1,817 research outputs found
Mathematical Perceptions: Changing Mindsets in Elementary School Classrooms
In classrooms throughout the country, you can hear students moan about the difficulty in learning mathematics. This senior capstone examines the students’ mindsets about mathematics in Monterey County through the use of literature review, classroom observations, and interview with teachers. The findings reveal that students’ mindsets can be changed over time if teachers have the right tools and appropriate training to help students
Measurement of charmless semileptonic decays of B mesons
complete author list: Bartelt J.; Csorna S.; Egyed Z.; Jain V.; Akerib D.; Barish B.; Chadha M.; Chan S.; Cowen D.; Eigen G.; Miller J.; O'Grady C.; Urheim J.; Weinstein A.; Acosta D.; Athanas M.; Masek G.; Paar H.; Sivertz M.; Bean A.; Gronberg J.; Kutschke R.; Menary S.; Morrison R.; Nakanishi S.; Nelson H.; Nelson T.; Richman J.; Ryd A.; Tajima H.; Schmidt D.; Sperka D.; Witherell M.; Procario M.; Yang S.; Cho K.; Daoudi M.; Ford W.; Johnson D.; Lingel K.; Lohner M.; Rankin P.; Smith J.; Alexander J.; Bebek C.; Berkelman K.; Besson D.; Browder T.; Cassel D.; Cho H.; Coffman D.; Drell P.; Ehrlich R.; Garcia-Sciveres M.; Geiser B.; Gittelman B.; Gray S.; Hartill D.; Heltsley B.; Jones C.; Jones S.; Kandaswamy J.; Katayama N.; Kim P.; Kreinick D.; Ludwig G.; Masui J.; Mevissen J.; Mistry N.; Ng C.; Nordberg E.; Ogg M.; Patterson J.; Peterson D.; Riley D.; Salman S.; Sapper M.; Worden H.; Würthwein F.; Avery P.; Freyberger A.; Rodriguez J.; Stephens R.; Yelton J.; Cinabro D.; Henderson S.; Kinoshita K.; Liu T.; Saulnier M.; Shen F.; Wilson R.; Yamamoto H.; Ong B.; Selen M.; Sadoff A.; Ammar R.; Ball S.; Baringer P.; Coppage D.; Copty N.; Davis R.; Hancock N.; Kelly M.; Kwak N.; Lam H.; Kubota Y.; Lattery M.; Nelson J.; Patton S.; Perticone D.; Poling R.; Savinov V.; Schrenk S.; Wang R.; Alam M.; Kim I.; Nemati B.; O'Neill J.; Severini H.; Sun C.; Zoeller M.; Crawford G.; Daubenmeir M.; Fulton R.; Fujino D.; Gan K.; Honscheid K.; Kagan H.; Kass R.; Lee J.; Malchow R.; Morrow F.; Skovpen Y.; Sung M.; White C.; Whitmore J.; Wilson P.; Butler F.; Fu X.; Kalbfleisch G.; Lambrecht M.; Ross W.; Skubic P.; Snow J.; Wang P.; Wood M.; Bortoletto D.; Brown D.; Fast J.; McIlwain R.; Miao T.; Miller D.; Modesitt M.; Schaffner S.; Shibata E.; Shipsey I.; Wang P.; Battle M.; Ernst J.; Kroha H.; Roberts S.; Sparks K.; Thorndike E.; Wang C.; Chelkov V.; Dominick J.; Sanghera S.; Skwarnicki T.; Stroynowski R.; Volobouev I.; Zadorozhny P.; Artuso M.; He D.; Goldberg M.; Horwitz N.; Kennett R.; Moneti G.; Muheim F.; Mukhin Y.; Playfer S.; Rozen Y.; Stone S.; Thulasidas M.; Vasseur G.; Zhu G.; Bartelt J.; Bartelt J.</p
Characterization of Generalized Haar Spaces
AbstractWe say that a subsetGofC0(T,Rk) is rotation-invariant if {Qg:g∈G{=Gfor anyk×korthogonal matrixQ. LetGbe a rotation-invariant finite-dimensional subspace ofC0(T,Rk) on a connected, locally compact, metric spaceT. We prove thatGis a generalized Haar subspace if and only ifPG(f) is strongly unique of order 2 wheneverPG(f) is a singleton
Error Estimates and Lipschitz Constants for Best Approximation in Continuous Function Spaces
We use a structural characterization of the metric projection PG(f), from the continuous function space to its one-dimensional subspace G, to derive a lower bound of the Hausdorff strong unicity constant (or weak sharp minimum constant) for PG and then show this lower bound can be attained. Then the exact value of Lipschitz constant for PG is computed. The process is a quantitative analysis based on the Gâteaux derivative of PG, a representation of local Lipschitz constants, the equivalence of local and global Lipschitz constants for lower semicontinuous mappings, and construction of functions
Modelling (001) surfaces of II-VI semiconductors
First, we present a two-dimensional lattice gas model with anisotropic
interactions which explains the experimentally observed transition from a
dominant c(2x2) ordering of the CdTe(001) surface to a local (2x1) arrangement
of the Cd atoms as an equilibrium phase transition. Its analysis by means of
transfer-matrix and Monte Carlo techniques shows that the small energy
difference of the competing reconstructions determines to a large extent the
nature of the different phases. Then, this lattice gas is extended to a model
of a three-dimensional crystal which qualitatively reproduces many of the
characteristic features of CdTe which have been observed during sublimation and
atomic layer epitaxy.Comment: 5 pages, 3 figure
Diffusional Relaxation in Random Sequential Deposition
The effect of diffusional relaxation on the random sequential deposition
process is studied in the limit of fast deposition. Expression for the coverage
as a function of time are analytically derived for both the short-time and
long-time regimes. These results are tested and compared with numerical
simulations.Comment: 9 pages + 2 figure
Kinetics of restricted solid-on-solid models of film growth
We consider the kinetics of irreversible film growth in solid-on-solid models with various restrictions on the adsorption (or growth) sites. We show how the master equations for the probabilities of subconfigurations of filled sites can be analyzed exactly to obtain coverages and spatial correlations for the first several layers. These provide an efficient framework for analysis of the early-stage growth kinetics, and indicate rapid attainment of asymptotic behavior. We illustrate the (1+1)- and (2+1)-dimensional cases for the simplest restricted solid-on-solid condition, and various modifications
Regulation of amylase expression in Aspergillus nidulans
We report the secretion of amylase by A. nidulans R153 and repression of its expression by various carbon sources
Exact island-size distributions for submonolayer deposition: Influence of correlations between island size and separation
We determine the exact scaling form of the size distribution of islands created via homogeneous nucleation and growth during submonolayer deposition. This scaling form is shown to be controlled by the dependence on size of the propensity for islands to capture diffusing adatoms. This size dependence is determined directly from simulations. It is distinct from mean-field predictions, reflecting strong correlations between island size and separation
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