Search results for "Quantitative Biology"

showing 10 items of 1025 documents

"Figure 5-3" of "Transverse momentum dependence of meson suppression in Au+Au collisions at sqrt(s_NN) = 200 GeV"

2021

Slope ${\eta}$ $R_{AA}$ ($5

Quantitative Biology::Biomoleculesmid-rapidityAstrophysics::Instrumentation and Methods for Astrophysicsppg115transverse momentumNuclear ExperimentetaComputer Science::Digital LibrariesQuantitative Biology::Other200AU AU --> ETA X
researchProduct

A Monte Carlo Study of Knots in Long Double-Stranded DNA Chains.

2016

We determine knotting probabilities and typical sizes of knots in double-stranded DNA for chains of up to half a million base pairs with computer simulations of a coarse-grained bead-stick model: Single trefoil knots and composite knots which include at least one trefoil as a prime factor are shown to be common in DNA chains exceeding 250,000 base pairs, assuming physiologically relevant salt conditions. The analysis is motivated by the emergence of DNA nanopore sequencing technology, as knots are a potential cause of erroneous nucleotide reads in nanopore sequencing devices and may severely limit read lengths in the foreseeable future. Even though our coarse-grained model is only based on …

Quantitative Biology::Biomoleculessurgical procedures operativestomatognathic systemlcsh:Biology (General)530 Physicsfood and beverages530 PhysikMathematics::Geometric Topologylcsh:QH301-705.5PLoS Computational Biology
researchProduct

Artificial Neural Networks for Prediction

2005

The design and implementation of intelligent systems with human capabilities is the starting point to design Artificial Neural Networks (ANNs). The original idea takes after neuroscience theory on how neurons in the human brain cooperate to learn from a set of input signals to produce an answer. Because the power of the brain comes from the number of neurons and the multiple connections between them, the basic idea is that connecting a large number of simple elements in a specific way can form an intelligent system.

Quantitative Biology::Neurons and CognitionArtificial neural networkComputer sciencebusiness.industryGenetic algorithmArtificial intelligencebusiness
researchProduct

An Application of Spike-Timing-Dependent Plasticity to Readout Circuit for Liquid State Machine

2007

Liquid state machine (LSM) is a neural system based on spiking neurons that implements a mapping between functions of time. A typical application of LSM is classification of time functions obtained observing the state of the liquid by using a memoryless readout circuit, usually implemented by a linear perceptron. Due to the high number of neurons in the liquid the training of the readout is difficult. In this paper we show that using the Spike-Timing-Dependent Plasticity (STDP) a single neuron with short training session can be used to recognize the state of the liquid due to an input signal. Using STDP it is possible to identify the spikes timing of the neurons in the liquid and this allow…

Quantitative Biology::Neurons and CognitionArtificial neural networkSpike-timing-dependent plasticitybusiness.industryComputer scienceLiquid state machineNoise (signal processing)PerceptronSignalmedicine.anatomical_structureSPike neural netwroksmedicineArtificial intelligenceNeuronState (computer science)businessAlgorithm
researchProduct

Experimental study of bifurcations in modified FitzHugh-Nagumo cell

2003

A nonlinear electrical circuit is proposed as a basic cell for modelling the FitzHugh-Nagumo equation with a modified excitability. Depending on initial conditions and parameters, experiments show various dynamics including stability with excitation threshold, bistability and oscillations.

Quantitative Biology::Neurons and CognitionBistabilityDynamics (mechanics)Fitzhugh nagumoStability (probability)law.inventionNonlinear systemClassical mechanicsControl theorylawElectrical networkElectrical and Electronic EngineeringExcitationMathematicsElectronics Letters
researchProduct

Electronic structure, lattice dynamics and thermodynamic stability of paramelaconite Cu4O3

2014

Abstract An ab initio study of the electronic structure, lattice dynamic and thermodynamic properties of paramelaconite Cu 4 O 3 is reported. The insulating, mixed-valence character of Cu 4 O 3 is elucidated by analyzing the band structure and the spin-orbital symmetry of the Cu-3 d hole states. Exchange coupling constants between Cu 2+ ions are computed which confirm the frustrated antiferromagnetism of the spin lattice. The lattice dynamics is studied from first principles and main features of the vibrational spectrum are assigned to the different chemical species Cu + , Cu 2+ and O. The thermodynamic stability of Cu 4 O 3 is investigated by calculating the free energy of the decompositio…

Quantitative Biology::Neurons and CognitionChemistryAb initioThermodynamicsEmpty lattice approximationElectronic structureParamelaconiteengineering.materialCondensed Matter PhysicsAb initio quantum chemistry methodsengineeringPhysical chemistryAntiferromagnetismCondensed Matter::Strongly Correlated ElectronsGeneral Materials ScienceChemical stabilityElectronic band structureMaterials Chemistry and Physics
researchProduct

Generation of stimulus features for analysis of FMRI during natural auditory experiences

2014

In contrast to block and event-related designs for fMRI experiments, it becomes much more difficult to extract events of interest in the complex continuous stimulus for finding corresponding blood-oxygen-level dependent (BOLD) responses. Recently, in a free music listening fMRI experiment, acoustic features of the naturalistic music stimulus were first extracted, and then principal component analysis (PCA) was applied to select the features of interest acting as the stimulus sequences. For feature generation, kernel PCA has shown its superiority over PCA in various applications, since it can implicitly exploit nonlinear relationship among features and such relationship seems to exist genera…

Quantitative Biology::Neurons and CognitionComputer Science::Soundsignaalinkäsittelyfeature extractionfMRIkernel PCAkokeet (tutkimustoiminta)riippumattomien komponenttien analyysiICAPolynomial kernelnaturalistic music
researchProduct

"Table 4" of "Lowest Q**2 measurement of the gamma* p --> delta reaction: Probing the pionic contribution."

2006

Measured value of SIG(C=LTP) as a function of the pion angle relative to the virtual photon direction.

Quantitative Biology::Neurons and CognitionElectron productionQuantitative Biology::Molecular NetworksNuclear TheoryIntegrated Cross SectionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONCross SectionSIG7.950E-017.950E-01E- P --> E- PI0 PExclusiveNuclear Experiment1.221ComputingMethodologies_COMPUTERGRAPHICSComputer Science::Cryptography and Security
researchProduct

Periodic orbits of single neuron models with internal decay rate 0 < β ≤ 1

2013

In this paper we consider a discrete dynamical system x n+1=βx n – g(x n ), n=0,1,..., arising as a discrete-time network of a single neuron, where 0 &lt; β ≤ 1 is an internal decay rate, g is a signal function. A great deal of work has been done when the signal function is a sigmoid function. However, a signal function of McCulloch-Pitts nonlinearity described with a piecewise constant function is also useful in the modelling of neural networks. We investigate a more complicated step signal function (function that is similar to the sigmoid function) and we will prove some results about the periodicity of solutions of the considered difference equation. These results show the complexity of …

Quantitative Biology::Neurons and CognitionMathematical analysisActivation functionSigmoid functionstabilitySingle-valued functiondynamical systemError functionsymbols.namesakefixed pointModeling and SimulationMittag-Leffler functionStep functioniterative processsymbolsPiecewiseQA1-939nonlinear problemConstant functionAnalysisMathematicsMathematicsMathematical Modelling and Analysis
researchProduct

Transition densities for stochastic Hodgkin-Huxley models

2012

We consider a stochastic Hodgkin-Huxley model driven by a periodic signal as model for the membrane potential of a pyramidal neuron. The associated five dimensional diffusion process is a time inhomogeneous highly degenerate diffusion for which the weak Hoermander condition holds only locally. Using a technique which is based on estimates of the Fourier transform, inspired by Fournier 2008, Bally 2007 and De Marco 2011, we show that the process admits locally a strictly positive continuous transition density. Moreover, we show that the presence of noise enables the stochastic system to imitate any possible deterministic spiking behavior, i.e. mixtures of regularly spiking and non-spiking ti…

Quantitative Biology::Neurons and CognitionProbability (math.PR)FOS: Mathematics60 J 60Mathematics - Probability
researchProduct