883 resultados para Functional Approach


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Large variations in human actions lead to major challenges in computer vision research. Several algorithms are designed to solve the challenges. Algorithms that stand apart, help in solving the challenge in addition to performing faster and efficient manner. In this paper, we propose a human cognition inspired projection based learning for person-independent human action recognition in the H.264/AVC compressed domain and demonstrate a PBL-McRBEN based approach to help take the machine learning algorithms to the next level. Here, we use gradient image based feature extraction process where the motion vectors and quantization parameters are extracted and these are studied temporally to form several Group of Pictures (GoP). The GoP is then considered individually for two different bench mark data sets and the results are classified using person independent human action recognition. The functional relationship is studied using Projection Based Learning algorithm of the Meta-cognitive Radial Basis Function Network (PBL-McRBFN) which has a cognitive and meta-cognitive component. The cognitive component is a radial basis function network while the Meta-Cognitive Component(MCC) employs self regulation. The McC emulates human cognition like learning to achieve better performance. Performance of the proposed approach can handle sparse information in compressed video domain and provides more accuracy than other pixel domain counterparts. Performance of the feature extraction process achieved more than 90% accuracy using the PTIL-McRBFN which catalyzes the speed of the proposed high speed action recognition algorithm. We have conducted twenty random trials to find the performance in GoP. The results are also compared with other well known classifiers in machine learning literature.

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DNA processing protein A (DprA) plays a crucial role in the process of natural transformation. This is accomplished through binding and subsequent protection of incoming foreign DNA during the process of internalization. DprA along with Single stranded DNA binding protein A (SsbA) acts as an accessory factor for RecA mediated DNA strand exchange. H. pylori DprA (HpDprA) is divided into an N-terminal domain and a C-terminal domain. In the present study, individual domains of HpDprA have been characterized for their ability to bind single stranded (ssDNA) and double stranded DNA (dsDNA). Oligomeric studies revealed that HpDprA possesses two sites for dimerization which enables HpDprA to form large and tightly packed complexes with ss and dsDNA. While the N-terminal domain was found to be sufficient for binding with ss or ds DNA, C-terminal domain has an important role in the assembly of poly-nucleoprotein complex. Using site directed mutagenesis approach, we show that a pocket comprising positively charged amino acids in the N-terminal domain has an important role in the binding of ss and dsDNA. Together, a functional cross talk between the two domains of HpDprA facilitating the binding and formation of higher order complex with DNA is discussed.

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We present a framework for obtaining reliable solid-state charge and optical excitations and spectra from optimally tuned range-separated hybrid density functional theory. The approach, which is fully couched within the formal framework of generalized Kohn-Sham theory, allows for the accurate prediction of exciton binding energies. We demonstrate our approach through first principles calculations of one- and two-particle excitations in pentacene, a molecular semiconducting crystal, where our work is in excellent agreement with experiments and prior computations. We further show that with one adjustable parameter, set to produce the known band gap, this method accurately predicts band structures and optical spectra of silicon and lithium fluoride, prototypical covalent and ionic solids. Our findings indicate that for a broad range of extended bulk systems, this method may provide a computationally inexpensive alternative to many-body perturbation theory, opening the door to studies of materials of increasing size and complexity.

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Functional linkage between reef habitat quality and fish growth and production has remained elusive. Most current research is focused on correlative relationships between a general habitat type and presence/absence of a species, an index of species abundance, or species diversity. Such descriptive information largely ignores how reef attributes regulate reef fish abundance (density-dependent habitat selection), trophic interactions, and physiological performance (growth and condition). To determine the functional relationship between habitat quality, fish abundance, trophic interactions, and physiological performance, we are using an experimental reef system in the northeastern Gulf of Mexico where we apply advanced sensor and biochemical technologies. Our study site controls for reef attributes (size, cavity space, and reef mosaics) and focuses on the processes that regulate gag grouper (Mycteroperca microlepis) abundance, behavior and performance (growth and condition), and the availability of their pelagic prey. We combine mobile and fixed-active (fisheries) acoustics, passive acoustics, video cameras, and advanced biochemical techniques. Fisheries acoustics quantifies the abundance of pelagic prey fishes associated with the reefs and their behavior. Passive acoustics and video allow direct observation of gag and prey fish behavior and the acoustic environment, and provide a direct visual for the interpretation of fixed fisheries acoustics measurements. New application of biochemical techniques, such as Electron Transport System (ETS) assay, allow the in situ measurement of metabolic expenditure of gag and relates this back to reef attributes, gag behavior, and prey fish availability. Here, we provide an overview of our integrated technological approach for understanding and quantifying the functional relationship between reef habitat quality and one element of production – gag grouper growth on shallow coastal reefs.

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A leucine-inserting tRNA has been transformed into a serine-inserting tRNA by changing 12 nucleotides. Only 8 of the 12 changes are required to effect the conversion of the leucine tRNA to serine tRNA identity. The 8 essential changes reside in basepair 11-24 in the D stem, basepairs 3-70, 2-71 and nucleotides 72 and 73, all of the acceptor stem.

Functional amber suppressor tRNA genes were generated for 14 species of tRNA in E. coli, and their amino acid specificities determined. The suppressors can be classified into three groups, based upon their specificities. Class I suppressors, tRNA^(Ala2)_(CUA), tRNA^(GlyU)_(CUA), tRNA^(HisA)_(CUA), tRNA^(Lys)_(CUA), and tRNA^(ProH)_(CUA), inserted the predicted amino acid. The Class II suppressors, tRNA^(GluA)_(CUA) , tRNA^(GlyT)_(CUA), and tRNA^(Ile1)_(CUA) were either partially or predominantly mischarged by the glutamine aminoacyl tRNA synthetase (AAS). The Class III suppressors, tRNA^(Arg)_(CUA), tRNA^(AspM)_(CUA), tRNA^(Ile2)_(CUA), tRNA^(Thr2)_(CUA), tRNA^(Met(m))_(CUA) and tRNA^(Val)_(CUA) inserted predominantly lysine.

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Methods that exploit the intrinsic locality of molecular interactions show significant promise in making tractable the electronic structure calculation of large-scale systems. In particular, embedded density functional theory (e-DFT) offers a formally exact approach to electronic structure calculations in which the interactions between subsystems are evaluated in terms of their electronic density. In the following dissertation, methodological advances of embedded density functional theory are described, numerically tested, and applied to real chemical systems.

First, we describe an e-DFT protocol in which the non-additive kinetic energy component of the embedding potential is treated exactly. Then, we present a general implementation of the exact calculation of the non-additive kinetic potential (NAKP) and apply it to molecular systems. We demonstrate that the implementation using the exact NAKP is in excellent agreement with reference Kohn-Sham calculations, whereas the approximate functionals lead to qualitative failures in the calculated energies and equilibrium structures.

Next, we introduce density-embedding techniques to enable the accurate and stable calculation of correlated wavefunction (CW) in complex environments. Embedding potentials calculated using e-DFT introduce the effect of the environment on a subsystem for CW calculations (WFT-in-DFT). We demonstrate that WFT-in-DFT calculations are in good agreement with CW calculations performed on the full complex.

We significantly improve the numerics of the algorithm by enforcing orthogonality between subsystems by introduction of a projection operator. Utilizing the projection-based embedding scheme, we rigorously analyze the sources of error in quantum embedding calculations in which an active subsystem is treated using CWs, and the remainder using density functional theory. We show that the embedding potential felt by the electrons in the active subsystem makes only a small contribution to the error of the method, whereas the error in the nonadditive exchange-correlation energy dominates. We develop an algorithm which corrects this term and demonstrate the accuracy of this corrected embedding scheme.

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In this work we chiefly deal with two broad classes of problems in computational materials science, determining the doping mechanism in a semiconductor and developing an extreme condition equation of state. While solving certain aspects of these questions is well-trodden ground, both require extending the reach of existing methods to fully answer them. Here we choose to build upon the framework of density functional theory (DFT) which provides an efficient means to investigate a system from a quantum mechanics description.

Zinc Phosphide (Zn3P2) could be the basis for cheap and highly efficient solar cells. Its use in this regard is limited by the difficulty in n-type doping the material. In an effort to understand the mechanism behind this, the energetics and electronic structure of intrinsic point defects in zinc phosphide are studied using generalized Kohn-Sham theory and utilizing the Heyd, Scuseria, and Ernzerhof (HSE) hybrid functional for exchange and correlation. Novel 'perturbation extrapolation' is utilized to extend the use of the computationally expensive HSE functional to this large-scale defect system. According to calculations, the formation energy of charged phosphorus interstitial defects are very low in n-type Zn3P2 and act as 'electron sinks', nullifying the desired doping and lowering the fermi-level back towards the p-type regime. Going forward, this insight provides clues to fabricating useful zinc phosphide based devices. In addition, the methodology developed for this work can be applied to further doping studies in other systems.

Accurate determination of high pressure and temperature equations of state is fundamental in a variety of fields. However, it is often very difficult to cover a wide range of temperatures and pressures in an laboratory setting. Here we develop methods to determine a multi-phase equation of state for Ta through computation. The typical means of investigating thermodynamic properties is via ’classical’ molecular dynamics where the atomic motion is calculated from Newtonian mechanics with the electronic effects abstracted away into an interatomic potential function. For our purposes, a ’first principles’ approach such as DFT is useful as a classical potential is typically valid for only a portion of the phase diagram (i.e. whatever part it has been fit to). Furthermore, for extremes of temperature and pressure quantum effects become critical to accurately capture an equation of state and are very hard to capture in even complex model potentials. This requires extending the inherently zero temperature DFT to predict the finite temperature response of the system. Statistical modelling and thermodynamic integration is used to extend our results over all phases, as well as phase-coexistence regions which are at the limits of typical DFT validity. We deliver the most comprehensive and accurate equation of state that has been done for Ta. This work also lends insights that can be applied to further equation of state work in many other materials.

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Kohn-Sham density functional theory (KSDFT) is currently the main work-horse of quantum mechanical calculations in physics, chemistry, and materials science. From a mechanical engineering perspective, we are interested in studying the role of defects in the mechanical properties in materials. In real materials, defects are typically found at very small concentrations e.g., vacancies occur at parts per million, dislocation density in metals ranges from $10^{10} m^{-2}$ to $10^{15} m^{-2}$, and grain sizes vary from nanometers to micrometers in polycrystalline materials, etc. In order to model materials at realistic defect concentrations using DFT, we would need to work with system sizes beyond millions of atoms. Due to the cubic-scaling computational cost with respect to the number of atoms in conventional DFT implementations, such system sizes are unreachable. Since the early 1990s, there has been a huge interest in developing DFT implementations that have linear-scaling computational cost. A promising approach to achieving linear-scaling cost is to approximate the density matrix in KSDFT. The focus of this thesis is to provide a firm mathematical framework to study the convergence of these approximations. We reformulate the Kohn-Sham density functional theory as a nested variational problem in the density matrix, the electrostatic potential, and a field dual to the electron density. The corresponding functional is linear in the density matrix and thus amenable to spectral representation. Based on this reformulation, we introduce a new approximation scheme, called spectral binning, which does not require smoothing of the occupancy function and thus applies at arbitrarily low temperatures. We proof convergence of the approximate solutions with respect to spectral binning and with respect to an additional spatial discretization of the domain. For a standard one-dimensional benchmark problem, we present numerical experiments for which spectral binning exhibits excellent convergence characteristics and outperforms other linear-scaling methods.

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Models for simulating Scanning Probe Microscopy (SPM) may serve as a reference point for validating experimental data and practice. Generally, simulations use a microscopic model of the sample-probe interaction based on a first-principles approach, or a geometric model of macroscopic distortions due to the probe geometry. Examples of the latter include use of neural networks, the Legendre Transform, and dilation/erosion transforms from mathematical morphology. Dilation and the Legendre Transform fall within a general family of functional transforms, which distort a function by imposing a convex solution.In earlier work, the authors proposed a generalized approach to modeling SPM using a hidden Markov model, wherein both the sample-probe interaction and probe geometry may be taken into account. We present a discussion of the hidden Markov model and its relationship to these convex functional transforms for simulating and restoring SPM images.©2009 SPIE.

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Product-Service Systems (PSS) are new business strategies moving and extending the product value towards its functional usage and related required services. From a theoretical point of view the PSS concept is known since a decade and many Authors reported reasonable possible success factors: higher profits over the entire life-cycle, diminished environmental burden, and localization of required services. Nevertheless the PSS promises remain quantitatively unproven relaying on a simple theory that involves a few constructs with some empirical grounding, but that is limited by weak conceptualization, few propositions, and/or rough underlying theoretical logic. A plausible interpretation to analyze the possible evolution of a PSS strategy could be considering it as a new business proposition competing on a traditional Product-Oriented (PO) market, assumed at its own equilibrium state at a given time. The analysis of the dynamics associated to a possible transition from a traditional PO to a PSS strategy allows investigating the main parameters and variables influencing an eventual successful adoption. This research is worthwhile because organizations undergoing fundamental PSS strategy are concerned about change and inertia key processes which, despite equilibrium theory and because of negative feedback loops, could undermine, economically, the return of their PSS proposition. In this paper Authors propose a qualitative System Dynamics (SD) approach by considering the PSS as a perturbation of an existing PO market featured by a set of known parameters. The proposed model incorporates several PSS factors able to influence the success of a PSS proposition under a set of given and justified assumptions, attempting to place this business strategy in a dynamic framework.

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The entry of human immunodeficiency virus (HIV) into cells depends on a sequential interaction of the gp120 envelope glycoprotein with the cellular receptors CD4 and members of the chemokine receptor family. The CC chemokine receptor CCR5 is such a receptor for several chemokines and a major coreceptor for the entry of R5 HIV type-1 (HIV-1) into cells. Although many studies focus on the interaction of CCR5 with HIV-1, the corresponding interaction sites in CCR5 and gp120 have not been matched. Here we used an approach combining protein structure modeling, docking and molecular dynamics simulation to build a series of structural models of the CCR5 in complexes with gp120 and CD4. Interactions such as hydrogen bonds, salt bridges and van der Waals contacts between CCR5 and gp120 were investigated. Three snapshots of CCR5-gp120-CD4 models revealed that the initial interactions of CCR5 with gp120 are involved in the negatively charged N-terminus (Nt) region of CCR5 and positively charged bridging sheet region of gp120. Further interactions occurred between extracellular loop2 (ECL2) of CCR5 and the base of V3 loop regions of gp120. These interactions may induce the conformational changes in gp120 and lead to the final entry of HIV into the cell. These results not only strongly support the two-step gp120-CCR5 binding mechanism, but also rationalize extensive biological data about the role of CCR5 in HIV-1 gp120 binding and entry, and may guide efforts to design novel inhibitors.

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We investigated the transition energy levels of the vacancy defects in gallium nitride by means of a hybrid density functional theory approach (DFT). We show that, in contrast to predictions from a recent study on the level of purely local DFT, the inclusion of screened exchange stabilizes the triply positive charge state of the nitrogen vacancy for Fermi energies close to the valence band. On the other hand, the defect levels associated with the negative charge states of the nitrogen vacancy hybridize with the conduction band and turn out to be energetically unfavorable, except for high n-doping. For the gallium vacancy, the increased magnetic splitting between up-spin and down-spin bands due to stronger exchange interactions in sX-LDA pushes the defect levels deeper into the band gap and significantly increases the associated charge transition levels. Based on these results, we propose the ϵ(0| - 1) transition level as an alternative candidate for the yellow luminescence in GaN.

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Density functional calculations have been employed to investigate the locating and binding of lanthanum cation, i.e., La(OH)(2)(+), on HZSM-5 zeolite. Through geometry optimization, it was determined that lanthanum ions are favorably accommodated in the two 6-T rings of the straight channels (Clusters 1 and 2, see Sec. III A for details). Cluster 1 was found to exist in prior to Cluster 2 due to the preference of Al substitution in the T11 site (Cluster 1) rather than in the T8 site (Cluster 2). Geometry-optimization of Cluster 1 containing another two lanthanide ions Nd3+ and Yb3+ was also carried out and it was found that a monotonic decrease in Ln-O bond length will take place as the atomic number increases, conforming well to the rule of lanthanide contraction. Some of the optimized parameters are comparable to the corresponding experimental values in Y zeolite, which confirms that the optimized configurations are acceptable. The average frequencies of hydroxyls attached to La3+ or Yb3+ in Cluster 1 fall at 3609.16 and 3579.76 cm(-1), respectively, with the gap of these two frequencies close to that in the sodalite cage of Y zeolite. Compared to H-form zeolite, the charges on both Al and O atoms in Ln-ZSM-5 zeolite show an obvious increase, which will undoubtedly lead to a stronger mutual interaction and hence enhance the stability of the [AlO4](-) anion. Moreover, the Ln(OH)(2)(+) seem to have thickened the zeolite framework, which can effectively retard the process of dealumination. Through the evaluation of the possibility for dimer formation, it turned out that when the exchange degree arrived to approximately 0.28, lanthanum monomers began to aggregate into dimers, and were completely converted into dimers when the exchange degree approached 0.60. (C) 2003 American Institute of Physics.

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Linking organisms or groups of organisms to specific functions within natural environments is a fundamental challenge in microbial ecology. Advances in technology for manipulating and analyzing nucleic acids have made it possible to characterize the members of microbial communities without the intervention of laboratory culturing. Results from such studies have shown that the vast majority of soil organisms have never been cultured, highlighting the risks of culture-based approaches in community analysis. The development of culture-independent techniques for following the flow of substrates through microbial communities therefore represents an important advance. These techniques, collectively known as stable isotope probing (SIP), involve introducing a stable isotope-labeled substrate into a microbial community and following the fate of the substrate by extracting diagnostic molecular species such as fatty acids and nucleic acids from the community and determining which specific molecules have incorporated the isotope. The molecules in which the isotope label appears provide identifying information about the organism that incorporated the substrate. Stable isotope probing allows direct observations of substrate assimilation in minimally disturbed communities, and thus represents an exciting new tool for linking microbial identity and function. The use of lipids or nucleic acids as the diagnostic molecule brings different strengths and weaknesses to the experimental approach, and necessitates the use of significantly different instrumentation and analytical techniques. This short review provides an overview of the lipid and nucleic acid approaches, discusses their strengths and weaknesses, gives examples of applications in various settings, and looks at prospects for the future of SIP technology.