959 resultados para Fuzzy K Nearest Neighbor


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Yeast and vertebrate nuclear pores display significant morphological similarity by electron microscopy, but sequence similarity between the respective proteins has been more difficult to observe. Herein we have identified a vertebrate nucleoporin, Nup93, in both human and Xenopus that has proved to be an evolutionarily related homologue of the yeast nucleoporin Nic96p. Polyclonal antiserum to human Nup93 detects corresponding proteins in human, rat, and Xenopus cells. Immunofluorescence and immunoelectron microscopy localize vertebrate Nup93 at the nuclear basket and at or near the nuclear entry to the gated channel of the pore. Immunoprecipitation from both mammalian and Xenopus cell extracts indicates that a small fraction of Nup93 physically interacts with the nucleoporin p62, just as yeast Nic96p interacts with the yeast p62 homologue. However, a large fraction of vertebrate Nup93 is extracted from pores and is also present in Xenopus egg extracts in complex with a newly discovered 205-kDa protein. Mass spectrometric sequencing of the human 205-kDa protein reveals that this protein is encoded by an open reading frame, KIAAO225, present in the human database. The putative human nucleoporin of 205 kDa has related sequence homologues in Caenorhabditis elegans and Saccharomyces cerevisiae. To analyze the role of the Nup93 complex in the pore, nuclei were assembled that lack the Nup93 complex after immunodepletion of a Xenopus nuclear reconstitution extract. The Nup93-complex–depleted nuclei are clearly defective for correct nuclear pore assembly. From these experiments, we conclude that the vertebrate and yeast pore have significant homology in their functionally important cores and that, with the identification of Nup93 and the 205-kDa protein, we have extended the knowledge of the nearest-neighbor interactions of this core in both yeast and vertebrates.

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Current evidence indicates that methylation of cytosine in mammalian DNA is restricted to both strands of the symmetrical sequence CpG, although there have been sporadic reports that sequences other than CpG may also be methylated. We have used a dual-labeling nearest neighbor technique and bisulphite genomic sequencing methods to investigate the nearest neighbors of 5-methylcytosine residues in mammalian DNA. We find that embryonic stem cells, but not somatic tissues, have significant cytosine-5 methylation at CpA and, to a lesser extent, at CpT. As the expression of the de novo methyltransferase Dnmt3a correlates well with the presence of non-CpG methylation, we asked whether Dnmt3a might be responsible for this modification. Analysis of genomic methylation in transgenic Drosophila expressing Dnmt3a reveals that Dnmt3a is predominantly a CpG methylase but also is able to induce methylation at CpA and at CpT.

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We present rules that allow one to predict the stability of DNA pyrimidine.purine.pyrimidine (Y.R.Y) triple helices on the basis of the sequence. The rules were derived from van't Hoff analysis of 23 oligonucleotide triplexes tested at a variety of pH values. To predict the enthalpy of triplex formation (delta H degrees), a simple nearest-neighbor model was found to be sufficient. However, to accurately predict the free energy of the triplex (delta G degrees), a combination model consisting of five parameters was needed. These parameters were (i) the delta G degrees for helix initiation, (ii) the delta G degrees for adding a T-A.T triple, (iii) the delta G degrees for adding a C(+)-G.C triple, (iv) the penalty for adjacent C bases, and (v) the pH dependence of the C(+)-G.C triple's stability. The fitted parameters are highly consistent with thermodynamic data from the basis set, generally predicting both delta H degrees and delta G degrees to within the experimental error. Examination of the parameters points out several interesting features. The combination model predicts that C(+) -G.C. triples are much more stabilizing than T-A.T triples below pH 7.0 and that the stability of the former increases approximately equal to 1 kcal/mol per pH unit as the pH is decreased. Surprisingly though, the most stable sequence is predicted to be a CT repeat, as adjacent C bases partially cancel the stability of one another. The parameters successfully predict tm values from other laboratories, with some interesting exceptions.

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Structurally neighboring residues are categorized according to their separation in the primary sequence as proximal (1-4 positions apart) and otherwise distal, which in turn is divided into near (5-20 positions), far (21-50 positions), very far ( > 50 positions), and interchain (from different chains of the same structure). These categories describe the linear distance histogram (LDH) for three-dimensional neighboring residue types. Among the main results are the following: (i) nearest-neighbor hydrophobic residues tend to be increasingly distally separated in the linear sequence, thus most often connecting distinct secondary structure units. (ii) The LDHs of oppositely charged nearest-neighbors emphasize proximal positions with a subsidiary maximum for very far positions. (iii) Cysteine-cysteine structural interactions rarely involve proximal positions. (iv) The greatest numbers of interchain specific nearest-neighbors in protein structures are composed of oppositely charged residues. (v) The largest fraction of side-chain neighboring residues from beta-strands involves near positions, emphasizing associations between consecutive strands. (vi) Exposed residue pairs are predominantly located in proximal linear positions, while buried residue pairs principally correspond to far or very far distal positions. The results are principally invariant to protein sizes, amino acid usages, linear distance normalizations, and over- and underrepresentations among nearest-neighbor types. Interpretations and hypotheses concerning the LDHs, particularly those of hydrophobic and charged pairings, are discussed with respect to protein stability and functionality. The pronounced occurrence of oppositely charged interchain contacts is consistent with many observations on protein complexes where multichain stabilization is facilitated by electrostatic interactions.

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As a measure of dynamical structure, short-term fluctuations of coherence between 0.3 and 100 Hz in the electroencephalogram (EEG) of humans were studied from recordings made by chronic subdural macroelectrodes 5-10 mm apart, on temporal, frontal, and parietal lobes, and from intracranial probes deep in the temporal lobe, including the hippocampus, during sleep, alert, and seizure states. The time series of coherence between adjacent sites calculated every second or less often varies widely in stability over time; sometimes it is stable for half a minute or more. Within 2-min samples, coherence commonly fluctuates by a factor up to 2-3, in all bands, within the time scale of seconds to tens of seconds. The power spectrum of the time series of these fluctuations is broad, extending to 0.02 Hz or slower, and is weighted toward the slower frequencies; little power is faster than 0.5 Hz. Some records show conspicuous swings with a preferred duration of 5-15s, either irregularly or quasirhythmically with a broad peak around 0.1 Hz. Periodicity is not statistically significant in most records. In our sampling, we have not found a consistent difference between lobes of the brain, subdural and depth electrodes, or sleeping and waking states. Seizures generally raise the mean coherence in all frequencies and may reduce the fluctuations by a ceiling effect. The coherence time series of different bands is positively correlated (0.45 overall); significant nonindependence extends for at least two octaves. Coherence fluctuations are quite local; the time series of adjacent electrodes is correlated with that of the nearest neighbor pairs (10 mm) to a coefficient averaging approximately 0.4, falling to approximately 0.2 for neighbors-but-one (20 mm) and to < 0.1 for neighbors-but-two (30 mm). The evidence indicates fine structure in time and space, a dynamic and local determination of this measure of cooperativity. Widely separated frequencies tending to fluctuate together exclude independent oscillators as the general or usual basis of the EEG, although a few rhythms are well known under special conditions. Broad-band events may be the more usual generators. Loci only a few millimeters apart can fluctuate widely in seconds, either in parallel or independently. Scalp EEG coherence cannot be predicted from subdural or deep recordings, or vice versa, and intracortical microelectrodes show still greater coherence fluctuation in space and time. Widely used computations of chaos and dimensionality made upon data from scalp or even subdural or depth electrodes, even when reproducible in successive samples, cannot be considered representative of the brain or the given structure or brain state but only of the scale or view (receptive field) of the electrodes used. Relevant to the evolution of more complex brains, which is an outstanding fact of animal evolution, we believe that measures of cooperativity are likely to be among the dynamic features by which major evolutionary grades of brains differ.

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In the last decades, an increasing interest in the research field of wide bandgap semiconductors was observed, mostly due to the progressive approaching of silicon-based devices to their theoretical limits. 4H-SiC is an example among these, and is a mature compound for applications. The main advantages offered 4H-SiC in comparison with silicon are an higher breakdown field, an higher thermal conductivity, a higher operating temperature, very high hardness and melting point, biocompatibility, but also low switching losses in high frequencies applications and lower on-resistances in unipolar devices. Then, 4H-SiC power devices offer great performance improvement; moreover, they can work in hostile environments where silicon power devices cannot function. Ion implantation technology is a key process in the fabrication of almost all kinds of SiC devices, owing to the advantage of a spatially selective doping. This work is dedicated to the electrical investigation of several differently-processed 4H-SiC ion- implanted samples, mainly through Hall effect and space charge spectroscopy experiments. It was also developed the automatic control (Labview) of several experiments. In the work, the effectiveness of high temperature post-implant thermal treatments (up to 2000°C) were studied and compared considering: (i) different methods, (ii) different temperatures and (iii) different duration of the annealing process. Preliminary p + /n and Schottky junctions were also investigated as simple test devices. 1) Heavy doping by ion implantation of single off-axis 4H-SiC layers The electrical investigation is one of the most important characterization of ion-implanted samples, which must be submitted to mandatory post-implant thermal treatment in order to both (i) recover the lattice after ion bombardment, and (ii) address the implanted impurities into lattice sites so that they can effectively act as dopants. Electrical investigation can give fundamental information on the efficiency of the electrical impurity activation. To understand the results of the research it should be noted that: (a) To realize good ohmic contacts it is necessary to obtain spatially defined highly doped regions, which must have conductivity as low as possible. (b) It has been shown that the electrical activation efficiency and the electrical conductivity increase with the annealing temperature increasing. (c) To maximize the layer conductivity, temperatures around 1700°C are generally used and implantation density high till to 10 21 cm -3 . In this work, an original approach, different from (c), is explored by the using very high annealing temperature, around 2000°C, on samples of Al + -implant concentration of the order of 10 20 cm -3 . Several Al + -implanted 4H-SiC samples, resulting of p-type conductivity, were investigated, with a nominal density varying in the range of about 1-5∙10 20 cm -3 and subjected to two different high temperature thermal treatments. One annealing method uses a radiofrequency heated furnace till to 1950°C (Conventional Annealing, CA), the other exploits a microwave field, providing a fast heating rate up to 2000°C (Micro-Wave Annealing, MWA). In this contest, mainly ion implanted p-type samples were investigated, both off-axis and on-axis <0001> semi-insulating 4H-SiC. Concerning p-type off-axis samples, a high electrical activation of implanted Al (50-70%) and a compensation ratio below 10% were estimated. In the work, the main sample processing parameters have been varied, as the implant temperature, CA annealing duration, and heating/cooling rates, and the best values assessed. MWA method leads to higher hole density and lower mobility than CA in equivalent ion implanted layers, resulting in lower resistivity, probably related to the 50°C higher annealing temperature. An optimal duration of the CA treatment was estimated in about 12-13 minutes. A RT resistivity on the lowest reported in literature for this kind of samples, has been obtained. 2) Low resistivity data: variable range hopping Notwithstanding the heavy p-type doping levels, the carrier density remained less than the critical one required for a semiconductor to metal transition. However, the high carrier densities obtained was enough to trigger a low temperature impurity band (IB) conduction. In the heaviest doped samples, such a conduction mechanism persists till to RT, without significantly prejudice the mobility values. This feature can have an interesting technological fall, because it guarantee a nearly temperature- independent carrier density, it being not affected by freeze-out effects. The usual transport mechanism occurring in the IB conduction is the nearest neighbor hopping: such a regime is effectively consistent with the resistivity temperature behavior of the lowest doped samples. In the heavier doped samples, however, a trend of the resistivity data compatible with a variable range hopping (VRH) conduction has been pointed out, here highlighted for the first time in p-type 4H-SiC. Even more: in the heaviest doped samples, and in particular, in those annealed by MWA, the temperature dependence of the resistivity data is consistent with a reduced dimensionality (2D) of the VRH conduction. In these samples, TEM investigation pointed out faulted dislocation loops in the basal plane, whose average spacing along the c-axis is comparable with the optimal length of the hops in the VRH transport. This result suggested the assignment of such a peculiar behavior to a kind of spatial confinement into a plane of the carrier hops. 3) Test device the p + -n junction In the last part of the work, the electrical properties of 4H-SiC diodes were also studied. In this case, a heavy Al + ion implantation was realized on n-type epilayers, according to the technological process applied for final devices. Good rectification properties was shown from these preliminary devices in their current-voltage characteristics. Admittance spectroscopy and deep level transient spectroscopy measurements showed the presence of electrically active defects other than the dopants ones, induced in the active region of the diodes by ion implantation. A critical comparison with the literature of these defects was performed. Preliminary to such an investigation, it was assessed the experimental set up for the admittance spectroscopy and current-voltage investigation and the automatic control of these measurements.

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This paper describes JANUS, a modular massively parallel and reconfigurable FPGA-based computing system. Each JANUS module has a computational core and a host. The computational core is a 4x4 array of FPGA-based processing elements with nearest-neighbor data links. Processors are also directly connected to an I/O node attached to the JANUS host, a conventional PC. JANUS is tailored for, but not limited to, the requirements of a class of hard scientific applications characterized by regular code structure, unconventional data manipulation instructions and not too large data-base size. We discuss the architecture of this configurable machine, and focus on its use on Monte Carlo simulations of statistical mechanics. On this class of application JANUS achieves impressive performances: in some cases one JANUS processing element outperfoms high-end PCs by a factor ≈1000. We also discuss the role of JANUS on other classes of scientific applications.

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We propose a realistic scheme to quantum simulate the so-far experimentally unobserved topological Mott insulator phase-an interaction-driven topological insulator-using cold atoms in an optical Lieb lattice. To this end, we study a system of spinless fermions in a Lieb lattice, exhibiting repulsive nearest-and next-to-nearest-neighbor interactions and derive the associated zero-temperature phase diagram within mean-field approximation. In particular, we analyze how the interactions can dynamically generate a charge density wave ordered, a nematic, and a topologically nontrivial quantum anomalous Hall phase. We characterize the topology of the different phases by the Chern number and discuss the possibility of phase coexistence. Based on the identified phases, we propose a realistic implementation of this model using cold Rydberg-dressed atoms in an optical lattice. The scheme, which allows one to access, in particular, the topological Mott insulator phase, robustly and independently of its exact position in parameter space, merely requires global, always-on off-resonant laser coupling to Rydberg states and is feasible with state-of-the-art experimental techniques that have already been demonstrated in the laboratory.

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In the current Information Age, data production and processing demands are ever increasing. This has motivated the appearance of large-scale distributed information. This phenomenon also applies to Pattern Recognition so that classic and common algorithms, such as the k-Nearest Neighbour, are unable to be used. To improve the efficiency of this classifier, Prototype Selection (PS) strategies can be used. Nevertheless, current PS algorithms were not designed to deal with distributed data, and their performance is therefore unknown under these conditions. This work is devoted to carrying out an experimental study on a simulated framework in which PS strategies can be compared under classical conditions as well as those expected in distributed scenarios. Our results report a general behaviour that is degraded as conditions approach to more realistic scenarios. However, our experiments also show that some methods are able to achieve a fairly similar performance to that of the non-distributed scenario. Thus, although there is a clear need for developing specific PS methodologies and algorithms for tackling these situations, those that reported a higher robustness against such conditions may be good candidates from which to start.

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The dynamical properties of an extended Hubbard model, which is relevant to quarter-filled layered organic molecular crystals, are analyzed. We have computed the dynamical charge correlation function, spectral density, and optical conductivity using Lanczos diagonalization and large-N techniques. As the ratio of the nearest-neighbor Coulomb repulsion, V, to the hopping integral, t, increases there is a transition from a metallic phase to a charge-ordered phase. Dynamical properties close to the ordering transition are found to differ from the ones expected in a conventional metal. Large-N calculations display an enhancement of spectral weight at low frequencies as the system is driven closer to the charge-ordering transition in agreement with Lanczos calculations. As V is increased the charge correlation function displays a collective mode which, for wave vectors close to (pi,pi), increases in amplitude and softens as the charge-ordering transition is approached. We propose that inelastic x-ray scattering be used to detect this mode. Large-N calculations predict superconductivity with d(xy) symmetry close to the ordering transition. We find that this is consistent with Lanczos diagonalization calculations, on lattices of 20 sites, which find that the binding energy of two holes becomes negative close to the charge-ordering transition.

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Different amorphous structures have been induced in monocrystalline silicon by high pressure in indentation and polishing. Through the use of high-resolution transmission electron microscopy and nanodiffraction, it was found that the structures of amorphous silicon formed at slow and fast loading/unloading rates are dissimilar and inherit the nearest-neighbor distance of the crystal in which they are formed. The results are in good agreement with recent theoretical predictions. (C) 2004 American Institute of Physics.

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We present a technique to identify exact analytic expressions for the multiquantum eigenstates of a linear chain of coupled qubits. A choice of Hilbert subspaces is described that allows an exact solution of the stationary Schrodinger equation without imposing periodic boundary conditions and without neglecting end effects, fully including the dipole-dipole nearest-neighbor interaction between the atoms. The treatment is valid for an arbitrary coherent excitation in the atomic system, any number of atoms, any size of the chain relative to the resonant wavelength and arbitrary initial conditions of the atomic system. The procedure we develop is general enough to be adopted for the study of excitation in an arbitrary array of atoms including spin chains and one-dimensional Bose-Einstein condensates.

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The effect of antiferromagnetic spin fluctuations on two-dimensional quarter-filled systems is studied theoretically. An effective t-J(')-V model on a square lattice which accounts for checkerboard charge fluctuations and next-nearest-neighbor antiferromagnetic spin fluctuations is considered. From calculations based on large-N theory on this model it is found that the exchange interaction J(') increases the attraction between electrons in the d(xy) channel only, so that both charge and spin fluctuations work cooperatively to produce d(xy) pairing.

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beta-turns are important topological motifs for biological recognition of proteins and peptides. Organic molecules that sample the side chain positions of beta-turns have shown broad binding capacity to multiple different receptors, for example benzodiazepines. beta-turns have traditionally been classified into various types based on the backbone dihedral angles (phi 2, psi 2, phi 3 and psi 3). Indeed, 57-68% of beta-turns are currently classified into 8 different backbone families (Type I, Type II, Type I', Type II', Type VIII, Type VIa1, Type VIa2 and Type VIb and Type IV which represents unclassified beta-turns). Although this classification of beta-turns has been useful, the resulting beta-turn types are not ideal for the design of beta-turn mimetics as they do not reflect topological features of the recognition elements, the side chains. To overcome this, we have extracted beta-turns from a data set of non-homologous and high-resolution protein crystal structures. The side chain positions, as defined by C-alpha-C-beta vectors, of these turns have been clustered using the kth nearest neighbor clustering and filtered nearest centroid sorting algorithms. Nine clusters were obtained that cluster 90% of the data, and the average intra-cluster RMSD of the four C-alpha-C-beta vectors is 0.36. The nine clusters therefore represent the topology of the side chain scaffold architecture of the vast majority of beta-turns. The mean structures of the nine clusters are useful for the development of beta-turn mimetics and as biological descriptors for focusing combinatorial chemistry towards biologically relevant topological space.

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A structurally based viscosity model for fully liquid silicate slags has been proposed and applied to the Al2O3-CaO-'FeO'-SiO2 system at metallic iron saturation. The model links the slag viscosity to the internal structure of melts through the concentrations of various anion/cation structural units (SUs). The concentrations of structural units are equivalent to the second nearest neighbor bond concentrations calculated by the quasi-chemical thermodynamic model. This viscosity model describes experimental data over the entire temperature and composition range within the Al2O3-CaO-'FeO'-SiO2 system at metallic iron saturation and can be extended to other industrial slag systems.