Search results for "Vector"

showing 10 items of 2660 documents

Adenoviral RB2/p130 gene transfer inhibits smooth muscle cell proliferation and prevents restenosis after angioplasty.

1999

Abstract —Smooth muscle cell (SMC) proliferation that results in neointima formation is implicated in the pathogenesis of atherosclerotic plaques and accounts for the high rates of restenosis that occur after percutaneous transluminal coronary angioplasty, a widespread treatment for coronary artery disease. Endothelial lesions trigger intense proliferative signals to the SMCs of the subintima, stimulating their reentry into the cell cycle from a resting G 0 state, resulting in neointima formation and vascular occlusion. Cellular proliferation is negatively controlled by growth-regulatory or tumor-suppressor genes, or both, such as the retinoblastoma gene family members ( RB/p105, p107, RB2…

NeointimaTranscriptional Activationmedicine.medical_specialtyPhysiologyadenovirus; cell cycle; gene therapy; p130; prb2; restenosisCellGenetic VectorsCell Cycle ProteinsPulmonary ArteryMuscle Smooth VascularAdenoviridaeCatheterizationPathogenesisRestenosisRecurrencemedicineAnimalsCarotid StenosisAngioplasty Balloon CoronaryGenes RetinoblastomaCells CulturedNeointimal hyperplasiaWound HealingRetinoblastoma-Like Protein p130business.industryCell growthGenetic transferCell CycleProteinsGenetic TherapyCell cyclemedicine.diseasePhosphoproteinsSurgeryE2F Transcription FactorsRatsDNA-Binding Proteinsmedicine.anatomical_structureCancer researchCardiology and Cardiovascular MedicinebusinessCarotid Artery InjuriesCarrier ProteinsTunica IntimaTranscription Factor DP1Cell DivisionRetinoblastoma-Binding Protein 1Transcription FactorsCirculation research
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What Could Be a Primary Cause of Multiple Sclerosis: Is It an Autoimmunity Triggered by Chronic Protozoan Infection?

2013

The generally accepted paradigm of multiple sclerosis is the autoimmune one; still, a body of evidence suggests that this disease may actually be triggered by an infectious factor. In this paper, it is hypothesized that multiple sclerosis may actually be a rare complication of a protozoan infection, which is usually asymptomatic but in some susceptible individuals is accompanied by autoimmune attack against the nervous tissue. If multiple sclerosis were actually caused by such an infection, then a microorganism responsible should exhibit several properties: it (i) is transmitted by an arthropod vector; (ii) is characterized by specific metabolism of the lipids; (iii) should be dependent on …

Nervous tissueMultiple sclerosisUsually asymptomaticDiseaseBiologymedicine.diseasemedicine.disease_causeAutoimmunitymedicine.anatomical_structureProtozoan infectionImmunologymedicineComplicationArthropod VectorJournal of Neuroparasitology
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Fault-Tolerant Application Mapping on to ZMesh topology based Network-on-Chip Design

2020

This paper proposes Particle Swarm Optimization (PSO) based fault-tolerant application mapping on to ZMesh topology based Network-on-Chip (NoC) design. Permanent faults in application cores has been considered and performed application mapping using PSO. The major contribution of this paper is to find out the best position for the spare core to be placed in the network using PSO. Experimentations have been carried out by scaling the ZMesh network size and percentage of network faults. The results show that the proposed approach leads to minimum overhead in communication cost over fault-free result.

Network on a chipComputer sciencePosition (vector)020204 information systems0202 electrical engineering electronic engineering information engineeringOverhead (computing)Particle swarm optimizationFault toleranceTopology (electrical circuits)Hardware_PERFORMANCEANDRELIABILITY02 engineering and technologyTopology020202 computer hardware & architecture2020 15th IEEE Conference on Industrial Electronics and Applications (ICIEA)
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Massive Lesions Classification using Features based on Morphological Lesion Differences

2007

Purpose of this work is the development of an automatic classification system which could be useful for radiologists in the investigation of breast cancer. The software has been designed in the framework of the MAGIC-5 collaboration. In the automatic classification system the suspicious regions with high probability to include a lesion are extracted from the image as regions of interest (ROIs). Each ROI is characterized by some features based on morphological lesion differences. Some classifiers as a Feed Forward Neural Network, a K-Nearest Neighbours and a Support Vector Machine are used to distinguish the pathological records from the healthy ones. The results obtained in terms of sensiti…

Neural Networks; K-Nearest Neighbours; Support Vector Machine; Computer Aided DiagnosisSupport Vector MachineSupportVector MachineNeural NetworksComputer Aided DiagnosisK-Nearest NeighboursNeural Networks K-Nearest Neighbours Support Vector Machine Computer Aided Diagnosis.Computer Aided Diagnosis.
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Some experimental issues of AFM tip blind estimation. The effect of noise and resolution

2006

The convolution of tip shape on sample topography can introduce significant inaccuracy in an AFM image, when the tip radius is comparable to the typical dimension of the sample features to be observed. The blind estimation method allows one to obtain information on the AFM tip through an unknown characterizer sample and thus to perform the deconvolution of the tip shape from an image. When applying the blind estimation method to determine the AFM tip shape, some apparently trivial issues relating to the experimental operating parameters must be taken into account. In this paper, the effects of the operating parameters, e.g., sampling intervals (resolution) and instrumental noise, have been …

Noise (signal processing)Applied MathematicsAcousticsResolution (electron density)Sampling (statistics)atomic force microscopy tip characterization blind estimationRadiusSample (graphics)ConvolutionDimension (vector space)StatisticsDeconvolutionInstrumentationEngineering (miscellaneous)Mathematics
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High-quality discretizations for microwave simulations

2016

We apply high-quality discretizations to simulate electromagnetic microwaves. Instead of the vector field presentations, we focus on differential forms and discretize the model in the spatial domain using the discrete exterior calculus. At the discrete level, both the Hodge operators and the time discretization are optimized for time-harmonic simulations. Non-uniform spatial and temporal discretization are applied in problems in which the wavelength is highly-variable and geometry contains sub-wavelength structures. peerReviewed

Noise measurementDiscretizationDifferential formMathematical analysisFinite difference methodnoise measurement010103 numerical & computational mathematicsmagnetic domainstime-domain analysis01 natural sciencesDiscrete exterior calculusVector field0101 mathematicsTemporal discretizationmicrowave theory and techniquesFocus (optics)finite difference methodskasvotMathematics2016 URSI International Symposium on Electromagnetic Theory (EMTS)
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Signal-to-noise ratio in reproducing kernel Hilbert spaces

2018

This paper introduces the kernel signal-to-noise ratio (kSNR) for different machine learning and signal processing applications}. The kSNR seeks to maximize the signal variance while minimizing the estimated noise variance explicitly in a reproducing kernel Hilbert space (rkHs). The kSNR gives rise to considering complex signal-to-noise relations beyond additive noise models, and can be seen as a useful signal-to-noise regularizer for feature extraction and dimensionality reduction. We show that the kSNR generalizes kernel PCA (and other spectral dimensionality reduction methods), least squares SVM, and kernel ridge regression to deal with cases where signal and noise cannot be assumed inde…

Noise model02 engineering and technologySNR010501 environmental sciences01 natural sciencesKernel principal component analysisSenyal Teoria del (Telecomunicació)Signal-to-noise ratioArtificial Intelligence0202 electrical engineering electronic engineering information engineeringHeteroscedastic0105 earth and related environmental sciencesMathematicsNoise (signal processing)Dimensionality reductionKernel methodsSignal classificationSupport vector machineKernel methodKernel (statistics)Anàlisi funcionalSignal ProcessingFeature extraction020201 artificial intelligence & image processingSignal-to-noise ratioComputer Vision and Pattern RecognitionAlgorithmSoftwareImatges ProcessamentReproducing kernel Hilbert spaceCausal inference
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Real-Time Vector Automata

2013

We study the computational power of real-time finite automata that have been augmented with a vector of dimension k, and programmed to multiply this vector at each step by an appropriately selected k×k matrix. Only one entry of the vector can be tested for equality to 1 at any time. Classes of languages recognized by deterministic, nondeterministic, and "blind" versions of these machines are studied and compared with each other, and the associated classes for multicounter automata, automata with multiplication, and generalized finite automata.

Nondeterministic algorithmDiscrete mathematicsMatrix (mathematics)TheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGESTheoryofComputation_COMPUTATIONBYABSTRACTDEVICESFinite-state machineDimension (vector space)Computer scienceMultiplicationNonlinear Sciences::Cellular Automata and Lattice GasesComputer Science::Formal Languages and Automata TheoryAutomatonPower (physics)
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Fuzzy cooperative control of automated ground passenger vehicles

2007

In this paper a fuzzy motion control for cooperative passenger automated vehicles where there are not collisions between the closest ones is proposed. Based on the position of the target and on the initial position of each cooperative vehicle, a supervisory plans nonholonomic circular trajectories which are without intersections, while a fuzzy control strategy assures the asymptotical stability of the motion errors and the reaching of the target with low acceleration values along the planned trajectories. Based on the ISO 2631-1 standard, the saturation properties of the fuzzy maps guarantees low values of the longitudinal and lateral accelerations to assure the comfort of the passengers. T…

Nonholonomic systemEngineeringFuzzy control Automatic control Land vehicles Road vehicles Trajectory Acceleration ISO standards Motion control Motion planning Asymptotic stabilitybusiness.industryStability (learning theory)Control engineeringFuzzy control systemMotion controlFuzzy logicComputer Science::RoboticsAccelerationSettore ING-INF/04 - AutomaticaExponential stabilityControl theoryPosition (vector)business2007 IEEE Conference on Emerging Technologies & Factory Automation (EFTA 2007)
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Predictive Intelligent Fuzzy Control for Cooperative Motion of Two Nonholonomic Wheeled Cars

2007

In this paper a problem of intelligent cooperative motion control of two wheeled nonholonomic cars (target and follower) is considered. Once a target car converges to a fixed state (position and orientation), a follower car coming from different position and orientation, converges to the state above, without excessive delay between the known arrival time of the target car and the arrival time of the follower. In this sense we present a new predictive fuzzy control system. A Kalman's filter and an odometric model are used to predict the future position and orientation of the target car. The prediction above is employed to plane a circular nonholonomic reference motion for the follower car. A…

Nonholonomic systemEngineeringbusiness.industryControl engineeringFuzzy control systemKalman filterMotion controlFuzzy logicModel predictive controlSettore ING-INF/04 - AutomaticaControl theoryPosition (vector)Intelligent control Fuzzy control Motion control Kinematics Velocity control Intelligent transportation systems Delay effects Vehicle dynamics State estimation Error correctionbusinessIntelligent control2007 IEEE Intelligent Transportation Systems Conference
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