Search results for " parameters"

showing 10 items of 13235 documents

CCDC 688227: Experimental Crystal Structure Determination

2009

Related Article: G.Bentabed-Ababsa, A.Derdour, T.Roisnel, J.A.Saez, P.Perez, E.Chamorro, L.R.Domingo, F.Mongin|2009|J.Org.Chem.|74|2120|doi:10.1021/jo8027104

cis-4-(13-Benzodioxol-5-yl)-2-(4-methoxyphenyl)-3-propyl-13-oxazolidine-55-dicarbonitrileSpace GroupCrystallographyCrystal SystemCrystal StructureCell ParametersExperimental 3D Coordinates
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CCDC 628062: Experimental Crystal Structure Determination

2007

Related Article: L.Vigo, M.Risto, E.M.Jahr, T.Bajorek, R.Oilunkaniemi, R.S.Laitinen, M.Lahtinen, M.Ahlgren|2006|Cryst.Growth Des.|6|2376|doi:10.1021/cg060348r

cis-Dichloro-bis(diphenylselenyl)-platinum(ii)Space GroupCrystallographyCrystal SystemCrystal StructureCell ParametersExperimental 3D Coordinates
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CCDC 628883: Experimental Crystal Structure Determination

2007

Related Article: Francisco Estevan, Pipsa Hirva, Mercedes Sanaú, MaAngeles Úbeda|2018|Organometallics|37|2980|doi:10.1021/acs.organomet.8b00342

cis-bis(mu~2~-2-(Diphenylphosphino)phenyl)-bis(mu~2~-pivalato)-dichloro-di-palladium(ii)Space GroupCrystallographyCrystal SystemCrystal StructureCell ParametersExperimental 3D Coordinates
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CCDC 713165: Experimental Crystal Structure Determination

2009

Related Article: Francisco Estevan, Pipsa Hirva, Mercedes Sanaú, MaAngeles Úbeda|2018|Organometallics|37|2980|doi:10.1021/acs.organomet.8b00342

cis-bis(mu~2~-acetato-1kappaO:2kappaO')-dichloro-bis(mu~2~-2-(diphenylphosphino-1kappaP)phenyl-2kappaC^1^)-(mu~2~-2-(diphenylphosphino-2kappaP)phenyl-1kappaC^1^)-di-palladium(ii)Space GroupCrystallographyCrystal SystemCrystal StructureCell ParametersExperimental 3D Coordinates
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CCDC 709728: Experimental Crystal Structure Determination

2009

Related Article: I.S.Jahro, D.Onggo, Ismunandar, S.I.Rahayu, M.C.Munoz, A.B.Gaspar, M.Seredyuk, P.Gutlich, J.A.Real|2008|Inorg.Chim.Acta|361|4047|doi:10.1016/j.ica.2008.03.122

clambdacdelta-tris(2-(2-Pyridyl)quinoline)-iron(ii) diperchlorateSpace GroupCrystallographyCrystal SystemCrystal StructureCell ParametersExperimental 3D Coordinates
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CCDC 234461: Experimental Crystal Structure Determination

2006

Related Article: R.Nunez, O.Tutusaus, F.Teixidor, C.Vinas, R.Sillanpaa, R.Kivekas|2005|Chem.-Eur.J.|11|5637|doi:10.1002/chem.200500288

commo-(33'-Cobalta(ii)bis(8-(dimethylsulfido)-12-dicarbaundecaborane(10)))Space GroupCrystallographyCrystal SystemCrystal StructureCell ParametersExperimental 3D Coordinates
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Influence of Biologically Oriented Preparation Technique on Peri-Implant Tissues; Prospective Randomized Clinical Trial with Three-Year Follow-Up. Pa…

2019

Purpose: The objective of this prospective randomized clinical trial (RCT) was to analyze and compare the clinical behavior of three types of prosthesis supported by single implants in the posterior region after three years of functional loading. Materials and methods: Seventy-five implants were divided into three groups according to the type of prosthetic restoration: screw-retained crown (group GS); cemented crown without finishing line (biologically oriented preparation technique) (group GBOPT); and conventional cemented crown with finishing line (group GCC). After three years in function, clinical parameters (presence of keratinized mucosa, probing depths, bleeding on probing, and radio…

complicationsmedicine.medical_treatmentRadiographyBleeding on probingPeriDentistryProsthesisCrown (dentistry)Articlelaw.invention03 medical and health sciencesimplant-supported prosthesis0302 clinical medicineRandomized controlled triallaw0502 economics and businessmedicinebusiness.industry05 social sciencesSoft tissue030206 dentistryGeneral MedicineBOPTscrew-retainedbone loss and clinical parameterscemented050211 marketingImplantmedicine.symptombusinesssoft tissuesJournal of Clinical Medicine
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Predictive control of convex polyhedron LPV systems with Markov jumping parameters

2012

The problem of receding horizon predictive control of stochastic linear parameter varying systems is discussed. First, constant coefficient matrices are obtained at each vertex in the interior of linear parameter varying system, and then, by considering semi-definite programming constraints, weight coefficients between each vertex are calculated, and the equal coefficients matrices for the time variable system are obtained. Second, in the given receding horizon, for each mode sequence of the stochastic convex polyhedron linear parameter varying systems, the optimal control input sequences are designed in order to make the states into a terminal invariant set. Outside of the receding horizon…

convex polyhedronMarkov chainlinear parameter varying systemsLinear systemMathematicsofComputing_NUMERICALANALYSISLinear matrix inequalityOptimal controlModel predictive controlControl theoryConvex polytopeConvex optimizationMarkov jumping parametersInvariant (mathematics)predictive controlMathematics2012 24th Chinese Control and Decision Conference (CCDC)
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Wpływ wybranych parametrów na efektywność katalizowanej wanadocenem kopolimeryzacji etylenu z norbornenem i właściwości otrzymanych produktów

2019

W pracy zbadano wpływ parametrów reakcji na kopolimeryzację etylenu z norbornenem wobec katalizatora wanadocenowego (Cp2VCl2) w obecności trichloroctanu etylu (ETA). Przeprowadzono serię reakcji kopolimeryzacji, zmieniając w każdej z nich jeden z parametrów reakcji: temperaturę lub ciśnienie etylenu. Następnie zbadano temperaturę zeszklenia, stopień wbudowania norbornenu i mikrostrukturę otrzymanych kopolimerów, poddając je analizie DSC oraz spektroskopii 13C NMR. Wykazano wpływ badanych parametrów na aktywność katalizatora oraz ilość i sposób wbudowania jednostek norbornenu w łańcuch polimerowy, jak również wartość temperatury zeszklenia produktu. Stwierdzono, że właściwości otrzymanego ko…

copolymerizationkopolimer etylen/norbornenreaction parameterskatalizator wanadowyethylene/norbornene copolymervanadium catalystkopolimeryzacjanorbornenenorbornenparametry reakcji
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Flow characteristics of a channelized debris-flow and implications in numerical modelling: a study case

2012

As it is known, debris flows are characterized by extreme propagation rapidity and by the ability to move high quantity of fluid mass. Furthermore, debris flows are fluid enough to travel long distances and, thus, to cause damage in vast areas, even far from the trigger ones. Debris-flow runout estimations are important for the delineation of potentially hazardous areas. Especially in recent years, several researches have been conducted in order to define predicitive models. But, existing runout estimation methods need input parameters that can be difficult to estimate. Recent advances in theory and in experimental research have allowed the assessment of the physics of the debris flows. On …

debris flow laboratory experiment parameters
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