tissue organs for early detection of cancer, we demonstrate the superior features of the pseudo-time marching schemes.
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The network scenario is that of an infrastructure IEEE 802.11 WLAN with a single AP with which several stations (STAs) are associated. The AP has a finite size buffer for storing packets. In this scenario, we consider TCP-controlled upload and download file transfers between the STAs and a server on the wireline LAN (e.g., 100 Mbps Ethernet) to which the AP is connected. In such a situation, it is well known that because of packet losses due to finite buffers at the AP, upload file transfers obtain larger throughputs than download transfers. We provide an analytical model for estimating the upload and download throughputs as a function of the buffer size at the AP. We provide models for the undelayed and delayed ACK cases for a TCP that performs loss recovery only by timeout, and also for TCP Reno. The models are validated incomparison with NS2 simulations.
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Ferrous iron bio-oxidation by Acidithiobacillus ferrooxidans immobilized on polyurethane foam was investigated. Cells were immobilized on foams by placing them in a growth environment and fully bacterially activated polyurethane foams (BAPUFs) were prepared by serial subculturing in batches with partially bacterially activated foam (pBAPUFs). The dependence of foam density on cell immobilization process, the effect of pH and BAPUF loading on ferrous oxidation were studied to choose operating parameters for continuous operations. With an objective to have high cell densities both in foam and the liquid phase, pretreated foams of density 50 kg/m3 as cell support and ferrous oxidation at pH 1.5 to moderate the ferric precipitation were preferred. A novel basket-type bioreactor for continuous ferrous iron oxidation, which features a multiple effect of stirred tank in combination with recirculation, was designed and operated. The results were compared with that of a free cell and a sheet-type foam immobilized reactors. A fivefold increase in ferric iron productivity at 33.02 g/h/L of free volume in foam was achieved using basket-type bioreactor when compared to a free cell continuous system. A mathematical model for ferrous iron oxidation by Acidithiobacillus ferrooxidans cells immobilized on polyurethane foam was developed with cell growth in foam accounted by an effectiveness factor. The basic parameters of simulation were estimated using the experimental data on free cell growth as well as from cell attachment to foam under nongrowing conditions. The model predicted the phase of both oxidation of ferrous in shake flasks by pBAPUFs as well as by fully activated BAPUFs for different cell loadings in foam. Model for stirred tank basket bioreactor predicted within 5% both transient and steady state of the experiments closely for the simulated dilution rates. Bio-oxidation at high Fe2+ concentrations were simulated with experiments when substrate and product inhibition coefficients were factored into cell growth kinetics.
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A mathematical model is developed to simulate oxygen consumption, heat generation and cell growth in solid state fermentation (SSF). The fungal growth on the solid substrate particles results in the increase of the cell film thickness around the particles. The model incorporates this increase in the biofilm size which leads to decrease in the porosity of the substrate bed and diffusivity of oxygen in the bed. The model also takes into account the effect of steric hindrance limitations in SSF. The growth of cells around single particle and resulting expansion of biofilm around the particle is analyzed for simplified zero and first order oxygen consumption kinetics. Under conditions of zero order kinetics, the model predicts upper limit on cell density. The model simulations for packed bed of solid particles in tray bioreactor show distinct limitations on growth due to simultaneous heat and mass transport phenomena accompanying solid state fermentation process. The extent of limitation due to heat and/or mass transport phenomena is analyzed during different stages of fermentation. It is expected that the model will lead to better understanding of the transport processes in SSF, and therefore, will assist in optimal design of bioreactors for SSF.
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Swarm Intelligence techniques such as particle swarm optimization (PSO) are shown to be incompetent for an accurate estimation of global solutions in several engineering applications. This problem is more severe in case of inverse optimization problems where fitness calculations are computationally expensive. In this work, a novel strategy is introduced to alleviate this problem. The proposed inverse model based on modified particle swarm optimization algorithm is applied for a contaminant transport inverse model. The inverse models based on standard-PSO and proposed-PSO are validated to estimate the accuracy of the models. The proposed model is shown to be out performing the standard one in terms of accuracy in parameter estimation. The preliminary results obtained using the proposed model is presented in this work.
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A considerable amount of work has been dedicated on the development of analytical solutions for flow of chemical contaminants through soils. Most of the analytical solutions for complex transport problems are closed-form series solutions. The convergence of these solutions depends on the eigen values obtained from a corresponding transcendental equation. Thus, the difficulty in obtaining exact solutions from analytical models encourages the use of numerical solutions for the parameter estimation even though, the later models are computationally expensive. In this paper a combination of two swarm intelligence based algorithms are used for accurate estimation of design transport parameters from the closed-form analytical solutions. Estimation of eigen values from a transcendental equation is treated as a multimodal discontinuous function optimization problem. The eigen values are estimated using an algorithm derived based on glowworm swarm strategy. Parameter estimation of the inverse problem is handled using standard PSO algorithm. Integration of these two algorithms enables an accurate estimation of design parameters using closed-form analytical solutions. The present solver is applied to a real world inverse problem in environmental engineering. The inverse model based on swarm intelligence techniques is validated and the accuracy in parameter estimation is shown. The proposed solver quickly estimates the design parameters with a great precision.
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A compact model for noise margin (NM) of single-electron transistor (SET) logic is developed, which is a function of device capacitances and background charge (zeta). Noise margin is, then, used as a metric to evaluate the robustness of SET logic against background charge, temperature, and variation of SET gate and tunnel junction capacitances (CG and CT). It is shown that choosing alpha=CT/CG=1/3 maximizes the NM. An estimate of the maximum tolerable zeta is shown to be equal to plusmn0.03 e. Finally, the effect of mismatch in device parameters on the NM is studied through exhaustive simulations, which indicates that a isin [0.3, 0.4] provides maximum robustness. It is also observed that mismatch can have a significant impact on static power dissipation.
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Many biological environments are crowded by macromolecules, organelles and cells which can impede the transport of other cells and molecules. Previous studies have sought to describe these effects using either random walk models or fractional order diffusion equations. Here we examine the transport of both a single agent and a population of agents through an environment containing obstacles of varying size and shape, whose relative densities are drawn from a specified distribution. Our simulation results for a single agent indicate that smaller obstacles are more effective at retarding transport than larger obstacles; these findings are consistent with our simulations of the collective motion of populations of agents. In an attempt to explore whether these kinds of stochastic random walk simulations can be described using a fractional order diffusion equation framework, we calibrate the solution of such a differential equation to our averaged agent density information. Our approach suggests that these kinds of commonly used differential equation models ought to be used with care since we are unable to match the solution of a fractional order diffusion equation to our data in a consistent fashion over a finite time period.