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

Island sizes and capture zone areas in submonolayer deposition: Scaling and factorization of the joint probability distribution

The joint probability distribution (JPD) for island sizes, s, and capture zone areas, A, provides extensive information on the distribution of islands formed during submonolayer deposition. For irreversible island formation via homogeneous nucleation, this JPD is shown to display scaling of the type F(s/sav,A/Aav), where “av” denotes average values. The form of F reflects both a broad monomodal distribution of island sizes, and a significant spread of capture zone areas for each island size. A key ingredient determining this scaling behavior is the impact of each nucleation event on existing capture zone areas, which we quantify by kinetic Monte Carlo simulations. Combining this characterization of the spatial aspects of nucleation with a simplified but realistic factorization ansatz for the JPD, we provide a concise rate equation formulation for the variation of both the capture zone area and the island density with island size. This is achieved by analysis of the first two moments of the evolution equations for the JPD