908 resultados para approach to learning


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Estimation of design quantiles of hydrometeorological variables at critical locations in river basins is necessary for hydrological applications. To arrive at reliable estimates for locations (sites) where no or limited records are available, various regional frequency analysis (RFA) procedures have been developed over the past five decades. The most widely used procedure is based on index-flood approach and L-moments. It assumes that values of scale and shape parameters of frequency distribution are identical across all the sites in a homogeneous region. In real-world scenario, this assumption may not be valid even if a region is statistically homogeneous. To address this issue, a novel mathematical approach is proposed. It involves (i) identification of an appropriate frequency distribution to fit the random variable being analyzed for homogeneous region, (ii) use of a proposed transformation mechanism to map observations of the variable from original space to a dimensionless space where the form of distribution does not change, and variation in values of its parameters is minimal across sites, (iii) construction of a growth curve in the dimensionless space, and (iv) mapping the curve to the original space for the target site by applying inverse transformation to arrive at required quantile(s) for the site. Effectiveness of the proposed approach (PA) in predicting quantiles for ungauged sites is demonstrated through Monte Carlo simulation experiments considering five frequency distributions that are widely used in RFA, and by case study on watersheds in conterminous United States. Results indicate that the PA outperforms methods based on index-flood approach.

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Systems biology is revealing multiple layers of regulatory networks that manifest spatiotemporal variations. Since genes and environment also influence the emergent property of a cell, the biological output requires dynamic understanding of various molecular circuitries. The metabolic networks continually adapt and evolve to cope with the changing milieu of the system, which could also include infection by another organism. Such perturbations of the functional networks can result in disease phenotypes, for instance tuberculosis and cancer. In order to develop effective therapeutics, it is important to determine the disease progression profiles of complex disorders that can reveal dynamic aspects and to develop mutitarget systemic therapies that can help overcome pathway adaptations and redundancy.

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Background: The set of indispensable genes that are required by an organism to grow and sustain life are termed as essential genes. There is a strong interest in identification of the set of essential genes, particularly in pathogens, not only for a better understanding of the pathogen biology, but also for identifying drug targets and the minimal gene set for the organism. Essentiality is inherently a systems property and requires consideration of the system as a whole for their identification. The available experimental approaches capture some aspects but each method comes with its own limitations. Moreover, they do not explain the basis for essentiality in most cases. A powerful prediction method to recognize this gene pool including rationalization of the known essential genes in a given organism would be very useful. Here we describe a multi-level multi-scale approach to identify the essential gene pool in a deadly pathogen, Mycobacterium tuberculosis. Results: The multi-level workflow analyses the bacterial cell by studying (a) genome-wide gene expression profiles to identify the set of genes which show consistent and significant levels of expression in multiple samples of the same condition, (b) indispensability for growth by using gene expression integrated flux balance analysis of a genome-scale metabolic model, (c) importance for maintaining the integrity and flow in a protein-protein interaction network and (d) evolutionary conservation in a set of genomes of the same ecological niche. In the gene pool identified, the functional basis for essentiality has been addressed by studying residue level conservation and the sub-structure at the ligand binding pockets, from which essential amino acid residues in that pocket have also been identified. 283 genes were identified as essential genes with high-confidence. An agreement of about 73.5% is observed with that obtained from the experimental transposon mutagenesis technique. A large proportion of the identified genes belong to the class of intermediary metabolism and respiration. Conclusions: The multi-scale, multi-level approach described can be generally applied to other pathogens as well. The essential gene pool identified form a basis for designing experiments to probe their finer functional roles and also serve as a ready shortlist for identifying drug targets.

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We have recently suggested a method (Pallavi Bhattacharyya and K. L. Sebastian, Physical Review E 2013, 87, 062712) for the analysis of coherence in finite-level systems that are coupled to the surroundings and used it to study the process of energy transfer in the Fenna-Matthews-Olson (FMO) complex. The method makes use of adiabatic eigenstates of the Hamiltonian, with a subsequent transformation of the Hamiltonian into a form where the terms responsible for decoherence and population relaxation could be separated out at the lowest order. Thus one can account for decoherence nonperturbatively, and a Markovian type of master equation could be used for evaluating the population relaxation. In this paper, we apply this method to a two-level system as well as to a seven-level system. Comparisons with exact numerical results show that the method works quite well and is in good agreement with numerical calculations. The technique can be applied with ease to systems with larger numbers of levels as well. We also investigate how the presence of correlations among the bath degrees of freedom of the different bacteriochlorophyll a molecules of the FMO Complex affect the rate of energy transfer. Surprisingly, in the cases that we studied, our calculations suggest that the presence of anticorrelations, in contrast to correlations, make the excitation transfer more facile.

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Chiral auxiliaries are used for the NMR spectroscopic study of enantiomers. Often the presence of impurities, overlap of peaks, line broadening and the multiplicity pattern restrict the chiral analysis in the 1D H-1 NMR spectrum. The present study introduces a simple 2D H-1 NMR experiment to unravel the overlapped spectrum. The experiment separates the spectra of enantiomers, thereby allowing the unambiguous assignment of all the coupled peaks and the measurement of enantiomeric excess (ee) from a single experiment even in combinatorial mixtures.

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Two new dicyanovinyl (DCV) functionalized triarylboranes (Mes(2)B-pi-spacer-DCV, for 1: pi-spacer = C6H4, for 2: pi-spacer = 2,3,5,6-tetramethyl-phenyl) are reported. The molecular structures of 1 and 2 are similar except for the spacer which connects the boryl and DCV units. This small structural perturbation induces drastic changes in the optical properties of 1 and 2. Compound 2 shows weak dual fluorescence emission in nonpolar solvents and a stronger emission in polar solvents. Compound 1 is weakly fluorescent in polar environments but shows an intense single luminescence peak in less polar environments. Compound 1 exhibits a turn-off fluorescence response for both fluoride and cyanide: in contrast, 2 shows a turn on fluorescence response for both anions with different fluorescence signatures. The NMR titration studies reveal that for compound 2, fluoride binds to the boron centre and cyanide binds to the DCV unit. For compound 1, the fluoride ion binds to the boron center, whereas the CN- binds to both the Ar3B and DCV units.

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The present article describes a working or combined calibration curve in laser-induced breakdown spectroscopic analysis, which is the cumulative result of the calibration curves obtained from neutral and singly ionized atomic emission spectral lines. This working calibration curve reduces the effect of change in matrix between different zone soils and certified soil samples because it includes both the species' (neutral and singly ionized) concentration of the element of interest. The limit of detection using a working calibration curve is found better as compared to its constituent calibration curves (i.e., individual calibration curves). The quantitative results obtained using the working calibration curve is in better agreement with the result of inductively coupled plasma-atomic emission spectroscopy as compared to the result obtained using its constituent calibration curves.

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An efficient and scalable total synthesis of the architecturally challenging sesquiterpenoid (+/-)-penifulvin A has been accomplished via a 12-step sequence with an overall yield of 16%. For the construction of this structurally complex tetracyclic molecule, the key steps used included 1,4-conjugate addition, a Pd(0) catalyzed cross-coupling reaction between an enol phosphate and trimethyl aluminum, Claisen rearrangement using the Johnson orthoester protocol, Ti(III)-mediated reductive epoxide opening-cyclization, Lewis acid catalyzed epoxy-aldehyde rearrangement, and finally a substrate controlled oxidative cascade lactonization process.

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Motivated by several recent experimental observations that vitamin-D could interact with antigen presenting cells (APCs) and T-lymphocyte cells (T-cells) to promote and to regulate different stages of immune response, we developed a coarse grained but general kinetic model in an attempt to capture the role of vitamin-D in immunomodulatory responses. Our kinetic model, developed using the ideas of chemical network theory, leads to a system of nine coupled equations that we solve both by direct and by stochastic (Gillespie) methods. Both the analyses consistently provide detail information on the dependence of immune response to the variation of critical rate parameters. We find that although vitamin-D plays a negligible role in the initial immune response, it exerts a profound influence in the long term, especially in helping the system to achieve a new, stable steady state. The study explores the role of vitamin-D in preserving an observed bistability in the phase diagram (spanned by system parameters) of immune regulation, thus allowing the response to tolerate a wide range of pathogenic stimulation which could help in resisting autoimmune diseases. We also study how vitamin-D affects the time dependent population of dendritic cells that connect between innate and adaptive immune responses. Variations in dose dependent response of anti-inflammatory and pro-inflammatory T-cell populations to vitamin-D correlate well with recent experimental results. Our kinetic model allows for an estimation of the range of optimum level of vitamin-D required for smooth functioning of the immune system and for control of both hyper-regulation and inflammation. Most importantly, the present study reveals that an overdose or toxic level of vitamin-D or any steroid analogue could give rise to too large a tolerant response, leading to an inefficacy in adaptive immune function.

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We develop an approach that combines the power of nonlinear dynamics with the evolution equations for the mobile and immobile dislocation densities and force to explain force fluctuations in nanoindentation experiments. The model includes nucleation, multiplication, and propagation thresholds for mobile dislocations, and other well known dislocation transformation mechanisms. The model predicts all the generic features of nanoindentation such as the Hertzian elastic branch followed by several force drops of decreasing magnitudes, and residual plasticity after unloading. The stress corresponding to the elastic force maximum is close to the yield stress of an ideal solid. The predicted values for all the quantities are close to those reported by experiments. Our model allows us to address the indentation-size effect including the ambiguity in defining the hardness in the force drop dominated regime. At large indentation depths, the hardness remains nearly constant with a marginal decreasing trend.

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A simple, mild, and cost effective methodology has been developed for the synthesis of aryl thio-and selenoglycosides from glycosyl halides and diaryl dichalcogenides. Diaryl dichalcogenides undergo reductive cleavage in the presence of rongalite (HOCH2SO2Na) to generate a chalcogenide anion in situ followed by reaction with glycosyl halides to furnish the corresponding aryl thio- and selenoglycosides in excellent yields. Using this protocol, synthesis of 4-methyl-7-thioumbelliferyl-beta-D-cellobioside (MUS-CB), a fluorescent non-hydrolyzable substrate analogue for cellulases has been achieved. (C) 2014 Elsevier Ltd. All rights reserved.

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This article presents our work on the sigma-Ferrier ring-expansion of carbohydrate derived vinylcyclopropanes (VCPs) under electrophilic conditions mediated by chloramine-T and a phase-transfer catalyst. The present work serves as the first example on the studies of the reactivity of carbohydrate VCPs towards the synthesis of densely functionalized oxepane analogues. The work elaborates on a reasonable mechanism for the product formation and our observations on the diastereoselectivity based on control experiments and gas-phase calculations. (C) 2014 Elsevier Ltd. All rights reserved.

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A new global stochastic search, guided mainly through derivative-free directional information computable from the sample statistical moments of the design variables within a Monte Carlo setup, is proposed. The search is aided by imparting to the directional update term additional layers of random perturbations referred to as `coalescence' and `scrambling'. A selection step, constituting yet another avenue for random perturbation, completes the global search. The direction-driven nature of the search is manifest in the local extremization and coalescence components, which are posed as martingale problems that yield gain-like update terms upon discretization. As anticipated and numerically demonstrated, to a limited extent, against the problem of parameter recovery given the chaotic response histories of a couple of nonlinear oscillators, the proposed method appears to offer a more rational, more accurate and faster alternative to most available evolutionary schemes, prominently the particle swarm optimization. (C) 2014 Elsevier B.V. All rights reserved.

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Information available in frequency response data is equivalently available in the time domain as a response due to an impulse excitation. The idea to pursue this equivalence to estimate series capacitance is linked to the well-known fact that under impulse excitation, the line/neutral current in a transformer has three distinct components, of which, the initial capacitive component is the first to manifest, followed by the oscillatory and inductive components. Of these, the capacitive component is temporally well separated from the rest-a crucial feature permitting its direct access and analysis. Further, the winding initially behaves as a pure capacitive network, so the initial component must obviously originate from only the (series and shunt) capacitances. With this logic, it should therefore be possible to estimate series capacitance, just by measuring the initial capacitive component of line current and the total shunt capacitance. The principle of the method and details of its implementation on two actual isolated transformerwindings (uniformly wound) are presented. For implementation, a low-voltage recurrent surge generator, a current probe, and a digital oscilloscope are all that is needed. The method is simple and requires no programming and needs least user intervention, thus paving the way for its widespread use.

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The objective of this work was to develop a versatile strategy for preparing biodegradable polymers with tunable properties for biomedical applications. A family of xylitol-based cross-linked polyesters was synthesized by melt condensation. The effect of systematic variation of chain length of the diacid, stoichiometric ratio, and postpolymerization curing time on the physicochemical properties was characterized. The degradation rate decreased as the chain length of the diacid increased. The polyesters synthesized by this approach possess a diverse spectrum of degradation (ranging from similar to 4 to 100% degradation in 7 days), mechanical strength (from 0.5 to similar to 15 MPa) and controlled release properties. The degradation was a first-order process and the rate constant of degradation decreased linearly as the hydrophobicity of the polyester increased. In controlled release studies, the order of diffusion increased with chain length and curing time. The polymers were found to be cytocompatible and are thus suitable for possible use as biodegradable polymers. This work demonstrates that this particular combinatorial approach to polymer synthesis can be used to prepare biomaterials with independently tunable properties.