Search results for "Computation"

showing 10 items of 7362 documents

Efficient differentiation of embryonic stem cells into mesodermal precursors by BMP, retinoic acid and Notch signalling

2012

The ability to direct differentiation of mouse embryonic stem (ES) cells into specific lineages not only provides new insights into the pathways that regulate lineage selection but also has translational applications, for example in drug discovery. We set out to develop a method of differentiating ES cells into mesodermal cells at high efficiency without first having to induce embryoid body formation. ES cells were plated on a feeder layer of PA6 cells, which have membrane-associated stromal-derived inducing activity (SDIA), the molecular basis of which is currently unknown. Stimulation of ES/PA6 co-cultures with Bone Morphogenetic Protein 4 (BMP4) both favoured self-renewal of ES cells and…

Stromal cellCellular differentiationMyocytes Smooth MuscleNotch signaling pathwaylcsh:MedicineDevelopmental SignalingTretinoinEmbryoid bodyBiologyCell LineMesoderm03 medical and health sciencesMice0302 clinical medicineRetinoic Acid Signaling CascadeMolecular Cell BiologyExpressió genèticaAnimalslcsh:ScienceBiologyEmbryonic Stem Cells030304 developmental biology0303 health sciencesMultidisciplinaryReceptors NotchStem Cellslcsh:RComputational BiologyCell DifferentiationNestinSignaling in Selected DisciplinesMolecular biologyEmbryonic stem cellSignaling CascadesSignaling NetworksP19 cellBone morphogenetic protein 4embryonic structuresBone Morphogenetic Proteinslcsh:QCellular TypesStromal CellsTranscriptomeCèl·lules mare030217 neurology & neurosurgeryResearch ArticleDevelopmental BiologySignal Transduction
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Nonlocal Elastic-Damage Interface Mechanical Model

2007

The paper presents a nonlocal extension of the elastic-damage interface mechanical model, which is able to describe the effects of the spatially extended microstructure on the decohesion (or fracture) process along a surface. The key feature of the proposed model is an integral constitutive relation between tractions and displacement jumps at the interface. The presence of an integral kernel brings in the model an internal length measure, which characterizes the transition from the microscale, dominated by heterogeneities and discontinuous media, to the mesoscale, characterized as an enhanced homogenized continuum with nonlocal features. The motivations and the fields of applications of the…

Strong nonlocalityMaterials scienceDamageComputer Networks and CommunicationsControl and Systems EngineeringInterface (Java)Nonlocal mechanicComputational MechanicsThermodynamicsMechanicsDecohesionInterfaceInternal length
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Maximal Operators with Respect to the Numerical Range

2018

Let $\mathfrak{n}$ be a nonempty, proper, convex subset of $\mathbb{C}$. The $\mathfrak{n}$-maximal operators are defined as the operators having numerical ranges in $\mathfrak{n}$ and are maximal with this property. Typical examples of these are the maximal symmetric (or accretive or dissipative) operators, the associated to some sesquilinear forms (for instance, to closed sectorial forms), and the generators of some strongly continuous semi-groups of bounded operators. In this paper the $\mathfrak{n}$-maximal operators are studied and some characterizations of these in terms of the resolvent set are given.

Strongly continuous semi-groupsPure mathematicsCayley transformSesquilinear form01 natural sciencesSettore MAT/05 - Analisi MatematicaMaximal operator0103 physical sciencesFOS: Mathematics0101 mathematicsMathematics::Representation TheoryNumerical rangeMathematics47A20 47A12 47B44 47A07Resolvent setApplied Mathematics010102 general mathematicsRegular polygonOperator theoryFunctional Analysis (math.FA)Mathematics - Functional AnalysisComputational MathematicsComputational Theory and MathematicsBounded functionDissipative systemSectorStrip010307 mathematical physicsNumerical rangeComplex Analysis and Operator Theory
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Structure and function of human BMAL1–CLOCK–DNA complex

2011

Structural BiologyChemistryComputational biologyDna complexStructure and functionActa Crystallographica Section A Foundations of Crystallography
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Limited Resistance Rigid Perfectly Plastic Hinges for Steel Frames

2017

The paper concerns the proposal of a new special device for steel frames that can be utilized as external constraint as well as internal one connecting the structure beam elements. The device is designed as a rigid perfectly plastic hinge characterized by suitably chosen stiffness and resistance. Its constituting material is steel. The elastic stiffness and the limit resistance, treated as independent of each other, are fixed with the aim of satisfying special features required to the structure. The proposed device is thought as a sandwich section with wing thickness appropriately variable. Its dimensions are designed so that it can exhibit the fixed independent stiffness and limit resistan…

Structural Devices Rigid Plastic Hinges Steel Structures Elastic Properties Limit ResistanceMaterials scienceResistance (ecology)business.industryComputational MechanicsHinge020101 civil engineering02 engineering and technologyBuilding and ConstructionStructural engineering0201 civil engineering020303 mechanical engineering & transports0203 mechanical engineeringMechanics of MaterialsArchitectureSettore ICAR/08 - Scienza Delle CostruzioniSafety Risk Reliability and QualitybusinessCivil and Structural EngineeringInternational Review of Civil Engineering (IRECE)
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Are Neural Networks Imitations of Mind?

2015

Artificial neural networks are often understood as a good way to imitate mind through the web structure of neurons in brain, but the very high complexity of human brain prevents to consider neural networks as good models for human mind;anyway neural networks are good devices for computation in parallel. The difference between feed-forward and feedback neural networks is introduced; the Hopfield network and the multi-layers Perceptron are discussed. In a very weak isomorphism (not similitude) between brain and neural networks, an artificial form of short term memory and of acknowledgement, in Elman neural networks, is proposed.

Structure (mathematical logic)Artificial neural networkQuantitative Biology::Neurons and CognitionArtificial neural networkComputer sciencebusiness.industryComputationComputer Science::Neural and Evolutionary ComputationAcknowledgementShort-term memoryRecurrent networkBrainFeed-forward networkSettore M-FIL/02 - Logica E Filosofia Della ScienzaPerceptroncomputer.software_genreMindSimilitudeHopfield networkArtificial intelligenceData miningbusinesscomputer
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Talking Blockchains: The Perspective of a Database Researcher

2021

There are few topics out there, that seem to create as much confusion and discussion as blockchains. This has a multitude of reasons: (1) A large number of drastically different concepts and systems are unified under the very broad term "blockchain". (2) The topic touches a variety of different fields, including databases, distributed processing, networks, cryptography, and even economics. (3) There exists a large number of different applications of the technology.The goal of this paper is to simplify and structure the discussion of blockchain technology. We first introduce a simple formalization of the basic components, that appear again and again in a variety of blockchain systems. Second…

Structure (mathematical logic)BlockchainDatabaseDistributed databaseTransaction processingComputer sciencebusiness.industryExistential quantification010102 general mathematicsCryptography0102 computer and information sciencescomputer.software_genre01 natural sciencesVariety (cybernetics)Workflow010201 computation theory & mathematics0101 mathematicsbusinesscomputer2021 IEEE 37th International Conference on Data Engineering Workshops (ICDEW)
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The structure of atractyligenin.

1965

Structure (mathematical logic)ChemistryChemical PhenomenaComputational chemistryChemistryTerpenesOrganic ChemistryDrug DiscoveryAtractyligeninBiochemistryTetrahedron letters
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Interactive Effects of Explicit Emergent Structure: A Major Challenge for Cognitive Computational Modeling

2015

International audience; David Marr's (1982) three-level analysis of computational cognition argues for three distinct levels of cognitive information processingnamely, the computational, representational, and implementational levels. But Marr's levels areand were meant to bedescriptive, rather than interactive and dynamic. For this reason, we suggest that, had Marr been writing today, he might well have gone even farther in his analysis, including the emergence of structurein particular, explicit structure at the conceptual levelfrom lower levels, and the effect of explicit emergent structures on the level (or levels) that gave rise to them. The message is that today's cognitive scientists …

Structure (mathematical logic)Cognitive scienceFeed backLinguistics and LanguageInteractive emergenceComputer scienceActive symbolsConcept FormationCognitive NeuroscienceComputational cognitionExperimental and Cognitive PsychologyCognitionEmergenceConnectionist modelsHuman-Computer InteractionCognitionAnalogy-makingInteractive effectsArtificial Intelligence[ SDV.NEU ] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]HumansLearning[SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]Neural Networks Computer
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A computational model for motor learning in insects

2013

The aim of this paper is to propose a computational model, inspired by Drosophila melanogaster, able to handle problems related to motor learning. The role of the Mushroom Bodies and the Central Complex in solving this problem is analyzed and plausible biologically inspired models are proposed. The designed computational models have been evaluated in simulation using a dynamic structure inspired by the fruit fly. The obtained results open the way to new neurobiological experiments focused to better understand the underlined mechanisms involved, to verify the feasibility of the hypotheses formulated and the significance of the obtained results.

Structure (mathematical logic)Computational modelbiologyComputer sciencebusiness.industryComputational modelBiologically inspired modelsNeurophysiologybiology.organism_classificationDrosophila melanogasterMushroom bodiesBiologically inspired models; Computational model; Drosophila melanogasterArtificial intelligenceDrosophila melanogasterMotor learningbusiness
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