Search results for "computational"

showing 10 items of 5884 documents

The Role of the Anchor Atom in the Ligand of the Monolayer-Protected Au25(XR)18– Nanocluster

2015

We present a density functional theory (DFT) investigation on the role of the anchor atom and ligand on the structural, electronic, and optical properties of the anionic Au25(XR)18– nanocluster (X = S, Se, Te; R = H, CH3, and (CH2)2Ph). Substituting the anchor atom with other group 16 elements induces subtle changes in the Au–Au and Au–X bond lengths and polarization of the covalent bond. The changes in the electronic structure based on substituting both the anchor and R groups are presented through careful analysis of the density of states and theoretical determined optical spectra. We give a detailed side-by-side comparison into the structural, electronic, and optical properties of Au25(X…

ta114LigandChemistryligandsElectronic structureanchor atomsSurfaces Coatings and FilmsElectronic Optical and Magnetic MaterialsBond lengthCrystallographyGeneral EnergyCovalent bondComputational chemistryAtomMonolayerDensity of statesDensity functional theoryPhysical and Theoretical Chemistryta116gold nanoclustersJournal of Physical Chemistry C
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Crystal Structures and Density Functional Theory Calculations of o-and p-Nitroaniline Derivatives: Combined Effect of Hydrogen Bonding and aromatic i…

2013

The interplay of strong and weak hydrogen bonds, dipole–dipole interactions, and aromatic interactions of o- and p-nitroaniline derivatives was studied by combining crystal structure analysis and density functional theory (DFT) calculations. Crystal structures of four 2-nitroaniline derivatives, 2-((2-nitrophenyl)amino)ethyl methanesulfonate (1A), 2-((2-nitrophenyl)amino)ethyl 4-methylbenzenesulfonate (2A), N,N′-((1,3-phenylenebis(oxy))bis(ethane-2,1-diyl))bis(2-nitroaniline) (3A), and N-(2-chloroethyl)-2-nitroaniline (4A), and crystal structures of three 4-nitroaniline derivatives, 2-((4-nitrophenyl)amino)ethyl methanesulfonate (1B), 2-((4-nitrophenyl)amino)ethyl 4-methylbenzenesulfonate (…

ta214Ethyl methanesulfonateta114Hydrogen bondIntermolecular forceAromaticityGeneral ChemistryCrystal structureCondensed Matter PhysicsRing (chemistry)Nitroanilinechemistry.chemical_compoundCrystallographychemistryComputational chemistryGeneral Materials ScienceDensity functional theoryta116Crystal Growth and Design
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Programming, blogs and videos : are these really part of literacy?

2018

tekstitaitoopiskelijatassessmentlukeminen (toiminta)videoblogitcomputational thinkingmonilukutaitoSuomilukutaitoperuskouluohjelmointimedialukutaitoarviointiFinlandreading (activity)opetussuunnitelmat
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Distinctive attributes for predicted secondary structures at terminal sequences of non-classically secreted proteins from proteobacteria

2008

Abstract C- and N-terminal sequences (64 amino acid residues each) of 89 non-classically secreted type I, type III and type IV proteins (Swiss-Prot/TrEMBL) from proteobacteria were transformed into predicted secondary structures. Multivariate analysis of variance (MANOVA) confirmed the significance of location (C- or N-termini) and secretion type as essential factors in respect of quantitative representations of structured (a-helices, b-strands) and unstructured (coils) elements. The profiles of secondary structures were transcripted using unequal property values for helices, strands and coils and corresponding numerical vectors (independent variables) were subjected to multiple discriminan…

terminal sequencesMultiple discriminant analysisGeneral Immunology and MicrobiologybiologyQH301-705.5General Neurosciencesecondary structureComputational biologyLinear discriminant analysisbiology.organism_classificationBioinformaticsdiscriminant analysisGeneral Biochemistry Genetics and Molecular BiologyCross-validationSecretory proteinDiscriminantprotein secretionSecretionProteobacteriaBiology (General)General Agricultural and Biological SciencesProtein secondary structureproteobacteriaOpen Life Sciences
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Multi-scale modelling of heterogeneous shell structures

2011

International audience; This paper reviews multi-scale computational homogenisation frameworks for the non-linear behaviour of heterogeneous thin planar shells. Based on a review of some of the currently available methods, a computational homogenisation scheme for shells is applied on to representative volume elements for plain weave composites. The effect of flexural loading on the potential failure modes of such materials is analysed, focusing on the reinforcement-matrix delamination mechanism. The attention is next shifted toward failure localisation in masonry unit cells. Subsequently, a recently developed computational FE2 solution scheme accounting for damage localisation at structura…

thin planar shellstextile reinforced compositesmasonry[ SPI.MAT ] Engineering Sciences [physics]/Materialscomputational homogenisation[SPI.MAT] Engineering Sciences [physics]/Materials[SPI.MAT]Engineering Sciences [physics]/Materialsfailure
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IDPlanT: the Italian database of plant translocation

2021

IDPlanT is the Italian Database of Plant Translocation, an initiative of the Nature Conservation Working Group of the Italian Botanical Society. IDPlanT currently includes 185 plant translocations. The establishment of a national database on plant translocation is a key step forward in data sharing and techniques improvement in this field of plant conservation. Supplemental data for this article is available online at https://doi.org/10.1080/11263504.2021.1985004.

threatened plantAssisted colonisation; data-sharing; plant conservation; plant reintroduction; population reinforcement; threatened plantspopulation reinforcementplant reintroductionAmbientaleplant conservationChromosomal translocationPlant ScienceComputational biologyData sharingGeographyAssisted colonisationassisted colonisation data-sharing plant conservation plant reintroduction population reinforcement threatened plantsthreatened plantsdata-sharingEcology Evolution Behavior and Systematics
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A Study on the Assessment of Introductory Computational Thinking via Scratch Programming in Primary Schools

2018

Computational thinking (CT), a transversal intellectual foundation integral to computer science, is making its way into compulsory comprehensive education worldwide. Students are expected to attain skills and knowledge in such interdisciplinary CT principles as Algorithmic thinking, Data representation, and Debugging. Problem-solving by designing and manipulating interactive media with Scratch, a graphical programming tool, is popular especially at the primary school level. However, there has been confusion regarding how introductory CT can be operationalized for educational practice. Teachers and students need research-based knowledge for setting appropriate learning goals in addition to i…

tietokoneavusteinen opetusgraphical programmingComputer scienceassessment02 engineering and technologyalakouluprimary schoolFormative assessmentcomputational thinking020204 information systemsComputingMilieux_COMPUTERSANDEDUCATION0202 electrical engineering electronic engineering information engineeringMathematics educationta516computer.programming_languageVisual programming languageta113educationOperationalizationConceptualizationbusiness.industryComputational thinking05 social sciences050301 educationScratchAssessment for learningScratchohjelmointiongelmanratkaisubusiness0503 educationcomputerInteractive media
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Single-cell analysis of population context advances RNAi screening at multiple levels

2012

Isogenic cells in culture show strong variability, which arises from dynamic adaptations to the microenvironment of individual cells. Here we study the influence of the cell population context, which determines a single cell's microenvironment, in image‐based RNAi screens. We developed a comprehensive computational approach that employs Bayesian and multivariate methods at the single‐cell level. We applied these methods to 45 RNA interference screens of various sizes, including 7 druggable genome and 2 genome‐wide screens, analysing 17 different mammalian virus infections and four related cell physiological processes. Analysing cell‐based screens at this depth reveals widespread RNAi‐induce…

toImage ProcessingDruggabilityGenomeImage analysis0302 clinical medicineComputer-AssistedSX00 SystemsX.ch2604 Applied MathematicsSingle-cell analysisRNA interferenceModels2400 General Immunology and MicrobiologyImage Processing Computer-AssistedViralRNA Small Interfering0303 health scienceseducation.field_of_studyApplied MathematicsSystems BiologyGenomics10124 Institute of Molecular Life SciencesCell biologycell variabilityComputational Theory and MathematicsCellular MicroenvironmentVirus DiseasesVirusesRNA ViralRNA InterferenceSingle-Cell AnalysisGeneral Agricultural and Biological SciencesInformation SystemsSystems biologyVirus infectionPopulationContext (language use)Genomics1100 General Agricultural and Biological SciencesBiologySmall InterferingModels BiologicalGeneral Biochemistry Genetics and Molecular BiologySX08 LipidX03 medical and health sciencesViral ProteinsCell-to-cell variability; Image analysis; Population context; RNAi; Virus infection1300 General Biochemistry Genetics and Molecular BiologyHumansComputer Simulationeducation030304 developmental biologyGeneral Immunology and MicrobiologyCell-to-cell variabilityReproducibility of ResultsBayes TheoremcellBiologicalPopulation contextRNAi570 Life sciences; biologyRNA030217 neurology & neurosurgeryHeLa CellsMolecular Systems Biology
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Some Remarks about Product Spaces

2018

Summary This article covers some technical aspects about the product topology which are usually not given much of a thought in mathematics and standard literature like [7] and [6], not even by Bourbaki in [4]. Let {Ti}i∈I be a family of topological spaces. The prebasis of the product space T = ∏ i∈I Ti is defined in [5] as the set of all π −1 i (V) with i ∈ I and V open in Ti . Here it is shown that the basis generated by this prebasis consists exactly of the sets ∏ i∈I Vi with Vi open in Ti and for all but finitely many i ∈ I holds Vi = Ti . Given I = {a} we have T ≅ Ta , given I = {a, b} with a≠ b we have T ≅ Ta ×Tb . Given another family of topological spaces {Si}i∈I such that Si ≅ Ti fo…

topologyApplied Mathematics020207 software engineering02 engineering and technology54b1068t99TopologyComputational Mathematics03b35Product (mathematics)QA1-9390202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingproduct spacesMathematicsTopology (chemistry)MathematicsFormalized Mathematics
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The impact of non-dipolar magnetic fields in core-collapse supernovae

2019

The magnetic field is believed to play an important role in at least some core-collapse supernovae if its magnitude reaches $10^{15}\,\rm{G}$, which is a typical value for a magnetar. In the presence of fast rotation, such a strong magnetic field can drive powerful jet-like explosions if it has the large-scale coherence of a dipole. The topology of the magnetic field is, however, probably much more complex with strong multipolar and small-scale components and the consequences for the explosion are so far unclear. We investigate the effects of the magnetic field topology on the dynamics of core-collapse supernovae and the properties of forming proto-neutron star (PNS) by comparing pre-collap…

transients: supernovaeMHDAstrophysics::High Energy Astrophysical PhenomenaFOS: Physical sciencesCompact starMagnetar01 natural sciencesstars: magnetars0103 physical sciences010303 astronomy & astrophysicsrelativistic processesPhysicsHigh Energy Astrophysical Phenomena (astro-ph.HE)Toroid010308 nuclear & particles physicsgamma-ray burststurbulenceAstronomy and AstrophysicsRotational energyComputational physicsMagnetic fieldSupernovaDipoleSpace and Planetary ScienceMagnetohydrodynamicsAstrophysics - High Energy Astrophysical Phenomena[PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph]Monthly Notices of the Royal Astronomical Society
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