Search results for "Godi"

showing 10 items of 88 documents

A revision of the typification of some names in the seagrass genera Amphibolis, Cymodocea, Halodule and Syringodium (Cymodoceaceae)

2020

The typification of eight names of species currently included in the family Cymodoceaceae is revised in order to contribute to their nomenclatural stability. The previously designated lectotype of Ruppia antarctica Labill. (≡ Amphibolis antarctica (Labill.) Sond. & Asch.) is cited. Lectotypes are designated here for Zostera nodosa Ucria (≡ Cymodocea nodosa (Ucria) Asch.), Cymodocea rotundata Asch. & Schweinf., Caulinia serrulata R. Br. (≡ Cymodocea serrulata (R. Br.) Asch. & Magnus), Halodule bermudensis Hartog, Diplanthera pinifolia Miki (≡ H. pinifolia (Miki) Hartog) and Cymodocea isoetifolia Asch. (≡ Syringodium isoetifolium (Asch.) Dandy). A neotype is designated here for Z. uninervis F…

0106 biological sciencesRuppiabiologyCymodocea nodosaPlant ScienceHalodulebiology.organism_classification010603 evolutionary biology01 natural sciencesSyringodiumCymodoceaBotanyCymodoceaceaeTypificationAmphibolisEcology Evolution Behavior and Systematics010606 plant biology & botanyWilldenowia
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Conformational dynamics of a single protein monitored for 24 hours at video rate

2018

We use plasmon rulers to follow the conformational dynamics of a single protein for up to 24 h at a video rate. The plasmon ruler consists of two gold nanospheres connected by a single protein linker. In our experiment, we follow the dynamics of the molecular chaperone heat shock protein 90 (Hsp90), which is known to show “open” and “closed” conformations. Our measurements confirm the previously known conformational dynamics with transition times in the second to minute time scale and reveals new dynamics on the time scale of minutes to hours. Plasmon rulers thus extend the observation bandwidth 3–4 orders of magnitude with respect to single-molecule fluorescence resonance energy transfer a…

0301 basic medicineLetterProtein ConformationMolecular ConformationFOS: Physical sciencesHsp90Bioengineeringsingle molecule02 engineering and technology7. Clean energyQuantitative Biology - Quantitative Methods03 medical and health sciencesMolecular dynamicsFluorescence Resonance Energy TransferNanotechnologyGeneral Materials ScienceHSP90 Heat-Shock ProteinsPhysics - Biological PhysicsQuantitative Methods (q-bio.QM)PlasmonPhysicsVideo rateMechanical EngineeringProtein dynamics92Biomolecules (q-bio.BM)General ChemistrySurface Plasmon Resonance021001 nanoscience & nanotechnologyCondensed Matter PhysicsGold nanospheres030104 developmental biologyFörster resonance energy transferQuantitative Biology - BiomoleculesBiological Physics (physics.bio-ph)Chemical physicsFOS: Biological sciencesprotein dynamicsPlasmon rulernonergodicityGold0210 nano-technologyLinker
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Retrieving infinite numbers of patterns in a spin-glass model of immune networks

2013

The similarity between neural and immune networks has been known for decades, but so far we did not understand the mechanism that allows the immune system, unlike associative neural networks, to recall and execute a large number of memorized defense strategies {\em in parallel}. The explanation turns out to lie in the network topology. Neurons interact typically with a large number of other neurons, whereas interactions among lymphocytes in immune networks are very specific, and described by graphs with finite connectivity. In this paper we use replica techniques to solve a statistical mechanical immune network model with `coordinator branches' (T-cells) and `effector branches' (B-cells), a…

0301 basic medicineSimilarity (geometry)Spin glassComputer sciencestatistical mechanicFOS: Physical sciencesGeneral Physics and AstronomyNetwork topologyTopology01 natural sciencesQuantitative Biology::Cell Behavior03 medical and health sciencesCell Behavior (q-bio.CB)0103 physical sciencesattractor neural-networks; statistical mechanics; brain networks; Physics and Astronomy (all)Physics - Biological Physics010306 general physicsAssociative propertybrain networkArtificial neural networkMechanism (biology)ErgodicityDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksAcquired immune system030104 developmental biologyBiological Physics (physics.bio-ph)FOS: Biological sciencesattractor neural-networkQuantitative Biology - Cell Behavior
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SINDROME DOLOROSA REGIONALE COMPLESSA DEL POLSO: APPROCCIO TERAPEUTICO INTEGRATO E NUOVE PROSPETTIVE RIABILITATIVE

2008

ALGODISTROFIA
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Dynamic stability of plane elastic frames

1982

Abstract The stability of plane elastic frames subjected to a vertical foundation motion of the stationary, ergodic type is investigated. The equations of motion are obtained in modal co-ordinates, with account taken of many modes of vibration. The problem is subsequently reduced to the study of only the first mode of vibration. By considering a particular case, the stability domains are sketched as functions of the variation of the rigidities of the beam-column connecting joints and as functions of the number of stories.

Acoustics and UltrasonicsPlane (geometry)Mechanical EngineeringSTRUCTURAL ANALYSISMotion (geometry)Equations of motionSTRUCTURAL ANALYSIS; MATHEMATICAL MODELS; STRUCTURAL FRAMESSTRUCTURAL FRAMESCondensed Matter PhysicsStability (probability)VibrationClassical mechanicsModalMechanics of MaterialsNormal modeErgodic theoryMATHEMATICAL MODELSMathematicsJournal of Sound and Vibration
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Chaotic dynamics and partial hyperbolicity

2017

The dynamics of hyperbolic systems is considered well understood from topological point of view as well as from stochastic point of view. S. Smale and R. Abraham gave an example showing that, in general, the hyperbolic systems are not dense among all differentiable systems. In 1970s, M. Brin and Y. Pesin proposed a new notion: partial hyperbolicity to release the notion of hyperbolicity. One aim of this thesis is to understand the dynamics of certain partially hyperbolic systems from stochastic point of view as well as from topological point of view. From stochastic point of view, we prove the following results: — There exists an open and dense subset U of robustly transitive nonhyperbolic …

Anosov flowPeriodic measureMesure périodiqueExposant de LyapunovTores transversaux[MATH.MATH-GM] Mathematics [math]/General Mathematics [math.GM]Homoclinic classTwist de DehnPartial hyperbolicityDehn twistMesure ergodique non hyperboliqueFlot d’AnosovNon-hyperbolic ergodic measureTransitivité robusteClasse homocliniqueRobust transitivityTransverse torusHyperbolicité partielleLyapunov exponent
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Fractional master equations and fractal time random walks

1995

Fractional master equations containing fractional time derivatives of order 0\ensuremath{\le}1 are introduced on the basis of a recent classification of time generators in ergodic theory. It is shown that fractional master equations are contained as a special case within the traditional theory of continuous time random walks. The corresponding waiting time density \ensuremath{\psi}(t) is obtained exactly as \ensuremath{\psi}(t)=(${\mathit{t}}^{\mathrm{\ensuremath{\omega}}\mathrm{\ensuremath{-}}1}$/C)${\mathit{E}}_{\mathrm{\ensuremath{\omega}},\mathrm{\ensuremath{\omega}}}$(-${\mathit{t}}^{\mathrm{\ensuremath{\omega}}}$/C), where ${\mathit{E}}_{\mathrm{\ensuremath{\omega}},\mathrm{\ensuremat…

CombinatoricsDistribution (mathematics)FractalMaster equationErgodic theoryOrder (ring theory)Function (mathematics)Random walkOmegaMathematicsPhysical Review E
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Extensions of cocycles for hyperfinite actions and applications

1997

Given a countable, hyperfinite, ergodic and measure-preserving equivalence relationR on a standard probability space (X, ℬ, μ) and an elementW of the normalizerN (R) ofR, we investigate the problem of extendingR-cocycles to\(\bar R\), where\(\bar R\) is the relation generated byR andW. As an application, we obtain that for a Bernoulli automorphism the smallest family of natural factors in sense of [6] consists of all factors. Given an automorphism which is embeddable in a measurable flow and a compact, metric group, we show that for a typical cocycle we cannot lift the whole flow to the centralizer of the corresponding group extension.

CombinatoricsGroup extensionGeneral MathematicsErgodic theoryCountable setStandard probability spaceAutomorphismEquivalence (measure theory)Hyperfinite setCentralizer and normalizerMathematicsMonatshefte für Mathematik
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The case of equality in the dichotomy of Mohammadi–Oh

2019

If $n \geq 3$ and $\Gamma$ is a convex-cocompact Zariski-dense discrete subgroup of $\mathbf{SO}^o(1,n+1)$ such that $\delta_\Gamma=n-m$ where $m$ is an integer, $1 \leq m \leq n-1$, we show that for any $m$-dimensional subgroup $U$ in the horospheric group $N$, the Burger-Roblin measure associated to $\Gamma$ on the quotient of the frame bundle is $U$-recurrent.

CombinatoricsMathematics::Group TheoryIntegerDiscrete groupGroup (mathematics)Astrophysics::High Energy Astrophysical PhenomenaApplied MathematicsErgodicityGeometry and TopologyMeasure (mathematics)Frame bundleQuotientMathematicsJournal of Fractal Geometry
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Determining a Random Schrödinger Operator : Both Potential and Source are Random

2020

We study an inverse scattering problem associated with a Schr\"odinger system where both the potential and source terms are random and unknown. The well-posedness of the forward scattering problem is first established in a proper sense. We then derive two unique recovery results in determining the rough strengths of the random source and the random potential, by using the corresponding far-field data. The first recovery result shows that a single realization of the passive scattering measurements uniquely recovers the rough strength of the random source. The second one shows that, by a single realization of the backscattering data, the rough strength of the random potential can be recovered…

Complex systemMicrolocal analysis01 natural sciencesinversio-ongelmatsähkömagneettinen säteilysymbols.namesakeOperator (computer programming)Mathematics - Analysis of PDEs0103 physical sciencessironta0101 mathematicsMathematical PhysicsMathematics35Q60 35J05 31B10 35R30 78A40osittaisdifferentiaaliyhtälötScattering010102 general mathematicsMathematical analysisErgodicityStatistical and Nonlinear PhysicsInverse scattering problemsymbols010307 mathematical physicsmatemaattiset mallitRealization (probability)Schrödinger's cat
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