Demonstrations for Children of All Age- The Cork Canon

Demonstrations are one of the most useful techniques for teaching science to anyone, regardless of age. Demonstrations attract attention and normally make the observer want to learn more about what is happening. This paper reports on The Cork Cannon, one of the favorite demonstrations done in the demonstration road show, Phun Physics, that travels to schools within about 60 miles of Charlottesville. The Department of Physics and the Center for Science, Mathematics, and Engineering Education sponsor this demonstration show, which was seen by about 8000 persons during the last school year. Although quite simple, the Cork Cannon demonstration is rich in pedagogy and can be used to illuminate several ideas, including temperature, pressure, phase change, heat conduction, water vapor, humidity, projectile motion, air resistance, atmosphere, and kinetic theory

Challenges for Science and Mathematics Faculty

The increased science and mathematics teacher licensure requirements for K-8 teachers are clearly necessary to prepare teachers to appropriately teach the new Virginia SOLs [1]; The expectations of a program equivalent to 12 hours of science and 12 hours of mathematics for the PreK-6 endorsement and the 21 hours each of math and science to teach middle school math and science must be chosen very carefully indeed if future teachers are to be prepared to teach the specific SOL content, as well as practical applications and the use of appropriate technology“. Most Virginia colleges and universities are not currently offering the appropriate courses nor the courses taught in the appropriate manner to meet new licensure requirements. Both interdisciplinary courses and interdisciplinary degree programs may be required

An event driven algorithm for fractal cluster formation

A new cluster based event-driven algorithm is developed to simulate the formation of clusters in a two dimensional gas: particles move freely until they collide and "stick" together irreversibly. These clusters aggregate into bigger structures in an isotompic way, forming fractal structures whose fractal dimension depends on the initial density of the system

Free Cooling Phase-Diagram of Hard-Spheres with Short- and Long-Range Interactions

We study the stability, the clustering and the phase-diagram of free cooling granular gases. The systems consist of mono-disperse particles with additional non-contact (long-range) interactions, and are simulated here by the event-driven molecular dynamics algorithm with discrete (short-range shoulders or wells) potentials (in both 2D and 3D). Astonishingly good agreement is found with a mean field theory, where only the energy dissipation term is modified to account for both repulsive or attractive non-contact interactions. Attractive potentials enhance cooling and structure formation (clustering), whereas repulsive potentials reduce it, as intuition suggests. The system evolution is controlled by a single parameter: the non-contact potential strength scaled by the fluctuation kinetic energy (granular temperature). When this is small, as expected, the classical homogeneous cooling state is found. However, if the effective dissipation is strong enough, structure formation proceeds, before (in the repulsive case) non-contact forces get strong enough to undo the clustering (due to the ongoing dissipation of granular temperature). For both repulsive and attractive potentials, in the homogeneous regime, the cooling shows a universal behaviour when the (inverse) control parameter is used as evolution variable instead of time. The transition to a non-homogeneous regime, as predicted by stability analysis, is affected by both dissipation and potential strength. This can be cast into a phase diagram where the system changes with time, which leaves open many challenges for future research.Comment: 22 pages, 15 figure

The monetary-fiscal policy debate and the Andersen-Jordan equation

Monetary theory ; Monetary policy ; Econometric models

Polynomial distributed lags and the estimation of the St. Louis equation

Econometric models ; Monetary policy

M1 or M2: which is the better monetary target?

Money supply ; Monetary policy

The discount rate, interest rates and foreign exchange rates: an analysis with daily data

Interest rates ; Foreign exchange ; Federal funds rate