LIMITS OF PUBLIC POLICY EDUCATION

Teaching/Communication/Extension/Profession,

TRANSPORTATION POLICY WORKSHOP

Public Economics,

PUBLIC POLICY EDUCATION- WHOM DO WE TEACH?

Public Economics,

PUBLIC POLICY EDUCATION FOR ENVIRONMENTAL AND ECONOMIC DEVELOPMENT ISSUES

Environmental Economics and Policy,

Analysis and design of transonic airfoils using streamwise coordinates

A new approach is developed for analysis and design of transonic airfoils. A set of full potential equivalent equations in von Mises coordinates is formulated from the Euler equations under the irrotationality and isentropic assumptions. This set is composed of a main equation for the main variable, y, and a secondary equations for the secondary variable, R. The main equation is solved by type dependent differencing combined with a shock point operator. The secondary equation is solved by marching from a non-characteristic boundary. Sample computations on NACA 0012 and biconvex airfoils show that, for the analysis problem, the present approach achieves good agreement with experimental C sub p distributions. For the design problem, the approach leads to a simple numerical algorithm in which the airfoil contour is calculated as part of the flow field solution

Magnetic circular dichroism spectra from resonant and damped coupled cluster response theory

A computational expression for the Faraday A term of magnetic circular dichroism (MCD) is derived within coupled cluster response theory and alternative computational expressions for the B term are discussed. Moreover, an approach to compute the (temperature-independent) MCD ellipticity in the context of coupled cluster damped response is presented, and its equivalence with the stick-spectrum approach in the limit of infinite lifetimes is demonstrated. The damped response approach has advantages for molecular systems or spectral ranges with a high density of states. Illustrative results are reported at the coupled cluster singles and doubles level and compared to time-dependent density functional theory results.Comment: Submitted to J. Chem. Phys. on May 10, 202

Anisotropic thermal expansion of Fe1.06Te and FeTe0.5Se0.5 single crystals

Heat capacity and anisotropic thermal expansion was measured for Fe1.06Te and FeTe0.5Se0.5 single crystals. Previously reported phase transitions are clearly seen in both measurements. In both cases the thermal expansion is anisotropic. The uniaxial pressure derivatives of the superconducting transition temperature in FeTe0.5Se0.5 inferred from the Ehrenfest relation have opposite signs for in-plane and c-axis pressures. Whereas the Gruneisen parameters for both materials are similar and only weakly temperature-dependent above ~ 80 K, at low temperatures (in the magnetically ordered phase) the magnetic contribution to the Gruneisen parameter in Fe1.06Te is significantly larger than electron and phonon contributions combined

Thermal expansion in carbon nanotubes and graphene: nonequilibrium Green's function approach

The nonequilibrium Green's function method is applied to investigate the coefficient of thermal expansion (CTE) in single-walled carbon nanotubes (SWCNT) and graphene. It is found that atoms deviate about 1% from equilibrium positions at T=0 K, resulting from the interplay between quantum zero-point motion and nonlinear interaction. The CTE in SWCNT of different sizes is studied and analyzed in terms of the competition between various vibration modes. As a result of this competition, the axial CTE is positive in the whole temperature range, while the radial CTE is negative at low temperatures. In graphene, the CTE is very sensitive to the substrate. Without substrate, CTE has large negative region at low temperature and very small value at high temperature limit, and the value of CTE at T=300 K is $-6\times 10^{-6}$ K$^{-1}$ which is very close to recent experimental result, $-7\times 10^{-6}$ K$^{-1}$ (Nat. Nanotechnol. \textbf{10}, 1038 (2009)). A very weak substrate interaction (about 0.06% of the in-plane interaction) can largely reduce the negative CTE region and greatly enhance the value of CTE. If the substrate interaction is strong enough, the CTE will be positive in whole temperature range and the saturate value at high temperature reaches $2.0\times 10^{-5}$ K$^{-1}$.Comment: final version, to appear in PR

SUSY vertex algebras and supercurves

This article is a continuation of math.QA/0603633 Given a strongly conformal SUSY vertex algebra V and a supercurve X we construct a vector bundle V_X on X, the fiber of which, is isomorphic to V. Moreover, the state-field correspondence of V canonically gives rise to (local) sections of these vector bundles. We also define chiral algebras on any supercurve X, and show that the vector bundle V_X, corresponding to a SUSY vertex algebra, carries the structure of a chiral algebra.Comment: 50 page

Artificial neural networks and player recruitment in professional soccer

The aim was to objectively identify key performance indicators in professional soccer that influence outfield players’ league status using an artificial neural network. Mean technical performance data were collected from 966 outfield players’ (mean SD; age: 25 ± 4 yr, 1.81 ±) 90-minute performances in the English Football League. ProZone’s MatchViewer system and online databases were used to collect data on 347 indicators assessing the total number, accuracy and consistency of passes, tackles, possessions regained, clearances and shots. Players were assigned to one of three categories based on where they went on to complete most of their match time in the following season: group 0 (n = 209 players) went on to play in a lower soccer league, group 1 (n = 637 players) remained in the Football League Championship, and group 2 (n = 120 players) consisted of players who moved up to the English Premier League. The models created correctly predicted between 61.5% and 78.8% of the players’ league status. The model with the highest average test performance was for group 0 v 2 (U21 international caps, international caps, median tackles, percentage of first time passes unsuccessful upper quartile, maximum dribbles and possessions gained minimum) which correctly predicted 78.8% of the players’ league status with a test error of 8.3%. To date, there has not been a published example of an objective method of predicting career trajectory in soccer. This is a significant development as it highlights the potential for machine learning to be used in the scouting and recruitment process in a professional soccer environment